Programming Languages Topic of Ultimate Mastery
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Zerohack Zer0pwn Youranonnews Yevgeniy Anikin Yes Men
Zerohack Zer0Pwn YourAnonNews Yevgeniy Anikin Yes Men YamaTough Xtreme x-Leader xenu xen0nymous www.oem.com.mx www.nytimes.com/pages/world/asia/index.html www.informador.com.mx www.futuregov.asia www.cronica.com.mx www.asiapacificsecuritymagazine.com Worm Wolfy Withdrawal* WillyFoReal Wikileaks IRC 88.80.16.13/9999 IRC Channel WikiLeaks WiiSpellWhy whitekidney Wells Fargo weed WallRoad w0rmware Vulnerability Vladislav Khorokhorin Visa Inc. Virus Virgin Islands "Viewpointe Archive Services, LLC" Versability Verizon Venezuela Vegas Vatican City USB US Trust US Bankcorp Uruguay Uran0n unusedcrayon United Kingdom UnicormCr3w unfittoprint unelected.org UndisclosedAnon Ukraine UGNazi ua_musti_1905 U.S. Bankcorp TYLER Turkey trosec113 Trojan Horse Trojan Trivette TriCk Tribalzer0 Transnistria transaction Traitor traffic court Tradecraft Trade Secrets "Total System Services, Inc." Topiary Top Secret Tom Stracener TibitXimer Thumb Drive Thomson Reuters TheWikiBoat thepeoplescause the_infecti0n The Unknowns The UnderTaker The Syrian electronic army The Jokerhack Thailand ThaCosmo th3j35t3r testeux1 TEST Telecomix TehWongZ Teddy Bigglesworth TeaMp0isoN TeamHav0k Team Ghost Shell Team Digi7al tdl4 taxes TARP tango down Tampa Tammy Shapiro Taiwan Tabu T0x1c t0wN T.A.R.P. Syrian Electronic Army syndiv Symantec Corporation Switzerland Swingers Club SWIFT Sweden Swan SwaggSec Swagg Security "SunGard Data Systems, Inc." Stuxnet Stringer Streamroller Stole* Sterlok SteelAnne st0rm SQLi Spyware Spying Spydevilz Spy Camera Sposed Spook Spoofing Splendide -
Understanding the Business Ofonline Pharmaceutical Affiliate Programs
PharmaLeaks: Understanding the Business of Online Pharmaceutical Affiliate Programs Damon McCoy Andreas Pitsillidis∗ Grant Jordan∗ Nicholas Weaver∗† Christian Kreibich∗† Brian Krebs‡ Geoffrey M. Voelker∗ Stefan Savage∗ Kirill Levchenko∗ Department of Computer Science ∗Department of Computer Science and Engineering George Mason University University of California, San Diego †International Computer Science Institute ‡KrebsOnSecurity.com Berkeley, CA Abstract driven by competition between criminal organizations), a broad corpus of ground truth data has become avail- Online sales of counterfeit or unauthorized products able. In particular, in this paper we analyze the content drive a robust underground advertising industry that in- and implications of low-level databases and transactional cludes email spam, “black hat” search engine optimiza- metadata describing years of activity at the GlavMed, tion, forum abuse and so on. Virtually everyone has en- SpamIt and RX-Promotion pharmaceutical affiliate pro- countered enticements to purchase drugs, prescription- grams. By examining hundreds of thousands of orders, free, from an online “Canadian Pharmacy.” However, comprising a settled revenue totaling over US$170M, even though such sites are clearly economically moti- we are able to provide comprehensive documentation on vated, the shape of the underlying business enterprise three key aspects of underground advertising activity: is not well understood precisely because it is “under- Customers. We provide detailed analysis on the con- ground.” In this paper we exploit a rare opportunity to sumer demand for Internet-advertised counterfeit phar- view three such organizations—the GlavMed, SpamIt maceuticals, covering customer demographics, product and RX-Promotion pharmaceutical affiliate programs— selection (including an examination of drug abuse as a from the inside. -
Counterfeit Medicines and Criminal Organisations
Study report COUNTERFEIT MEDICINES AND CRIMINAL ORGANISATIONS - All rights reserved to IRACM - 2 Eric Przyswa, Research Fellow Mines ParisTech in the Centre for Research on Risks and Crises, wrote this report under the leadership and initiative of the Institute of Research against Counterfeit Medicines (IRACM). The author writes in many French and foreign academic reviews (Hermès, Futuribles, Tribune de la santé, Information and Society, etc.) and conducts research on the human safety. The report is available in its entirety on: www.iracm.com. Institut de Recherche Anti-Contrefaçon de Médicaments 54 avenue Hoche 75008 Paris - France [email protected] IRACM – September 2013 - All rights reserved to IRACM - 3 - All rights reserved to IRACM - 4 COUNTERFEIT MEDICINES AND CRIMINAL ORGANIZATIONS IRACM and Eric Przyswa - All rights reserved to IRACM - 5 Table of contents Foreword __________________________________________________________________________ 9 Introduction _______________________________________________________________________ 11 I. Medicine counterfeiting, criminal organisations and cybercrime __________________________ 13 I.1. Counterfeiting, falsification and medicines ___________________________________________ 13 I.2. State of play __________________________________________________________________ 16 In light of this assessment of counterfeit medicines, how can a more specific analysis be made of the criminal organisations involved in this ever-growing illicit trafficking? __________________________ 23 I.3. Criminal organisations -
00079-141173.Pdf (5.08
CHRIS JAY HOOFNAGLE Adjunct Full Professor School of Information School of Law Faculty Director Berkeley Center for Law & Technology August 22, 2017 University of California, Berkeley VIA THE WEB Berkeley, CA Tel: 5 Federal Trade Commission https://hoofnagle.berkeley.edu Office of the Secretary 600 Pennsylvania Avenue NW. Suite CC–5610 (Annex B) Washington, DC 20580 Re: Comment of Chris Hoofnagle on Controlling the Assault of Non-Solicited Pornography and Marketing Act (CAN–SPAM Rule, 16 CFR part 316, Project No. R711010) Dear Mr. Brown, Thank you for soliciting public comment on the CAN–SPAM Rule. My comments below focus on the need for the CAN–SPAM Rule, the costs that spam imposes on consumers and the economy, the prospect that technical interventions on intermediaries can be effective, that spam senders strategically use transaction costs to deter recipients from opting out, that senders impose privacy penalties on those who opt out, for the FTC to consider third-party lookups for email addresses to be an aggravated violation of CAN–SPAM, to revisit that the idea of a Do-Not-Email Registry, and finally, to keep the computer science literature on spam in focus. There is a Continuing Need for the CAN–SPAM Rule Because the Injuries Caused by Spam Are Economic and Social and Are on Par with Serious Crimes In a 2001 speech, FTC Chairman Timothy Muris identified spam messages as injurious under the Commission’s “harm-based” approach.1 Today, the majority of e-mail is spam. Senders of marketing e- mails can leverage the technical and economic properties of the internet to send tens of billions of messages a day. -
Detecting Web Robots with Passive Behavioral Analysis and Forced Behavior by Douglas Brewer (Under the Direction of Kang Li)
Detecting Web Robots with Passive Behavioral Analysis and Forced Behavior by Douglas Brewer (Under the direction of Kang Li) Abstract The use of web robots has exploded on today's World Wide Web (WWW). Web robots are used for various nefarious activities including click fraud, spamming, email scraping, and gaining an unfair advantage. Click fraud and unfair advantage present a way for bot writers to gain a monetary advantage. Click fraud web bots allow their authors to trick advertisement (ad) networks into paying for clicks on ads that do not belong to a human being. This costs ad networks and advertisers money they wanted to spend on advertisements for human consumption. It also affects the reputation for ad networks in the eyes of advertisers. These problems make combating web robots an important and necessary step on the WWW. Combating web robots is done by various methods that provide the means to make the distinction between bot visits and human visits. These methods involve looking at web server logs or modifying the pages on a website The enhanced log method for identifying web robots expands on previous work using web server access logs to find attributes and uses AI techniques like decision-trees and bayesian- networks for detection. Enhanced log analysis first breaks down attributes into passive and active methods; it also goes further looking at deeper levels of logging including traffic traces. This allows for previously unexplored attributes like web user agent sniffing, condi- tional comments, OS sniffing, javascript requests, and specific HTTP responses. Expanding the attribute footprint in log analysis allows for unique web bot identification. -
Internet Securitysecurity
InternetInternet SecuritySecurity #1 Final Projects Due Mon May 5 • The “automated testing” is a favor, not a necessity – PS5/7 is still due even if it is down (email me) #2 Votes • Undergrad PL Take-Home Final • Compilers Take-Home Final • Future: PA5c, PA6c? #3 One-Slide Summary • Physical security and operating system security are of critical importance and must be understood. • Key issues in internet security, including buffer overruns, virus detection, spam filtering, SQL code-injection attacks, and cross-site scripting can all be understood in terms of lexing and parsing. #4 Lecture Outline • Physical Security • Operating System Security – Privileges • Viruses and Scanning • Side Channel and Non-Control Data Attacks • Spam and Filtering • SQL Injection Attacks #6 Physical Security • It is generally accepted that anyone with physical access to a machine (i.e., anyone who can open the case) can compromise that entire machine. • Given physical access ... – How would I read your personal files? – How would I leave a backdoor (rootkit) for myself? – How would I log in as you? • Ignore networked/encrypted filesystems for now ... #7 • Them: Important user, NT box, lost admin password, sad, sad, sad. • Me: No problem, change password with magic linux disk, offline NT password editor. • Them: No, no, no. Never work. NT secure. Get real. • Me: Watch. (reboot) • Them: Gasp! This floppy is dangerous! Where did you get it? • Me: Internet. Been around forever. • Them: How do we keep students from using this? • Me: Can't. Migrate. Linux. Mac. • Them: No, no, no. Just make NT safe. • Me: Can't. NT inherently unsafe. -
Computer Security 37 8.1 Vulnerabilities
Contents 1 Antivirus software 1 1.1 History ................................................ 1 1.1.1 1949-1980 period (pre-antivirus days) ............................ 1 1.1.2 1980-1990 period (early days) ................................ 2 1.1.3 1990-2000 period (emergence of the antivirus industry) ................... 2 1.1.4 2000-2005 period ...................................... 3 1.1.5 2005 to present ........................................ 3 1.2 Identification methods ........................................ 4 1.2.1 Signature-based detection .................................. 4 1.2.2 Heuristics ........................................... 4 1.2.3 Rootkit detection ....................................... 5 1.2.4 Real-time protection ..................................... 5 1.3 Issues of concern ........................................... 5 1.3.1 Unexpected renewal costs ................................... 5 1.3.2 Rogue security applications .................................. 5 1.3.3 Problems caused by false positives .............................. 5 1.3.4 System and interoperability related issues ........................... 6 1.3.5 Effectiveness ......................................... 6 1.3.6 New viruses .......................................... 6 1.3.7 Rootkits ............................................ 6 1.3.8 Damaged files ......................................... 6 1.3.9 Firmware issues ........................................ 7 1.4 Performance and other drawbacks .................................. 7 1.5 Alternative solutions -
Botnet from Wikipedia, the Free Encyclopedia
Call for participation in WikiConference India 2011 is now open. If you wish to Speak at or conduct anything else related to Wikipedia during the conference, please submit your proposal here. Last date for submission is August 30, 2011. Botnet From Wikipedia, the free encyclopedia This article may require copy editing for grammar, style, cohesion, tone, or spelling. You can assist by editing it. (May 2011) This article needs attention from an expert on the subject. See the talk page for details. Consider associating this request with a WikiProject. (May 2011) This article needs additional citations for verification. Please help improve this article by adding reliable references. Unsourced material may be challenged and removed. (February 2008) In information technology, a botnet is a collection of compromised computers connected to the Internet, termed bots, that are used for malicious purposes. When a computer becomes compromised, it becomes a part of a botnet. Botnets are usually controlled via standards based network protocols such as IRC and http.[1] Contents [hide] 1 Background 2 Recruitment 3 Organization 4 Formation and exploitation 5 Types of attacks 6 Preventive measures 7 Historical list of botnets 8 See also 9 References 10 External links [edit] Background Bots originated as a useful tool to use without any significant malicious overtone; they were originally developed as a virtual individual that could sit in an IRC channel and perform tasks while the user was too occupied to do so.[2] Soon after the release of the first IRC bot, a few worms which exploited vulnerabilities in IRC clients began to appear. -
Syssec-D5.4-Internet-Fraud.Pdf
SEVENTH FRAMEWORK PROGRAMME Information & Communication Technologies Trustworthy ICT NETWORK OF EXCELLENCE A European Network of Excellence in Managing Threats and Vulnerabilities in the Future Internet: Europe for the World y Deliverable D5.4: Intermediate Report on Internet Fraud Abstract: This deliverable presents an overview of the current state of Internet fraud based on the research and analysis conducted in the context of WP5. It also presents the current research being performed by the SysSec consortium to gather and analyze data on the Internet fraud phenomena. Contractual Date of Delivery August 2013 Actual Date of Delivery September 2013 Deliverable Dissemination Level Public Editor Stefano Zanero, Christian Platzer Contributors All SysSec partners Quality Assurance Davide Balzarotti, Herbert Bos The SysSec consortium consists of: FORTH-ICS Coordinator Greece Politecnico Di Milano Principal Contractor Italy Vrije Universiteit Amsterdam Principal Contractor The Netherlands Institut Eur´ecom Principal Contractor France IICT-BAS Principal Contractor Bulgaria Technical University of Vienna Principal Contractor Austria Chalmers University Principal Contractor Sweden TUBITAK-BILGEM Principal Contractor Turkey y The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 257007. www.syssec-project.eu 2 September 23, 2013 Contents 1 Introduction9 2 Overview of current research on online banking and payment card fraud 11 2.1 Main Threats to Internet Banking................ 11 2.2 The Anomaly and Fraud Detection Problem.......... 13 2.2.1 Types of Anomaly..................... 14 2.2.2 Approaches to Anomaly Detection........... 15 2.3 Online Banking Fraud and Detection Systems Characteristics. 18 2.3.1 Online Banking Fraud................. -
Internet Securitysecurity
InternetInternet SecuritySecurity #1 One-Slide Summary • Physical security and operating system security are of critical importance and must be understood. • Key issues in internet security, including buffer overruns, virus detection, spam filtering, SQL code-injection attacks, and cross-site scripting can all be understood in terms of lexing and parsing. #2 High-Level Lecture Today! #3 Lecture Outline • Physical Security • Operating System Security – Privileges • Viruses and Scanning • Side Channel and Non-Control Data Attacks • Spam and Filtering • SQL Injection Attacks #4 Physical Security • It is generally accepted that anyone with physical access to a machine (i.e., anyone who can open the case) can compromise that entire machine. • Given physical access ... – How would I read your personal files? – How would I leave a backdoor (rootkit) for myself? – How would I log in as you? • Ignore networked filesystems for now ... #5 • Them: Important user, NT box, lost admin password, sad, sad, sad. • Me: No problem, change password with magic linux disk, offline NT password editor. • Them: No, no, no. Never work. NT secure. Get real. • Me: Watch. (reboot) • Them: Gasp! This floppy is dangerous! Where did you get it? • Me: Internet. Been around forever. • Them: How do we keep students from using this? • Me: Can't. Migrate. Linux. Mac. • Them: No, no, no. Just make NT safe. • Me: Can't. NT inherently unsafe. • Them: Must be safe. NT good. We have never seen problems. • Me: You just saw one now. • Them: No, no, no. NT good. Win2k better. • Me: Win2k is NT. Same thing. Should I give this floppy to a student? • Them: No, no, no. -
Spam Value Chain: Defensive Intervention Analysis
UNIVERSITY OF CALIFORNIA, SAN DIEGO Spam Value Chain: Defensive Intervention Analysis A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Computer Science by Andreas Pitsillidis Committee in charge: Professor Stefan Savage, Chair Professor Geoffrey M. Voelker, Co-Chair Professor Bill Lin Professor Ramesh Rao Professor Lawrence K. Saul 2013 Copyright Andreas Pitsillidis, 2013 All rights reserved. The dissertation of Andreas Pitsillidis is approved, and it is acceptable in quality and form for publication on microfilm and electronically: Co-Chair Chair University of California, San Diego 2013 iii DEDICATION To Dimitris, Despo and Sophia. iv TABLE OF CONTENTS Signature Page.................................. iii Dedication..................................... iv Table of Contents.................................v List of Figures.................................. vii List of Tables...................................x Acknowledgements................................ xi Vita........................................ xiii Abstract of the Dissertation........................... xv Chapter 1 Introduction............................1 1.1 Contributions........................3 1.2 Organization.........................5 Chapter 2 Background and Related Work..................7 2.1 E-mail Spam Feeds.....................8 2.2 Spamming Botnets..................... 10 2.3 Current Anti-spam Approaches.............. 12 2.4 Spam Value Chain..................... 13 2.4.1 How Modern Spam Works............