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Data Mining and Business Intelligence for Cyber Security Applications Summer Program at BGU
 
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The purpose of the Summer Program in Data Mining and Business Intelligence is to provide both theoretical and practical knowledge, including tools, on data mining. The program offers two academic courses (each for 3 credits), where students learn the basic tools of data mining and the utilization of machine learning techniques for solving cyber security problems. The program includes a mandatory one week internship at BGU’s Cyber Security Research Center. The internship corresponds with the course materials and contributes the practical experience component. In addition, students will take part in professional fieldtrips to leading companies, in order to enhance their understanding of data mining and cyber security To Apply: https://www.tfaforms.com/399172 For More information: www.bgu.ac.il/global
Views: 1315 BenGurionUniversity
Data Mining for Security - Konrad Rieck
 
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Many tasks in computer security revolve around the manual analysis of data, such as the inspection of log files or network traffic. Data mining and machine learning can help to accelerate these tasks and provides versatile tools for detecting and analyzing security data. The sesions deals with the combination of machine learning and computer security. After a short introduction to the basics of machine learning, we present common learning concepts and discuss how they are applied to security problems, such as intrusion detection, malware analysis or vulnerability discovery. I am a Professor of Computer Science at Technische Universität Braunschweig. I am leading the Institute of System Security. Prior to taking this position, I have been working at the University of Göttingen, Technische Universität Berlin and Fraunhofer Institute FIRST. My research interests revolve around computer security and machine learning. This includes the detection of computer attacks, the analysis of malicious software, and the discovery of vulnerabilities. I am also interested in efficient algorithms for analyzing structured data, such as sequences, trees and graphs. My Erdős number is 3 (Müller → Jagota → Erdős). My Bacon number is ∞, though.
Views: 865 secappdev.org
CCS 2016 Tutorial - Adversarial Data Mining: Big Data Meets Cyber Security
 
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Tutorial Lecturers: Murat Kantarcioglu, University of Texas at Dallas, US & Bowei Xi, Purdue University, US presented at CCS 2016 - the 23rd ACM Conference on Computer and Communications Security (Hofburg Palace Vienna, Austria / October 24-28, 2016) - organized by SBA Research
Views: 1571 CCS 2016
Machine Learning Fundamentals for Cybersecurity Professionals
 
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Artificial intelligence (AI) is an increasingly used component within our cybersecurity arsenal, to defend, detect, and automate incident response. Equip yourself to critically evaluate the underpinnings of next generation AI powered cybersecurity tools by understanding key machine learning (ML) algorithms, training methodologies, development options, and ML examples for attacker behaviour detection. Cut through the hyperbole and empower yourself to ask insightful and probing questions that validate or expose vendor claims around AI cybersecurity solutions. Learning Outcomes: Understand the principle operations and security applications of key ML algorithms Learn how to select appropriate ML algorithm training approaches Examine a security threat detection and ML algorithms development lifecycle Evaluate make vs buy decisions for ML in cybersecurity Learn probing questions on AI and ML that will draw out insight or demonstrate weaknesses from vendors of AI security solution
Views: 2423 Vectra AI, Inc.
FloCon 2015: Graph Based Role Mining Techniques for Cyber Security by Oler and Choudhury
 
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Watch Kiri Oler and Sutanay Choudhury of Pacific Northwest Laboratory discuss Graph Based Role Mining Techniques for Cyber Security.
Privacy-Preserving Data Mining: Methods, Metrics and Applications
 
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Privacy-Preserving Data Mining: Methods, Metrics and Applications S/W: Java , JSP, MySQL IEEE 2017-18
A Software Engineer’s Career Path into Application Security
 
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There are many different skills that are useful when creating a career in application security, and not all of them are technical.
Views: 1747 Security Innovation
#HITB2012KUL D1T1 - Chris Wysopal - Data Mining a Mountain of Vulnerabilities
 
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PRESENTATION MATERIALS: http://conference.hitb.org/hitbsecconf2012kul/materials/ PRESENTATION ABSTRACT: Every day, software developers around the world, from Bangalore to Silicon Valley, churn out millions of lines of insecure code. We used static binary analysis on thousands of applications submitted to us by large enterprises, commercial software vendors, open source projects, and software outsourcers, to create an anonymized vulnerability data set. By mining this data we can answer some interesting questions. There are significant differences in the quantity and types of vulnerabilities in software due to differences in where the software was developed, the type of software it is, in what language it was developed, and for what type of business the software was developed for. Which industries have the most secure and least secure code? What types of mistakes do developers make most often? Which languages and platforms have the apps with the most vulnerabilities? Should you be most worried of internally built apps, open source, commercial software, or outsourcers? How do latent vulnerabilities relate to those most often exploited. These questions and many more will be answered as we tunnel through vulnerability mountain. ABOUT CHRIS WYSOPAL Chris Wysopal (AKA Weld Pond), Veracode's CTO and Co-Founder, is responsible for the company's software security analysis capabilities. In 2008 he was named one of InfoWorld's Top 25 CTO's and one of the 100 most influential people in IT by eWeek. In 2010 he was named a SANS Security Thought Leader. One of the original vulnerability researchers and a member of L0pht Heavy Industries, he has testified on Capitol Hill in the US on the subjects of government computer security and how vulnerabilities are discovered in software. Chris was one of the first vulnerability researchers for web applications and Windows, publishing advisories in Lotus Domino, Cold Fusion, and Windows back in the mid 1990′s. Around the same time he also co-authored L0phtCrack, which he still sells today, and ported netcat to Windows. He graduated from Rensselaer Polytechnic Institute with a BS in Computer & Systems Engineering and is the author of "The Art of Software Security Testing" published by Addison-Wesley.
Computer Security 101 - Simple Security Tips
 
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★ http://youtube.com/runestation ➫ Subscribe ⓣ http://twitter.com/runestation ➫ Tweet me « In this video, I show how to keep your computer clean and smooth running by using free software to protect against viruses, keyloggers, or RATs. » References NOTE: Only download and use ONE anti-virus as they can conflict (Choose Avast OR Microsoft Security Essentials in the list below). Avast http://www.avast.com/en-us/index Protection Microsoft Security Essentials http://windows.microsoft.com/en-US/windows/security-essentials-download Anti-Malware Malwarebytes Anti-Malware http://www.malwarebytes.org/ Comodo Firewall http://personalfirewall.comodo.com/ CCleaner http://download.cnet.com/CCleaner/3000-18512_4-10315544.html VirusTotal http://virustotal.com Sandboxie http://www.sandboxie.com/
Views: 2178 Runestation
INTRODUCTION TO DATA MINING IN HINDI
 
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Buy Software engineering books(affiliate): Software Engineering: A Practitioner's Approach by McGraw Hill Education https://amzn.to/2whY4Ke Software Engineering: A Practitioner's Approach by McGraw Hill Education https://amzn.to/2wfEONg Software Engineering: A Practitioner's Approach (India) by McGraw-Hill Higher Education https://amzn.to/2PHiLqY Software Engineering by Pearson Education https://amzn.to/2wi2v7T Software Engineering: Principles and Practices by Oxford https://amzn.to/2PHiUL2 ------------------------------- find relevant notes at-https://viden.io/
Views: 110837 LearnEveryone
Leveraging Propagation for Data Mining: Models, Algorithms and Applications (Part 1)
 
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Authors: Naren Ramakrishnan, Department of Computer Science, Virginia Polytechnic Institute and State University B. Aditya Prakash, Department of Computer Science, Virginia Polytechnic Institute and State University Abstract: Can we infer if a user is sick from her tweet? How do opinions get formed in online forums? Which people should we immunize to prevent an epidemic as fast as possible? How do we quickly zoom out of a graph? Graphs - also known as networks - are powerful tools for modeling processes and situations of interest in real life domains of social systems, cyber-security, epidemiology, and biology. They are ubiquitous, from online social networks, gene-regulatory networks, to router graphs. This tutorial will cover recent and state-of-the-art research on how propagation-like processes can help big-data mining specifically involving large networks and time-series, algorithms behind network problems, and their practical applications in various diverse settings. Topics include diffusion and virus propagation in networks, anomaly and outbreak detection, event prediction and connections with work in public health, the web and online media, social sciences, humanities, and cyber-security. More on http://www.kdd.org/kdd2016/ KDD2016 Conference is published on http://videolectures.net/
Views: 114 KDD2016 video
Detecting Network Intrusions With Machine Learning Based Anomaly Detection Techniques
 
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Machine learning techniques used in network intrusion detection are susceptible to “model poisoning” by attackers. The speaker will dissect this attack, analyze some proposals for how to circumvent such attacks, and then consider specific use cases of how machine learning and anomaly detection can be used in the web security context. Author: Clarence Chio More: http://www.phdays.com/program/tech/40866/ Any use of this material without the express consent of Positive Technologies is prohibited.
Views: 10066 Positive Technologies
What is Web Application (Hindi)
 
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What is Web Application HTML Tutorials : http://goo.gl/O254f9 CSS Tutorials: https://goo.gl/1QNdiB SQL Tutorials: https://goo.gl/U4TcEX Check Out Our Other Playlists: https://www.youtube.com/user/GeekyShow1/playlists SUBSCRIBE to Learn Programming Language ! http://goo.gl/glkZMr Learn more about subject: http://www.geekyshows.com/ ________________________________________________ If you found this video valuable, give it a like. If you know someone who needs to see it, share it. If you have questions ask below in comment section. Add it to a playlist if you want to watch it later. ________________________________________________ T A L K W I T H M E ! Business Email: [email protected] Youtube Channel: https://www.youtube.com/c/geekyshow1 Facebook: https://www.facebook.com/GeekyShow Twitter: https://twitter.com/Geekyshow1 Google Plus: https://plus.google.com/+Geekyshowsgeek Website: http://www.geekyshows.com/ _______________________________________________ Make sure you LIKE, SUBSCRIBE, COMMENT, and REQUEST A VIDEO! :) _______________________________________________
Views: 45799 Geeky Shows
Data Science: The Engine to Power Next-Gen Cybersecurity
 
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How can you harness the power of data science to boost cyber situational awareness and proactively defend against threats? Listen as Richard Xie, our Principal Security Data Scientist, explains what security professionals need to know. Check out the white paper here: http://land.threattracksecurity.com/Data-Science-The-Engine-to-Power-Next-Generation-Cybersecurity.html
DEF CON 24 - Clarence Chio - Machine Duping 101: Pwning Deep Learning Systems
 
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Deep learning and neural networks have gained incredible popularity in recent years. The technology has grown to be the most talked-about and least well-understood branch of machine learning. Aside from it’s highly publicized victories in playing Go, numerous successful applications of deep learning in image and speech recognition has kickstarted movements to integrate it into critical fields like medical imaging and self-driving cars. In the security field, deep learning has shown good experimental results in malware/anomaly detection, APT protection, spam/phishing detection, and traffic identification. This DEF CON 101 session will guide the audience through the theory and motivations behind deep learning systems. We look at the simplest form of neural networks, then explore how variations such as convolutional neural networks and recurrent neural networks can be used to solve real problems with an unreasonable effectiveness. Then, we demonstrate that most deep learning systems are not designed with security and resiliency in mind, and can be duped by any patient attacker with a good understanding of the system. The efficacy of applications using machine learning should not only be measured with precision and recall, but also by their malleability in an adversarial setting. After diving into popular deep learning software, we show how it can be tampered with to do what you want it do, while avoiding detection by system administrators. Besides giving a technical demonstration of deep learning and its inherent shortcomings in an adversarial setting, we will focus on tampering real systems to show weaknesses in critical systems built with it. In particular, this demo-driven session will be focused on manipulating an image recognition system built with deep learning at the core, and exploring the difficulties in attacking systems in the wild. We will introduce a tool that helps deep learning hackers generate adversarial content for arbitrary machine learning systems, which can help make models more robust. By discussing defensive measures that should be put in place to prevent the class of attacks demonstrated, we hope to address the hype behind deep learning from the context of security, and look towards a more resilient future of the technology where developers can use it safely in critical deployments. Bio: Clarence Chio graduated with a B.S. and M.S. in Computer Science from Stanford, specializing in data mining and artificial intelligence. He currently works as a Security Research Engineer at Shape Security, building a product that protects high valued web assets from automated attacks. At Shape, he works on the data analysis systems used to tackle this problem. Clarence spoke on Machine Learning and Security at PHDays, BSides Las Vegas and NYC, Code Blue, SecTor, and Hack in Paris. He had been a community speaker with Intel, and is also the founder and organizer of the ‘Data Mining for Cyber Security’ meet up group, the largest gathering of security data scientists in the San Francisco Bay Area.
Views: 8754 DEFCONConference
Machine Learning and the Cloud: Disrupting Threat Detection and Prevention
 
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Mark Russinovich, Chief Technology Officer, Microsoft Azure, Microsoft Machine learning with large data sets gives unprecedented insights and anomaly detection capability. Learn how Microsoft uses the agility and scale of the cloud to protect its infrastructure and customers by applying data mining and machine learning algorithms and security domain learnings to the vast amounts of data and telemetry gathered by its many different systems and services. http://www.rsaconference.com/events/us16
Views: 8127 RSA Conference
Applied Data Science for Security Professionals
 
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Today’s security professionals encounter challenging roles. Many analysts find themselves spending time on wrestling with data and not analyzing it. Our course will teach analysts how to become more productive by using Data Science in Cyber Security. More information available at www.gtkcyber.com
Views: 1736 GTK Cyber
Cyber Security
 
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Uncover the mysteries of Cyber Theft using Centrifuge Visual Network Analysis.
Views: 1025 centrifugesystems
Building a future-proof cyber security platform with Apache Metron
 
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Qsight IT gives you insight in how we use Metron in securing our customers by continuously analyzing and monitoring users, applications, data, and networks. We show you how we implemented Metron as a replacement for our former security platform based on rule-based security. Since we are dealing with a non-conventional use case “serving many customers with one platform,” we developed a business classification module that enables us to score threats according to the customer’s input. To be future ready, we are working on extending this rule-based way of detection with machine learning models like web defacement, suspicious URL’s, UEBA, and many more to come. In order to provide all the necessary information to the SOC analysts at a glance, we are developing a custom SOC application from where they can handle security alarms, analyze captured data, and have historical data at hand. We regard our new Metron based Security Platform as an emerging giant—a future-proof cyber security platform! Speakers: Bas Van de Lustraaf, Big Data Engineer, QSight IT Michiel Van Tilborg, BI Engineer, QSight IT
Views: 1354 DataWorks Summit
Combating Advanced Cybersecurity Threats with AI & Machine Learning - Cybersecurity TiE Inflect 2018
 
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Speakers: Amit Sinha CTO, Executive Vice President of Engineering and Cloud Operations, Zscaler May Wang Co-founder & CTO ZingBox Ram Varadarajan Co-Founder & CEO Acalvio Moderator: Vijay Ganti Head of Product & ML/AI Research, Security Products VMware Advanced machine learning (ML) and artificial intelligence (AI) are the future of cybersecurity. They learn complex patterns and understand subtle interactions from oceans of diverse security telemetry data. This is critical for protecting against increasingly sophisticated attacks. This session will explore ML and AI to scale, automate, personalize and innovate solutions to combat Cybersecurity Threats. Building on the twenty-five year legacy of TiEcon, we have designed TiE Inflect 2018 to focus on the business and human impact of AI. Come and learn from the world’s best minds on how AI combined with disruptive technologies like Blockchain and IOT are radically transforming every industry including FinTech, MarTech, HealthTech and more. The future is waiting. Welcome to TiE Inflect 2018. Recorded at TiE Inflect 2018, May 4-5, 2018 tieinflect.org
Views: 582 TiE Silicon Valley
Leveraging Propagation for Data Mining: Models, Algorithms and Applications (Part 2)
 
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Authors: Naren Ramakrishnan, Department of Computer Science, Virginia Polytechnic Institute and State University B. Aditya Prakash, Department of Computer Science, Virginia Polytechnic Institute and State University Abstract: Can we infer if a user is sick from her tweet? How do opinions get formed in online forums? Which people should we immunize to prevent an epidemic as fast as possible? How do we quickly zoom out of a graph? Graphs - also known as networks - are powerful tools for modeling processes and situations of interest in real life domains of social systems, cyber-security, epidemiology, and biology. They are ubiquitous, from online social networks, gene-regulatory networks, to router graphs. This tutorial will cover recent and state-of-the-art research on how propagation-like processes can help big-data mining specifically involving large networks and time-series, algorithms behind network problems, and their practical applications in various diverse settings. Topics include diffusion and virus propagation in networks, anomaly and outbreak detection, event prediction and connections with work in public health, the web and online media, social sciences, humanities, and cyber-security. More on http://www.kdd.org/kdd2016/ KDD2016 Conference is published on http://videolectures.net/
Views: 51 KDD2016 video
Data Mining Tutorial || Mr.Narayana Reddy || Introduction And Applications - Part-1
 
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These Videos Will Make You To Perfect In Data Mining Introduction And Applications Of Data Mining ****************Subscribe For More Videos***************** Follow Me On Facebook : https://www.facebook.com/narayanaitechnologies
Cyber Security in Hindi
 
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It’s important that we each understand the risks as well as the actions we can take to help protect ourinformation and systems. Use strong passwords (combination of upper and lower case letters, numbers and special characters) and do not share passwords. if you want learn complete this course contact no-09369614263 www.aryaprofessionalacademy.com alok mishra keyboard ethical hacking cyber security social media training social media strategy social media tools social media companies social media consultant social media for small busines
Views: 113160 Alok Mishra
What is Backup and Restore - Types of Backup - Archiving - Explained - Details - In Hindi
 
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What is Backup and Restore, types of backup, archiving this is what I am going to explain you in details in Hindi. What is Backup Backup is a process of copying or archiving files and folders for the purpose of being able to restore them in case of data loss. Data loss can happen in many ways like hardware\software failure or due to any disaster or catastrophic events. There might be chances where we feel like the data we have stored might become corrupt, recently the WannaCry ransomware attacks created an havoc by encrypting the files of computer and asking for ransome. Restore is a process to copying the backed up files to the original or different location. Types of Backup There are many types of backup generally you can consider if you want to learn it more technically however main four types of backup I will explain to you. 1. Normal Backup 2. Full Backup 3. Incremental Backup 4. Differential Backup Normal backup : is nothing but just to copy paste the files from one location to another Full Backup : Full backup is the complete backup of the system. Incremental Backup : is the backup of the files and folders which has been changed since from last backup. Differential backup : is the backup of the files and folders changed since from last full backup. Backup Schedule : is the regular time or day in which backup job runs. Backup Window : is the time in which backup need to be completed. Retention Period : is the duration of time for which the backup need to be stored. Storage Device\Media : can be of many types, basically its divided in two categories disks and tapes based Archiving : is the process to backup the data and store in some location where you do not want to access it frequently Famous Backup Software and Companies Microsoft Windows : Windows Backup and Restore, NTBackup Veritas Software : Netbackup, Backup Exec HP : HP data protector IBM : IBM TSM EMC : EMC Networker etc Link to the presentation https://1drv.ms/p/s!AsyTaFuYv8zcg0klM-964ufk7oyZ Please watch the complete video for proper understanding. ----------------------------------------------------------------------------------------------------------- My ebook Real Ways to Make Money Online - E-book (Lifetime Free updates) (Rs.149) : https://goo.gl/oB95Pt Donate us to Keep Motivated paypal.me/techbulu Products I use Samson Go Mic: https://amzn.to/2LoefhP Pop filter: https://amzn.to/2uyZRJR Microsoft Office 365: https://amzn.to/2JBVP8y My phone: https://amzn.to/2uMuwCV Desktop : https://amzn.to/2JCe5yF Digital Pen: https://amzn.to/2LpvCin Share, Support, Subscribe!!! Youtube: https://www.youtube.com/c/TECHBULU Twitter: https://twitter.com/techbulu Facebook: https://www.facebook.com/techbulu/ Pinterest: https://www.pinterest.com/techbulu/ Google Plus: https://goo.gl/sZhdc0 Linkedin: https://www.linkedin.com/in/tech-bulu-15834b140/ BlogSite: http://www.techbulu.com/ About Us: TECHBULU is a YouTube Channel, where you will find technical and education videos. -----------------------------------------------------------------------------------------------------------
Views: 27162 TECH BULU
Leveraging Propagation for Data Mining: Models, Algorithms and Applications (Part 3)
 
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Authors: Naren Ramakrishnan, Department of Computer Science, Virginia Polytechnic Institute and State University B. Aditya Prakash, Department of Computer Science, Virginia Polytechnic Institute and State University Abstract: Can we infer if a user is sick from her tweet? How do opinions get formed in online forums? Which people should we immunize to prevent an epidemic as fast as possible? How do we quickly zoom out of a graph? Graphs - also known as networks - are powerful tools for modeling processes and situations of interest in real life domains of social systems, cyber-security, epidemiology, and biology. They are ubiquitous, from online social networks, gene-regulatory networks, to router graphs. This tutorial will cover recent and state-of-the-art research on how propagation-like processes can help big-data mining specifically involving large networks and time-series, algorithms behind network problems, and their practical applications in various diverse settings. Topics include diffusion and virus propagation in networks, anomaly and outbreak detection, event prediction and connections with work in public health, the web and online media, social sciences, humanities, and cyber-security. More on http://www.kdd.org/kdd2016/ KDD2016 Conference is published on http://videolectures.net/
Views: 40 KDD2016 video
Machine Learning in Cybersecurity: Fact, Fantasy, and Moving Forward
 
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Dan Liebermann, Senior Associate of Advanced Analytics, Booz Allen — In the last several years we have seen personal assistants like Alexa, self-driving cars, and automated foreign language translation all made possible by machine learning. Looking for new investment opportunities, the venture capital community has turned its attention to machine learning in cybersecurity and is investing millions of dollars into the sector. Now, nearly every product advertises machine learning, which has led to confusion between what’s real and what’s marketing. This talk will demystify machine learning in cybersecurity, separating fact from fantasy. We will discuss what machine learning is, why it is particularly challenging in cybersecurity, and how to design machine learning applications that will have the biggest impact for cyber applications. Dan Liebermann is a senior associate at Booz Allen where he leads the advanced analytics team in the firm’s commercial practice. He has thirteen years of experience leading the development and implementation of successful strategic and technical solutions in the data and analytics space. Over the course of his career he has developed advanced analytics solutions as a data scientist and analyst, and most recently has focused on helping organizations develop and stand-up their own advanced analytics capabilities across industries. Mr. Liebermann holds a master’s degree from Columbia University, a bachelor’s degree from Carnegie Mellon University, and certifications in data science, agile management, and project management. https://www.ischool.berkeley.edu/events/2018/machine-learning-cybersecurity-fact-fantasy-and-moving-forward
The Growing Threat and Impact of Web-Based Malware - Stanford Computer Security
 
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http://scpd.stanford.edu/computerSecurity/ - The way malware is being distributed has undergone a fundamental shift, with attackers focusing on planting "drive-by downloads" on legitimate sites in an automated fashion, taking advantage of vulnerabilities in hosting platforms, web applications, and structural vulnerabilities in web sites. This webinar presents data analyzing the growth of infections, and show how webmasters can take a holistic approach to preventing, detecting, containing, and recovering from such attacks. Speaker: Neil Daswani, Co-founder, Dasient, Inc.
Views: 2470 stanfordonline
2007-02-28 CERIAS - Assured Information Sharing between Trustworthy, Semi-trustworthy and Untrust...
 
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Recorded: 02/28/2007 CERIAS Security Seminar at Purdue University Assured Information Sharing between Trustworthy, Semi-trustworthy and Untrust... Bhavani Thuraisingham, The University of Texas at Dallas Data mining is the process of posing queries and extracting patterns, often previously unknown from large quantities of data using pattern matching or other reasoning techniques. Data mining has many ap-plications in security including for national security as well as for cyber security. The threats to national security include attacking buildings, destroying critical infrastructures such as power grids and telecom-munication systems. Data mining techniques are being investigated to find out who the suspicious people are and who is capable of carrying out terrorist activities. Cyber security is involved with protecting the computer and network systems against corruption due to Trojan horses, worms and viruses. Data mining is also being applied to provide solutions such as intrusion detection and auditing. The first part of the presentation will discuss my joint research with Prof. Latifur Khan and our students at the University of Texas at Dallas on data mining for cyber security applications For example; anomaly detection techniques could be used to detect unusual patterns and behaviors. Link analysis may be used to trace the viruses to the perpetrators. Classification may be used to group various cyber attacks and then use the profiles to detect an attack when it occurs. Prediction may be used to determine potential future attacks depending in a way on information learnt about terrorists through email and phone conversations. Data mining is also being applied for intrusion detection and auditing. Other applications include data mining for malicious code detection such as worm detection and managing firewall policies.This second part of the presentation will discuss the various types of threats to national security and de-scribe data mining techniques for handling such threats. Threats include non real-time threats and real-time threats. We need to understand the types of threats and also gather good data to carry out mining and obtain useful results. The challenge is to reduce false positives and false negatives. The third part of the presentation will discuss some of the research challenges. We need some form of real-time data mining, that is, the results have to be generated in real-time, we also need to build models in real-time for real-time intrusion detection. Data mining is also being applied for credit card fraud de-tection and biometrics related applications. While some progress has been made on topics such as stream data mining, there is still a lot of work to be done here. Another challenge is to mine multimedia data including surveillance video. Finally, we need to maintain the privacy of individuals. Much research has been carried out on privacy preserving data mining. In summary, the presentation will provide an overview of data mining, the various types of threats and then discuss the applications of data mining for malicious code detection and cyber security. Then we will discuss the consequences to privacy. Dr. Bhavani Thuraisingham joined The University of Texas at Dallas in October 2004 as a Professor of Computer Science and Director of the Cyber Security Research Center in the Erik Jonsson School of Engineering and Computer Science. She is an elected Fellow of three professional organizations: the IEEE (Institute for Electrical and Electronics Engineers), the AAAS (American Association for the Advancement of Science) and the BCS (British Computer Society) for her work in data security. She received the IEEE Computer Society�s prestigious 1997 Technical Achievement Award for �outstanding and innovative contributions to secure data management.�Dr Thuraisingham�s work in information security and information management has resulted in over 70 journal articles, over 200 refereed conference papers and workshops, and three US patents. She is the au-thor of seven books in data management, data mining and data security including one on data mining for counter-terrorism and another on Database and Applications Security and is completing her eighth book on Trustworthy Semantic Web. She has given over 30 keynote presentations at various technical confer-ences and has also given invited talks at the White House Office of Science and Technology Policy and at the United Nations on Data Mining for counter-terrorism. She serves (or has served) on editorial boards of leading research and industry journals and currently serves as the Editor in Chief of Computer Stan-dards and Interfaces Journal. She is also an Instructor at AFCEA�s (Armed Forces Communications and Electronics Association) Professional Development Center and has served on panels for the Air For... (Visit: www.cerias.purude.edu)
Views: 167 ceriaspurdue
Jay Jacobs on The Joys and Pains of Researching in Cybersecurity - Duo Tech Talk
 
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Abstract: When people think of data science in cybersecurity they naturally think of intrusion detection, malware identification and other “catch the hacker” analytic tools. But what if we switched focus to the defenders and looked at the decisions, policies and systems that help shape the security posture of an organization? This talk will dive into data from tens of thousands of organizations and share the insights along with the joys and pains from sifting for signal among terabytes of cybersecurity data. Speaker: Jay Jacobs is currently a Sr. Data Scientist at BitSight, and before that, he spent four years as the Lead Data Analyst on the Verizon Data Breach Investigations Report (DBIR). Jay is the Co-Author of Data Driven Security, a book covering data analysis and visualizations for information security. Jay is also a Co-Founder and Partner at Cyentia Institute, a group dedicated to advancing cybersecurity knowledge and practice through data-driven research. Host: Duo Security is a cloud-based Trusted Access provider protecting thousands of the world's largest and fastest-growing organizations, including Dresser-Rand Group, Etsy, Facebook, K-Swiss, Paramount Pictures, Random House, SuddenLink, Toyota, Twitter, Yelp, Zillow and more. Duo Security's innovative and easy-to-use technology can be quickly deployed to protect users, data and applications from breaches, credential theft and account takeover.
Views: 384 Duo Security
Hit & Miss: Student security and data mining
 
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Watch the full episode here: http://bit.ly/1lc6R3u Following the European Court's declaration that data mining is invalid, we look at the hits & misses of online privacy. Google, facing legal action for using student emails for targeted advertising, announced it is removing ad scanning from education apps. Meanwhile, Yahoo has removed the 'Do Not Track' option on their service, leading to fears users will be unable to stop targeted third party advertising, and governments possibly using it as a back door to carry on data mining. LIKE Going Underground http://fb.me/GoingUndergroundRT FOLLOW Going Underground http://twitter.com/Underground_RT FOLLOW Afshin Rattansi http://twitter.com/AfshinRattansi FOLLOW on Instagram http://instagram.com/officialgoingundergroundrt
Views: 115 goingundergroundRT
Inside Lakhshya: Meet Niveditha Cyber Security Intern
 
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Meet Niveditha Natarajan Lakhshya cybersecurity intern, describe her experience and what she gained from this program.
MIIA - Real-world Machine Learning applications in Security and Mining industries
 
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Machine Intelligence Institute of Africa (MIIA) Meetup 21 June 2017 Real-world Machine Learning applications in Security and Mining industries The meetup was sponsored by Cortex Logic and Barclays Rise. MIIA Meetup Agenda Introduction and quick MIIA update - Dr Jacques Ludik DeepAlert: Realtime Video Analytics and Alerting using Deep Learning, Dr Jasper Horrell, Founder & CEO, DeepData. Using CNNs with transfer learning to train deep networks, Shaun Irwin, M.Eng, Lead Developer, Stone Three Mining Solutions
CERIAS - 2015-04-15: Engineering Secure Computation -- Efficiently
 
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Secure Multiparty Computation offers cryptographically strong guarantees on the secrecy of data used in collaborative computing among untrusted parties. It has many important applications ranging from peer-to-peer secure auction to privacy-preserving data mining. In this talk, I will present my experience in building efficient secure computation protocols. I will also share my vision on how to blend modern cryptography and programming languages research to solve interesting cyber-security problems. About the Speaker Dr. Yan Huang is an assistant professor at Indiana University. Dr. Huang is interested in developing secure protocols, with applications in private collaborative data mining, secure cloud computing, and cyber-physical systems. His research combines techniques from systems, cryptography, and programming languages to build secure systems. He is the creator of FastGC and ObliVM, the leading software tools to build efficient secure computation applications. The tools are freely available and have been used in several research projects by both academia and industry labs world-wide. http://www.cerias.purdue.edu
Views: 108 ceriaspurdue
A Practical Beginners' Guide to Differential Privacy - CERIAS Security Seminar, Purdue University
 
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Differential privacy is a very powerful approach to protecting individual privacy in data-mining; it's also an approach that hasn't seen much application outside academic circles. There's a reason for this: many people aren't quite certain how it works. Uncertainty poses a serious problem when considering the public release of sensitive data. Intuitively, differentially private data-mining applications protect individuals by injecting noise which "covers up" the impact any individual can have on the query results. In this talk, I will discuss the concrete details of how this is accomplished, exactly what it does and does not guarantee, common mistakes and misconceptions, and give a brief overview of useful differentially privatized data-mining techniques. This talk will be accessible to researchers from all domains; no previous background in statistics or probability theory is assumed. My goal in this presentation is to offer a short-cut to researchers who would like to apply differential privacy to their work and thus enable a broader adoption of this powerful tool. About the Speaker Christine Task is a PhD candidate in the Computer Science department of Purdue University, and a member of CERIAS. She has five years experience teaching discrete math and computability theory at the undergraduate level. Her research interests are in differential privacy and its application to social network analysis, and her research advisor is CERIAS fellow Chris Clifton.
Views: 7288 ceriaspurdue
Computer Applications: An International Journal (CAIJ)
 
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Computer Applications: An International Journal (CAIJ) ISSN :2393 - 8455 http://airccse.com/caij/index.html Call for papers Computer Applications: An International Journal (CAIJ) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Computer Science Applications. The journal is devoted to the publication of high quality papers on theoretical and practical aspects of computer science applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on Computer science application advancements, and establishing new collaborations in these areas. Original research papers, state-of-the-art reviews are invited for publication in all areas of Computer Science Applications. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Computer Science Applications. Topics of interest include, but are not limited to, the following Accessible Computing Applications Algorithms and Computation theory Artificial Intelligence and Soft Computing Bioinformatics and Biosciences Computer Architecture Computer Graphics and Animation Computer Science / Information Technology Education Cryptography and Information security Data Communication and Computer Networks Data Mining and Knowledge Management Process Database Management Systems Design Automation Digital Signal and Image Processing Electronic Commerce Embedded Systems Genetic and Evolutionary Computation Health Informatics High Performance Computing Information Retrieval Internet Engineering & Web services Management Information Systems Measurement and Evaluation Micro architecture Multimedia and Applications Operating Systems Programming Languages Security, Privacy and Trust Management Simulation and Modeling Software Engineering Ubiquitous computing Wireless and Mobile networks Paper Submission Authors are invited to submit papers for this journal through E-mail: [email protected] . Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. For other details please visit http://airccse.com/caij/index.html
Views: 13 aircc journal
Computer Applications : An International Journal CAIJ
 
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Computer Applications: An International Journal (CAIJ) ISSN :2393 - 8455 http://airccse.com/caij/index.html Call for papers Computer Applications: An International Journal (CAIJ) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Computer Science Applications. The journal is devoted to the publication of high quality papers on theoretical and practical aspects of computer science applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on Computer science application advancements, and establishing new collaborations in these areas. Original research papers, state-of-the-art reviews are invited for publication in all areas of Computer Science Applications. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Computer Science Applications. Topics of interest include, but are not limited to, the following Accessible Computing Applications Algorithms and Computation theory Artificial Intelligence and Soft Computing Bioinformatics and Biosciences Computer Architecture Computer Graphics and Animation Computer Science / Information Technology Education Cryptography and Information security Data Communication and Computer Networks Data Mining and Knowledge Management Process Database Management Systems Design Automation Digital Signal and Image Processing Electronic Commerce Embedded Systems Genetic and Evolutionary Computation Health Informatics High Performance Computing Information Retrieval Internet Engineering & Web services Management Information Systems Measurement and Evaluation Micro architecture Multimedia and Applications Operating Systems Programming Languages Security, Privacy and Trust Management Simulation and Modeling Software Engineering Ubiquitous computing Wireless and Mobile networks Paper Submission Authors are invited to submit papers for this journal through E-mail: [email protected] Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal.
Facebook Data Privacy ? | Complete Information & Truth
 
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Views: 162507 Technical Sagar
KEY LOGGER - Computer Security
 
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KEY LOGGER Computer Security (2110413 – 2015 Class) Present Krerk Piromsopa, Ph.D. Assistant Professor BY Pinkaew Klaysuwan 5630433021 Rujira Jitcharoenporn 5630513521 Wipavanee Vatcharadejsakul 5631082521 Wisit Wongchaianukul 5630558821
[Hindi] Cloud Computing Explained in Detail
 
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Namaskaar Dosto, is video mein maine aapko CLOUD Computing ke baare mein bataya hai, Cloud computing kya hai, iska naam clouc computing kyu hai, aap is se kya kya kaam kar sakte hai? Aur cloud Computing ka future kya hai? yeh sabhi baatein maine aapko is video mein batayi hai. Mujhe Umeed hai ki Cloud Computing ki yeh video aapko acchi lagegi. Cloud computing ek bahut hi acchi technology hai, aur aane wale dino mein aur bhi jyada popular hone wali hai, hum sabhi aaj bhi kisi na kisi tareeke se cloud computing ka use karte hai, magar hume pata nahi hota ki hum cloud computing technology ko use kar rahe hai. Enter MEGA Giveaway here: http://bit.ly/1PPOvbc Share, Support, Subscribe!!! Subscribe: http://bit.ly/1Wfsvt4 Youtube: http://www.youtube.com/c/TechnicalGuruji Twitter: http://www.twitter.com/technicalguruji Facebook: http://www.facebook.com/technicalguruji Instagram: http://instagram.com/technicalguruji Google Plus: https://plus.google.com/+TechnicalGuruji About : Technical Guruji is a YouTube Channel, where you will find technological videos in Hindi, New Video is Posted Everyday :)
Views: 498219 Technical Guruji
Computer Applications: An International Journal (CAIJ)
 
00:11
Computer Applications: An International Journal (CAIJ) ISSN :2393 - 8455 http://airccse.com/caij/index.html Call for papers Computer Applications: An International Journal (CAIJ) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Computer Science Applications. The journal is devoted to the publication of high quality papers on theoretical and practical aspects of computer science applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on Computer science application advancements, and establishing new collaborations in these areas. Original research papers, state-of-the-art reviews are invited for publication in all areas of Computer Science Applications. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Computer Science Applications. Topics of interest include, but are not limited to, the following • Accessible Computing Applications • Algorithms and Computation theory • Artificial Intelligence and Soft Computing • Bioinformatics and Biosciences • Computer Architecture • Computer Graphics and Animation • Computer Science / Information Technology Education • Cryptography and Information security • Data Communication and Computer Networks • Data Mining and Knowledge Management Process • Database Management Systems • Design Automation • Digital Signal and Image Processing • Electronic Commerce • Embedded Systems • Genetic and Evolutionary Computation • Health Informatics • High Performance Computing • Information Retrieval • Internet Engineering & Web services • Management Information Systems • Measurement and Evaluation • Micro architecture • Multimedia and Applications • Operating Systems • Programming Languages • Security, Privacy and Trust Management • Simulation and Modeling • Software Engineering • Ubiquitous computing • Wireless and Mobile networks Paper Submission Authors are invited to submit papers for this journal through E-mail: [email protected] . Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. For other details please visit http://airccse.com/caij/index.html
Views: 22 aircc journal
CompTIA Cyber Security Analyst (CSO-001) Exam Intro Exam Training Review csa casp security plus
 
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Please support my channel by subscribing (Subscribe). With your continued support I will invest in better quality content and monthly prize drawings... Please check the video description for links for discounted services if applicable. NEW COURSE. CSA BOOTCAMP https://www.udemy.com/comptia-cybersecurity-analyst-csa-test-prep-bootcamp/?couponCode=YOUTUBE2017CSA Want some practice questions to ramp up for the exam at a discounted price! https://www.udemy.com/comptia-cybersecurity-analyst-csa-cert-practice-tests/?couponCode=YOUTUBECSAE2017 The CompTIA Cybersecurity Analyst+ examination CS0-001 is designed for IT security analysts, vulnerability analysts, or threat intelligence analysts. The exam will certify that the successful candidate has the knowledge and skills required to configure and use threat detection tools, perform data analysis, and interpret the results to identify vulnerabilities, threats, and risks to an organization with the end goal of securing and protecting applications and systems within an organization.” Cloudbursting Corp EXAM LINK https://certification.comptia.org/certifications/cybersecurity-analyst Exam Objectives Identify tools and techniques to use to perform an environmental reconnaissance of a target network or security system. Collect, analyze, and interpret security data from multiple log and monitoring sources. Use network host and web application vulnerability assessment tools and interpret the results to provide effective mitigation. Understand and remediate identity management, authentication, and access control issues. Participate in a senior role within an incident response team and use forensic tools to identify the source of an attack. Understand the use of frameworks, policies, and procedures and report on security architecture with recommendations for effective compensating controls Topic Overview Incident Response Forensic Tools Incident Analysis and Recovery Secure Network Design Managing Identities Security Frameworks Cybersecurity Analysts Reconnassiance Techniques Security Appliances Logging Vulnerabilities (Managing and Remediating) Secure Software Development Job Roles Security Analyst Security Operations Center (SOC) Analyst Vulnerability Analyst Cybersecurity Specialist Threat Intelligence Analyst Security Engineer Check out my Discounted Google Cloud Platform Architect Bootcamp. https://www.udemy.com/google-cloud-certified-professional-architect-bootcamp/?couponCode=GCPCAYOUTUBE2017 Check out my Google Cloud Platform Cloud Architect Test Prep Practice Questions. Just like the exam experience..... https://www.udemy.com/google-cloud-certified-architect-practice-questions/?couponCode=GCPCAQYOUTUBE2017 GCP Cloud Architect Exam Review. A Google Certified Professional - Cloud Architect enables organizations to leverage Google Cloud technologies. Through an understanding of cloud architecture and Google technology, this individual designs, develops, and manages robust, secure, scalable, highly available, and dynamic solutions to drive business objectives. The Cloud Architect should be proficient in all aspects of solution development including implementation details, developing prototypes, and architectural best practices. The Cloud Architect should also be experienced in microservices and multi-tiered distributed applications which span multi-cloud or hybrid environments. Check out my Cloud Architect Course on Udemy. https://www.udemy.com/become-a-high-earning-cloud-solutions-architect-bootcamp/ Check out my Litecoin(LTC) course on Udemy. https://www.udemy.com/the-complete-litecoin-crypto-currency-bootcamp/#curriculum Genesis Mining https://www.genesis-mining.com/a/1023226 and you can use "9zoi8F" in the Promo Code. Coinbase Get $10.00 in free Bitcoin... https://www.coinbase.com/join/58ba2387a66a5b0184e25d49 security plus casp ips ids
Views: 17529 The Cloud Tech Guy Joe
Computer Applications: An International Journal (CAIJ)
 
00:09
Computer Applications: An International Journal (CAIJ) ISSN :2393 - 8455 http://airccse.com/caij/index.html Call for papers Computer Applications: An International Journal (CAIJ) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Computer Science Applications. The journal is devoted to the publication of high quality papers on theoretical and practical aspects of computer science applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on Computer science application advancements, and establishing new collaborations in these areas. Original research papers, state-of-the-art reviews are invited for publication in all areas of Computer Science Applications. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Computer Science Applications. Topics of interest include, but are not limited to, the following • Accessible Computing Applications • Algorithms and Computation theory • Artificial Intelligence and Soft Computing • Bioinformatics and Biosciences • Computer Architecture • Computer Graphics and Animation • Computer Science / Information Technology Education • Cryptography and Information security • Data Communication and Computer Networks • Data Mining and Knowledge Management Process • Database Management Systems • Design Automation • Digital Signal and Image Processing • Electronic Commerce • Embedded Systems • Genetic and Evolutionary Computation • Health Informatics • High Performance Computing • Information Retrieval • Internet Engineering & Web services • Management Information Systems • Measurement and Evaluation • Micro architecture • Multimedia and Applications • Operating Systems • Programming Languages • Security, Privacy and Trust Management • Simulation and Modeling • Software Engineering • Ubiquitous computing • Wireless and Mobile network Paper Submission Authors are invited to submit papers for this journal through E-mail: [email protected] . Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. For other details please visit http://airccse.com/caij/index.html
Views: 24 aircc journal
Data Mining - Clustering
 
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What is clustering Partitioning a data into subclasses. Grouping similar objects. Partitioning the data based on similarity. Eg:Library. Clustering Types Partitioning Method Hierarchical Method Agglomerative Method Divisive Method Density Based Method Model based Method Constraint based Method These are clustering Methods or types. Clustering Algorithms,Clustering Applications and Examples are also Explained.
Nikunj Oza: "Data-driven Anomaly Detection" | Talks at Google
 
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This talk will describe recent work by the NASA Data Sciences Group on data-driven anomaly detection applied to air traffic control over Los Angeles, Denver, and New York. This data mining approach is designed to discover operationally significant flight anomalies, which were not pre-defined. These methods are complementary to traditional exceedance-based methods, in that they are more likely to yield false alarms, but they are also more likely to find previously-unknown anomalies. We discuss the discoveries that our algorithms have made that exceedance-based methods did not identify. Nikunj Oza is the leader of the Data Sciences Group at NASA Ames Research Center. He also leads a NASA project team which applies data mining to aviation safety. Dr. Ozaąs 40+ research papers represent his research interests which include data mining, machine learning, anomaly detection, and their applications to Aeronautics and Earth Science. He received the Arch T. Colwell Award for co-authoring one of the five most innovative technical papers selected from 3300+ SAE technical papers in 2005. His data mining team received the 2010 NASA Aeronautics Research Mission Directorate Associate Administratorąs Award for best technology achievements by a team. He received his B.S. in Mathematics with Computer Science from MIT in 1994, and M.S. (in 1998) and Ph.D. (in 2001) in Computer Science from the University of California at Berkeley.
Views: 7979 Talks at Google
Jerking parker learns his lesson
 
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title says it all :3 _______________________________________ airport security alarm systems anonymous proxy authentication background check background screening biometric id blackberry blogger privacy bodyguards bugged canada cctv cctv camera cctv cameras cctv security systems cctv spying cctv surveillance cell phone censorship china chinese hackers civil rights closed circuit television closed circuit tv cloud computing computer security cryptography cyber crime cyber crimes cyber security cyber security plan cybercrime cybersecurity data breach data mining data theft disclosure dna database dumpster diving education employee privacy employment screening encryption european union expectations of privacy facebook facebook groups facebook privacy facebook privacy policy fact fcra federal trade commission ferpa fraud ftc glb act google buzz google china google privacy google street view govt gps gps jammer gps tracking guidelines hackers harassment home security home surveillance identity fraud identity theft identity theft report info sharing information information security international internet internet freedom internet privacy internet privacy in china invasion of privacy laws locks locksmith locksmith services locksmiths lower merion school district malware national id national security network security new york no tech hacking nsa office of the privacy commissioner online privacy online security personal information personal protection personal security phishing phishing scams police officers privacy privacy bill privacy concerns privacy invasion privacy issues privacy laws privacy news privacy policy privacy risks privacy violation private detective private eye private information private investigator private investigators proxy server proxy servers proxy sites public information punishment red light cameras reports rfid rfid applications rfid privacy rfid tags rfid technology rogue anti spyware safety san antonio sarah palin scam artists second life security security cameras security guards security issues security risks security services security systems security technology security threats self defense social hacking social network privacy social networking social networking privacy social security number spying spyware spyware removal ssn stalking street view surveillance surveillance cameras surveillance equipment surveillance systems tax evasion technology texas threats threshold cryptography training twitter twitviewer uk spying united kingdom usb security victims video video surveillance virtual worlds virus web interview web users privacy wire tapping wiretapping Complete tag list for Privacy Blog
Views: 3254 Bombalega600