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Classroom Contents
Understanding Old Malware Tricks to Find New Malware Families
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- 1 Introduction
- 2 Who are we
- 3 Phishing
- 4 Ransomware
- 5 Normal Hunting
- 6 Common Networks
- 7 Network Size
- 8 Big Data
- 9 Machine Learning
- 10 Combining
- 11 Challenges
- 12 Muller Dynamic
- 13 Metadata
- 14 Other Changes
- 15 Basic Features
- 16 Flowbased
- 17 Bagbased
- 18 Examples
- 19 Action Recognition
- 20 Overview
- 21 Multiple Instance Learning Approach
- 22 HTML paper
- 23 Training Data
- 24 Positive Unlabeled Training
- 25 Random Product
- 26 Neural Networks
- 27 Classification Topology
- 28 Active Learning
- 29 Classification Module
- 30 Summary
- 31 Mark the relatives
- 32 Thread analyse
- 33 N stranger
- 34 Audience Changer
- 35 Source Source
- 36 Mamba
- 37 In summary
- 38 Advertising gone rogue
- 39 Traffic in the network
- 40 Second opinion
- 41 Popnet
- 42 Mapping the infrastructure
- 43 Host names
- 44 The finish
- 45 The algorithm
- 46 More campaigns
- 47 Conclusions
- 48 What got us here
- 49 Questions
- 50 Future of security
