Survey and Taxonomy of Botnet Research Through Life-Cycle
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A the Hacker
A The Hacker Madame Curie once said “En science, nous devons nous int´eresser aux choses, non aux personnes [In science, we should be interested in things, not in people].” Things, however, have since changed, and today we have to be interested not just in the facts of computer security and crime, but in the people who perpetrate these acts. Hence this discussion of hackers. Over the centuries, the term “hacker” has referred to various activities. We are familiar with usages such as “a carpenter hacking wood with an ax” and “a butcher hacking meat with a cleaver,” but it seems that the modern, computer-related form of this term originated in the many pranks and practi- cal jokes perpetrated by students at MIT in the 1960s. As an example of the many meanings assigned to this term, see [Schneier 04] which, among much other information, explains why Galileo was a hacker but Aristotle wasn’t. A hack is a person lacking talent or ability, as in a “hack writer.” Hack as a verb is used in contexts such as “hack the media,” “hack your brain,” and “hack your reputation.” Recently, it has also come to mean either a kludge, or the opposite of a kludge, as in a clever or elegant solution to a difficult problem. A hack also means a simple but often inelegant solution or technique. The following tentative definitions are quoted from the jargon file ([jargon 04], edited by Eric S. Raymond): 1. A person who enjoys exploring the details of programmable systems and how to stretch their capabilities, as opposed to most users, who prefer to learn only the minimum necessary. -
Analysis of Malware and Domain Name System Traffic
Analysis of Malware and Domain Name System Traffic Hamad Mohammed Binsalleeh A Thesis in The Department of Computer Science and Software Engineering Presented in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy at Concordia University Montréal, Québec, Canada July 2014 c Hamad Mohammed Binsalleeh, 2014 CONCORDIA UNIVERSITY Division of Graduate Studies This is to certify that the thesis prepared By: Hamad Mohammed Binsalleeh Entitled: Analysis of Malware and Domain Name System Traffic and submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy complies with the regulations of this University and meets the accepted standards with respect to originality and quality. Signed by the final examining committee: Chair Dr. Christian Moreau External Examiner Dr. Nadia Tawbi Examiner to Program Dr. Lingyu Wang Examiner Dr. Peter Grogono Examiner Dr. Olga Ormandjieva Thesis Co-Supervisor Dr. Mourad Debbabi Thesis Co-Supervisor Dr. Amr Youssef Approved by Chair of the CSE Department 2014 Dean of Engineering ABSTRACT Analysis of Malware and Domain Name System Traffic Hamad Mohammed Binsalleeh Concordia University, 2014 Malicious domains host Command and Control servers that are used to instruct in- fected machines to perpetuate malicious activities such as sending spam, stealing creden- tials, and launching denial of service attacks. Both static and dynamic analysis of malware as well as monitoring Domain Name System (DNS) traffic provide valuable insight into such malicious activities and help security experts detect and protect against many cyber attacks. Advanced crimeware toolkits were responsible for many recent cyber attacks. In order to understand the inner workings of such toolkits, we present a detailed reverse en- gineering analysis of the Zeus crimeware toolkit to unveil its underlying architecture and enable its mitigation. -
Diapositiva 1
Feliciano Intini Responsabile dei programmi di Sicurezza e Privacy di Microsoft Italia • NonSoloSecurity Blog: http://blogs.technet.com/feliciano_intini • Twitter: http://twitter.com/felicianointini 1. Introduction - Microsoft Security Intelligence Report (SIR) 2. Today‘s Threats - SIR v.8 New Findings – Italy view 3. Advancements in Software Protection and Development 4. What the Users and Industry Can Do The 8th volume of the Security Intelligence Report contains data and intelligence from the past several years, but focuses on the second half of 2009 (2H09) Full document covers Malicious Software & Potentially Unwanted Software Email, Spam & Phishing Threats Focus sections on: Malware and signed code Threat combinations Malicious Web sites Software Vulnerability Exploits Browser-based exploits Office document exploits Drive-by download attacks Security and privacy breaches Software Vulnerability Disclosures Microsoft Security Bulletins Exploitability Index Usage trends for Windows Update and Microsoft Update Microsoft Malware Protection Center (MMPC) Microsoft Security Response Center (MSRC) Microsoft Security Engineering Center (MSEC) Guidance, advice and strategies Detailed strategies, mitigations and countermeasures Fully revised and updated Guidance on protecting networks, systems and people Microsoft IT ‗real world‘ experience How Microsoft IT secures Microsoft Malware patterns around the world with deep-dive content on 26 countries and regions Data sources Malicious Software and Potentially Unwanted Software MSRT has a user base -
Proposal of N-Gram Based Algorithm for Malware Classification
SECURWARE 2011 : The Fifth International Conference on Emerging Security Information, Systems and Technologies Proposal of n-gram Based Algorithm for Malware Classification Abdurrahman Pektaş Mehmet Eriş Tankut Acarman The Scientific and Technological The Scientific and Technological Computer Engineering Dept. Research Council of Turkey Research Council of Turkey Galatasaray University National Research Institute of National Research Institute of Istanbul, Turkey Electronics and Cryptology Electronics and Cryptology e-mail:[email protected] Gebze, Turkey Gebze, Turkey e-mail:[email protected] e-mail:[email protected] Abstract— Obfuscation techniques degrade the n-gram malware used by the previous work. Similar methodologies features of binary form of the malware. In this study, have been used in source authorship, information retrieval methodology to classify malware instances by using n-gram and natural language processing [5], [6]. features of its disassembled code is presented. The presented The first known use of machine learning in malware statistical method uses the n-gram features of the malware to detection is presented by the work of Tesauro et al. in [7]. classify its instance with respect to their families. n-gram is a fixed size sliding window of byte array, where n is the size of This detection algorithm was successfully implemented in the window. The contribution of the presented method is IBM’s antivirus scanner. They used 3-grams as a feature set capability of using only one vector to represent malware and neural networks as a classification model. When the 3- subfamily which is called subfamily centroid. Using only one grams parameter is selected, the number of all n-gram vector for classification simply reduces the dimension of the n- features becomes 2563, which leads to some spacing gram space. -
An Analysis of the Asprox Botnet
An Analysis of the Asprox Botnet Ravishankar Borgaonkar Technical University of Berlin Email: [email protected] Abstract—The presence of large pools of compromised com- motives. Exploitable vulnerabilities may exist in the Internet puters, also known as botnets, or zombie armies, represents a infrastructure, in the clients and servers, in the people, and in very serious threat to Internet security. This paper describes the way money is controlled and transferred from the Internet the architecture of a contemporary advanced bot commonly known as Asprox. Asprox is a type of malware that combines into traditional cash. Many security firms and researchers are the two threat vectors of forming a botnet and of generating working on developing new methods to fight botnets and to SQL injection attacks. The main features of the Asprox botnet mitigate against threats from botnets [7], [8], [9]. are the use of centralized command and control structure, HTTP based communication, use of advanced double fast-flux service Unfortunately, there are still many questions that need to networks, use of SQL injection attacks for recruiting new bots be addressed to find effective ways of protecting against the and social engineering tricks to spread malware binaries. The threats from botnets. In order to fight against botnets in future, objective of this paper is to contribute to a deeper understanding of Asprox in particular and a better understanding of modern it is not enough to study the botnets of past. Botnets are botnet designs in general. This knowledge can be used to develop constantly evolving, and we need to understand the design more effective methods for detecting botnets, and stopping the and structure of the emerging advanced botnets. -
Detecting Botnets Using File System Indicators
Detecting botnets using file system indicators Master's thesis University of Twente Author: Committee members: Peter Wagenaar Prof. Dr. Pieter H. Hartel Dr. Damiano Bolzoni Frank Bernaards LLM (NHTCU) December 12, 2012 Abstract Botnets, large groups of networked zombie computers under centralised control, are recognised as one of the major threats on the internet. There is a lot of research towards ways of detecting botnets, in particular towards detecting Command and Control servers. Most of the research is focused on trying to detect the commands that these servers send to the bots over the network. For this research, we have looked at botnets from a botmaster's perspective. First, we characterise several botnet enhancing techniques using three aspects: resilience, stealth and churn. We see that these enhancements are usually employed in the network communications between the C&C and the bots. This leads us to our second contribution: we propose a new botnet detection method based on the way C&C's are present on the file system. We define a set of file system based indicators and use them to search for C&C's in images of hard disks. We investigate how the aspects resilience, stealth and churn apply to each of the indicators and discuss countermeasures botmasters could take to evade detection. We validate our method by applying it to a test dataset of 94 disk images, 16 of which contain C&C installations, and show that low false positive and false negative ratio's can be achieved. Approaching the botnet detection problem from this angle is novel, which provides a basis for further research. -
Pax Technica
pax technica YY6658.indb6658.indb i 22/2/15/2/15 11:15:1811:15:18 AAMM YY6658.indb6658.indb iiii 22/2/15/2/15 11:15:1811:15:18 AAMM philip n. howard pax technica how the internet of things may set us free or lock us up new haven & london YY6658.indb6658.indb iiiiii 22/2/15/2/15 11:15:1811:15:18 AAMM Published with assistance from the Mary Cady Tew Memorial Fund. Copyright © 2015 by Philip N. Howard. All rights reserved. This book may not be reproduced, in whole or in part, including illustrations, in any form (beyond that copying permitted by Sections 107 and 108 of the U.S. Copyright Law and except by reviewers for the public press), without written permission from the publishers. An online version of the work is made available under a Creative Commons license for use that is noncommercial and not derivative. The terms of the license are set forth at http://creativecommons.org/licenses/by-nc-nd/4.0/. For more information about a digital copy of the work, please see the author’s website: http://philhoward.org/. Yale University Press books may be purchased in quantity for educational, business, or promotional use. For information, please e-mail sales.press@yale .edu (U.S. offi ce) or [email protected] (U.K. offi ce). Set in Joanna type by Newgen North America, Austin, Texas. Printed in the United States of America. ISBN 978-0-300-19947-5 (cloth : alk. paper) Catalogue records for this book are available from the Library of Congress and the British Library. -
Download Slides
Scott Wu Point in time cleaning vs. RTP MSRT vs. Microsoft Security Essentials Threat events & impacts More on MSRT / Security Essentials MSRT Microsoft Windows Malicious Software Removal Tool Deployed to Windows Update, etc. monthly since 2005 On-demand scan on prevalent malware Microsoft Security Essentials Full AV RTP Inception in Oct 2009 RTP is the solution One-off cleaner has its role Quiikck response Workaround Baseline ecosystem cleaning Industrypy response & collaboration Threat Events Worms (some are bots) have longer lifespans Rogues move on quicker MarMar 2010 2010 Apr Apr 2010 2010 May May 2010 2010 Jun Jun 2010 2010 Jul Jul 2010 2010 Aug Aug 2010 2010 1,237,15 FrethogFrethog 979,427 979,427 Frethog Frethog 880,246880,246 Frethog Frethog465,351 TaterfTaterf 5 1,237,155Taterf Taterf 797,935797,935 TaterfTaterf 451,561451,561 TaterfTaterf 497,582 497,582 Taterf Taterf 393,729393,729 Taterf Taterf447,849 FrethogFrethog 535,627535,627 AlureonAlureon 493,150 493,150 AlureonAlureon 436,566 436,566 RimecudRimecud 371,646 371,646 Alureon Alureon 308,673308,673 Alureon Alureon 441,722 RimecudRimecud 341,778341,778 FrethogFrethog 473,996473,996 BubnixBubnix 348,120 348,120 HamweqHamweq 289,603 289,603 Rimecud Rimecud289,629 289,629 Rimecud Rimecud318,041 AlureonAlureon 292,810 292,810 BubnixBubnix 471,243 471,243 RimecudRimecud 287,942287,942 ConfickerConficker 286,091286, 091 Hamwe Hamweqq 250,286250, 286 Conficker Conficker220,475220, 475 ConfickerConficker 237237,348, 348 RimecudRimecud 280280,440, 440 VobfusVobfus 251251,335, 335 -
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 -
Classification of Malware Models Akriti Sethi San Jose State University
San Jose State University SJSU ScholarWorks Master's Projects Master's Theses and Graduate Research Spring 5-20-2019 Classification of Malware Models Akriti Sethi San Jose State University Follow this and additional works at: https://scholarworks.sjsu.edu/etd_projects Part of the Artificial Intelligence and Robotics Commons, and the Information Security Commons Recommended Citation Sethi, Akriti, "Classification of Malware Models" (2019). Master's Projects. 703. DOI: https://doi.org/10.31979/etd.mrqp-sur9 https://scholarworks.sjsu.edu/etd_projects/703 This Master's Project is brought to you for free and open access by the Master's Theses and Graduate Research at SJSU ScholarWorks. It has been accepted for inclusion in Master's Projects by an authorized administrator of SJSU ScholarWorks. For more information, please contact [email protected]. Classification of Malware Models A Project Presented to The Faculty of the Department of Computer Science San José State University In Partial Fulfillment of the Requirements for the Degree Master of Science by Akriti Sethi May 2019 © 2019 Akriti Sethi ALL RIGHTS RESERVED The Designated Project Committee Approves the Project Titled Classification of Malware Models by Akriti Sethi APPROVED FOR THE DEPARTMENT OF COMPUTER SCIENCE SAN JOSÉ STATE UNIVERSITY May 2019 Dr. Mark Stamp Department of Computer Science Dr. Thomas Austin Department of Computer Science Dr. Philip Heller Department of Computer Science ABSTRACT Classification of Malware Models by Akriti Sethi Automatically classifying similar malware families is a challenging problem. In this research, we attempt to classify malware families by applying machine learning to machine learning models. Specifically, we train hidden Markov models (HMM) for each malware family in our dataset. -
|||FREE||| Meltdown
MELTDOWN FREE DOWNLOAD Robert Rigby,Andy McNab | 304 pages | 01 May 2008 | Random House Children's Publishers UK | 9780552552240 | English | London, United Kingdom Meltdown and Spectre Most certainly, yes. Eee-o eleven Meltdown and Spectre Vulnerabilities in Meltdown computers leak passwords and sensitive data. Meltdown could Meltdown impact a wider Meltdown of computers than presently identified, as there is little to no variation in the microprocessor families used by Meltdown computers. Help Learn to edit Community portal Recent changes Upload file. In fact, the safety checks of said best practices actually increase the attack surface and may make applications more susceptible to Spectre. What can be leaked? Vox Media, Inc. We would Meltdown to thank Intel for awarding us with a bug bounty for the responsible disclosure process, and their professional handling of this issue through communicating a clear timeline and connecting all involved researchers. Mitigation of the vulnerability requires changes to operating Meltdown kernel code, including increased isolation of kernel memory from user-mode Meltdown. DarkSeoul CryptoLocker. Send us feedback. Life - reality at large- becomes overwhelming. Rush B Cyka Meltdown Play the game. Meltdown Note. Logos are designed by Natascha Eibl. Who reported Spectre? English Language Learners Definition of meltdown. Cloud providers Meltdown users to execute programs on the same physical servers where sensitive data might be stored, and rely Meltdown safeguards provided by the Meltdown to prevent unauthorized access to the privileged memory locations where that data is stored, a feature that the Meltdown exploit circumvents. Categories Meltdown Computer security exploits Hardware bugs Intel x86 microprocessors Side-channel attacks Speculative execution security vulnerabilities in computing X86 architecture X86 memory management. -
Ethical Hacking
Ethical Hacking Alana Maurushat University of Ottawa Press ETHICAL HACKING ETHICAL HACKING Alana Maurushat University of Ottawa Press 2019 The University of Ottawa Press (UOP) is proud to be the oldest of the francophone university presses in Canada and the only bilingual university publisher in North America. Since 1936, UOP has been “enriching intellectual and cultural discourse” by producing peer-reviewed and award-winning books in the humanities and social sciences, in French or in English. Library and Archives Canada Cataloguing in Publication Title: Ethical hacking / Alana Maurushat. Names: Maurushat, Alana, author. Description: Includes bibliographical references. Identifiers: Canadiana (print) 20190087447 | Canadiana (ebook) 2019008748X | ISBN 9780776627915 (softcover) | ISBN 9780776627922 (PDF) | ISBN 9780776627939 (EPUB) | ISBN 9780776627946 (Kindle) Subjects: LCSH: Hacking—Moral and ethical aspects—Case studies. | LCGFT: Case studies. Classification: LCC HV6773 .M38 2019 | DDC 364.16/8—dc23 Legal Deposit: First Quarter 2019 Library and Archives Canada © Alana Maurushat, 2019, under Creative Commons License Attribution— NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) https://creativecommons.org/licenses/by-nc-sa/4.0/ Printed and bound in Canada by Gauvin Press Copy editing Robbie McCaw Proofreading Robert Ferguson Typesetting CS Cover design Édiscript enr. and Elizabeth Schwaiger Cover image Fragmented Memory by Phillip David Stearns, n.d., Personal Data, Software, Jacquard Woven Cotton. Image © Phillip David Stearns, reproduced with kind permission from the artist. The University of Ottawa Press gratefully acknowledges the support extended to its publishing list by Canadian Heritage through the Canada Book Fund, by the Canada Council for the Arts, by the Ontario Arts Council, by the Federation for the Humanities and Social Sciences through the Awards to Scholarly Publications Program, and by the University of Ottawa.