Machine Learning Resources

An Introduction to Statistical Learning, with Application in R Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani This is a great book to start learning. It offers a gentle introduction to machine learning guided by examples. It gives little for granted and the mathematical notation is not heavy. It is beginner/medium level. With the “The Elements of Statistical Learning, Data Mining, Inference, and Prediction” offers a complete description of most well-known machine learning methods. It doesn’t discuss about neural networks. The Elements of Statistical Learning, Data Mining, Inference, and Prediction Trevor Hastie, Robert Tibshirani, Jerome Friedman It is the natural continuation of the “An Introduction to Statistical Learning, with Application in R” book. This book is medium/advanced level. It offers more in depth explanation where the introduction book hide some details. The mathematical is sometimes heavy. It does cover neural network in a chapter. Petter Recognition and Machine Learning Christopher M. Bishop This is the bible of all the machine learning books. It starts from the fundamentals to build up. It offers both frequentist and bayesian views of probabilities. The explanations are well discussed and easy to follow. Deep Learning Ian Goodfellow, Yoshua Bengio, and Aaron Courville The books talks about neural networks and most of its variants. It starts from the theory needed to understand all the concepts before diving into neural networks. Given the interest in this topic and the practical applications that use this methods worldwide, it is a book worth read it. Among other, it covers convolutional, recurrent and recursive neural networks.

System Security Resources

This is a collection of system security resources that I found it interesting. Web Tangled Web, A Guide to Securing Modern Web Applications. Michal Zalewski A fantastic guide to understand the web and the browser. It starts from a historic view of the web and evolves to cover the modern world. Threat modeling Threat Modeling: Designing for Security Adam Shostack The Art of Software Security Assessment: Identifying and Preventing Software Vulnerabilities Mark Dowd, John McDonald, Justin Schuh Secure coding Secure Coding in C and C++ Robert C. Seacord A fantastic guide to really understand behind the hoods of a C/C++ program. It covers the explanations of different vulnerabilities but it does not guide you to exploit them. It covers the discussion on different coding standard, e.g., C99, OpenBSD and C11. One of the best book I have read. Exploitation Hacking, the Art of Exploitation Jon Erickson One of the bibles on exploitation. It covers shellcode, assembly, the exploitation of different vulnerabilities as well as some network and crypto attacks. Although the examples are mainly for 32 bit architecture, it is still a very good source of knowledge. The Shellcoder's Handbook: Discovering and Exploiting Security Holes Chris Anley, John Heasman, Felix Lindner, Gerardo Richarte -- Reverse engineering Practical Malware Analysis, The Hands-On Guide to Dissecting Malicious Software Michael Sikorski and Andrew Honig A good introduction -- Practical Binary Analysis, Build Your Own Linux Tools for Instrumenting, Analyzing, and Disassembling Binaries Dennis Andriesse It covers entirely the binary and its parts. It is a fairly new book and most of the examples are on 64 bit architecture. It covers also dynamic taint analysis and symbolic execution with practical tools. The IDA Pro Book, The Unofficial Guide to the World's Most Popular Disassembler Chris Eagle Practical Reverse Engineering: x86, x64, ARM, Windows Kernel, Reversing Tools, and Obfuscation Bruce Dang, Alexandre Gazet, Elias Bachaalany, S├ębastien Josse Reversing: Secrets of Reverse Engineering Eldad Eilam