Saxe, Joshua.
Malware data science : attack detection and attribution / Joshua Saxe, Hillary Sanders. - xxvi, 243 pages : illustrations, charts ; 24 cm
Includes index.
Table of contents: Introduction --
1: Basic Static Malware Analysis --
2: Beyond Basic Static Analysis: x86 Disassembly --
3: A Brief Introduction to Dynamic Analysis --
4: Identifying Attack Campaigns Using Malware Networks --
5: Shared Code Analysis --
6: Understanding Machine Learning-Based Malware Detectors --
7: Evaluating Malware Detection Systems --
8: Building Machine Learning Detectors --
9: Visualizing Malware Trends --
10: Deep Learning Basics --
11: Building a Neural Network Malware Detector with Keras --
12: Becoming a Data Scientist
This title shows you how to apply machine learning, statistics and data visualization as you build your own detection and intelligence system. Following an overview of basic reverse engineering concepts like static and dynamic analysis, you'll learn to measure code similarities in malware samples and use machine learning frameworks like scikit-learn and Keras to build and train your own detectors.
College of Engineering and Computer Studies Bachelor of Science in Computer Science
Text in English
9781593278595 (print) 1593278594 (print) 9781593278601 (ebk.) 1593278608 (ebk.)
2018949204
Malware (Computer software)
Computer viruses.
Debugging in computer science.
Computer security.
005.84 Sa97 2018
Malware data science : attack detection and attribution / Joshua Saxe, Hillary Sanders. - xxvi, 243 pages : illustrations, charts ; 24 cm
Includes index.
Table of contents: Introduction --
1: Basic Static Malware Analysis --
2: Beyond Basic Static Analysis: x86 Disassembly --
3: A Brief Introduction to Dynamic Analysis --
4: Identifying Attack Campaigns Using Malware Networks --
5: Shared Code Analysis --
6: Understanding Machine Learning-Based Malware Detectors --
7: Evaluating Malware Detection Systems --
8: Building Machine Learning Detectors --
9: Visualizing Malware Trends --
10: Deep Learning Basics --
11: Building a Neural Network Malware Detector with Keras --
12: Becoming a Data Scientist
This title shows you how to apply machine learning, statistics and data visualization as you build your own detection and intelligence system. Following an overview of basic reverse engineering concepts like static and dynamic analysis, you'll learn to measure code similarities in malware samples and use machine learning frameworks like scikit-learn and Keras to build and train your own detectors.
College of Engineering and Computer Studies Bachelor of Science in Computer Science
Text in English
9781593278595 (print) 1593278594 (print) 9781593278601 (ebk.) 1593278608 (ebk.)
2018949204
Malware (Computer software)
Computer viruses.
Debugging in computer science.
Computer security.
005.84 Sa97 2018
