Learn about traditional and mobile malware, the security threats they represent, state-of-the-art analysis and detection techniques, and the underground ecosystem that drives such a profitable but illegal business.
Malicious Software and its Underground Economy: Two Sides to Every Story is a short, introductory, and experimental (i.e., pilot) course featuring 6 lectures. Each lecture lasts roughly anything between 1h and 1.5h and is logically divided in a number of ~15 mins self-contained units. Although a non-negligible effort has been made to fulfill this breakdown, some units last definitely longer and require a bit more effort---just pause the video and take a break ;-)
In addition, the course features 6 multiple-choices mandatory quizzes (i.e., 1 per lecture) and 1 bonus quiz. Passing all the mandatory quizzes awards a "pass" mark of the course, while passing all the mandatory quizzes and the bonus one awards a "distinction" mark.
Malicious Software and its Underground Economy: Two Sides to Every Story
proposé par
University of London
Programme du cours : ce que vous apprendrez dans ce cours
Semaine
1Introduction
After reporting on the insights of a real-world research about a botnet takeover, students will learn about malicious software, with a particular glimpse at botnets and their detection to finally conlude brielfy with rootkits.<BR><BR><B>Lecture outline</B><BR>1. Should we care? A botnet takeover storytelling<BR>2. Admin blabbing<BR>3. Malicious software <BR>4. (a glimpse at)Botnets<BR>5. (a glimpse at) Botnets detection & Rootkits
12 vidéos (Total 115 min), 1 lecture, 1 quiz
12 vidéos
Should we care? A botnet takeover storytelling11 min
Admin blabbing 11 min
Malicious Software (part 1) 10 min
Malicious Software (part 2) 9 min
(a glimpse at) Botnets (part 1) 10 min
(a glimpse at) Botnets (part 2) 6 min
(a glimpse at) Botnets (part 3) 10 min
(a glimpse at) Botnets detection and Rootkits (part 1)8 min
(a glimpse at) Botnets detection and Rootkits (part 2)9 min
(a glimpse at) Botnets detection and Rootkits (part 3)11 min
(a glimpse at) Botnets detection and Rootkits (part 4)13 min
1 lectures
Module One Reading10 min
1 exercices pour s'entraîner
Week 1 — Quiz50 min
Semaine
2Static analysis and its limitations
Students will look at the malware landscape of the early days and what effort and challenges the AV industry was facing to fight malware threats. The lecture covers static analysis as a first technique to analyze and detect malware; (basic) assembly and reverse engineering notions are provided with a look at basic techniques to fool the state-of-the-art disassembly algorithm, quickly highlighting the limits of static analysis, especially when focused on analyzing malware. A walk-through to reverse engineer an example program concludes the lecture.<BR><BR>Given the complexity of the topic and the fact the course is a short and introductory class on a vast topic, the aim of the lecture is to provide a broad overview, with a few detailed insights wherever appropriate.<BR><BR><B>Lecture outline</b><BR><BR>1. Early days, AV industry<BR>2. (a glimpse at) Reverse engineering (part 1)<BR>3. (a glimpse at) Reverse engineering (part 2)<BR>4. (a glimpse at) Polymorphism, code obfuscation<BR>5. IDA Pro—a very simple example. . .
8 vidéos (Total 99 min), 1 lecture, 1 quiz
8 vidéos
Early days, AV industry 15 min
(a glimpse at) Reverse engineering (part 1.1) 11 min
(a glimpse at) Reverse engineering (part 1.2) 11 min
(a glimpse at) Reverse engineering (part 1.3) 8 min
(a glimpse at) Reverse engineering (part 2) 9 min
(a glimpse at) Polymorphism, code obfuscation 18 min
IDA Pro—a very simple example. . . (part 1) 10 min
IDA Pro—a very simple example. . . (part 2) 13 min
1 lectures
Module Two Reading10 min
1 exercices pour s'entraîner
Week 2 — Quiz4 min
Semaine
3Dynamic analysis and its limitations
While looking at how the malware landscape has been evolving, students will be given an introduction at dynamic analysis, a complementary technique to static analysis to fight malware threats. Packing and algorithmic-agnostic unpacking is introduced as an initial step toward full dynamic analysis. The lecture quickly mentions sandboxes and limits of dynamic analysis and sandboxes, to finally conclude with a brief overview of a particular academic research state-of-the-art for malware protection.<BR><BR>Given the complexity of the topic and the fact the course is a short and introductory class on a vast topic, the aim of the lecture is to provide a broad overview, with a few detailed insights wherever appropriate.<BR><BR><B>Lecture outline</b><BR><BR>1. Toward dynamic analysis<BR>2. (a glimpse at) Dynamic analysis (part 1)<BR>3. (a glimpse at) Dynamic analysis (part 2)<BR>4. (a glimpse at) Limits of dynamic analysisM<BR>5. AccessMiner—system-centric models
7 vidéos (Total 87 min), 1 lecture, 1 quiz
7 vidéos
Toward dynamic analysis 15 min
(a glimpse at) Dynamic analysis (part 1.1) 11 min
(a glimpse at) Dynamic analysis (part 1.2) 14 min
(a glimpse at) Dynamic analysis (part 2.1) 10 min
(a glimpse at) Dynamic analysis (part 2.2) 9 min
(a glimpse at) Limits of dynamic analysis 11 min
AccessMiner — system-centric models 15 min
1 lectures
Module Three Reading10 min
1 exercices pour s'entraîner
Week 3 — Dynamic analysis and its limitations2 min
Semaine
4Mobile malware
The lecture introduces the students to mobile malware threats; in particular, the lecture focuses on Android malware, providing a quick overview of Android applications and describing a <A href= "http://copperdroid.isg.rhul.ac.uk/">virtual machine-based dynamic analysis research</a> carried out in the <a href= "http://www.isg.rhul.ac.uk/">ISG</a> at <a href= "http://www.rhul.ac.uk/">Royal Holloway University of London</a> in collaboration with the <a href= "http://security.di.unimi.it/">LaSER</a> at <a href= "http://www.unimi.it/"> University of Milan</a>.<BR><BR><B>Lecture outline</B><BR><BR>1. Introduction<BR>2. Background<BR>3. CopperDroid: dynamic analysis of Android malware (part 1)<BR>4. CopperDroid: dynamic analysis of Android malware (part 2)
4 vidéos (Total 49 min), 1 lecture, 1 quiz
4 vidéos
Introduction 10 min
Background 12 min
Dynamic analysis of Android malware (part 1) 15 min
Dynamic analysis of Android malware (part 2) 10 min
1 lectures
Module Four Reading10 min
1 exercices pour s'entraîner
Week 4 — Mobile malware52 min
Enseignants
Dr Lorenzo Cavallaro
Reader (Associate Professor)Information Security Group, Royal Holloway, University of London
À propos de University of London
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