Binary Code Fingerprinting for Cybersecurity: Application to Malicious Code Fingerprinting: 78 (Advances in Information Security) - Tapa blanda

Acerca del autor

Mourad Debbabi is a Full Professor at the Concordia Institute for Information Systems Engineering (CIISE) and Associate Dean Research and Graduate Studies at the Gina Cody School of Engineering and Computer Science. He holds the NSERC/Hydro-Québec Thales Senior Industrial Research Chair in Smart Grid Security and the Concordia Research Chair Tier I in Information Systems Security. He is also the President of the National Cyber Forensics and Training Alliance (NCFTA) Canada, and a member of CATAAlliance's Cybercrime Advisory Council. He is the founder and one of the leaders of the Security Research Centre at Concordia University. Dr. Debbabi holds Ph.D. and M.Sc. degrees in computer science from Paris-XI Orsay, University, France. He published 3 books and more than 260 peer-reviewed research articles in international journals and conferences on cybersecurity, cyber forensics, privacy, cryptographic protocols, threat intelligence generation, malware analysis, smart grid security, reverse engineering, specification and verification of safety-critical systems, programming languages and type theory. He supervised to successful completion of 30 Ph.D. students and more than 70 Master students.

De la contraportada

This book addresses automated software fingerprinting in binary code, especially for cybersecurity applications. The reader will gain a thorough understanding of binary code analysis and several software fingerprinting techniques for cybersecurity applications, such as malware detection, vulnerability analysis, and digital forensics. More specifically, it starts with an overview of binary code analysis and its challenges, and then discusses the existing state-of-the-art approaches and their cybersecurity applications. Furthermore, it discusses and details a set of practical techniques for compiler provenance extraction, library function identification, function fingerprinting, code reuse detection, free open-source software identification, vulnerability search, and authorship attribution. It also illustrates several case studies to demonstrate the efficiency, scalability and accuracy of the above-mentioned proposed techniques and tools.
This book also introduces several innovative quantitative and qualitative techniques that synergistically leverage machine learning, program analysis, and software engineering methods to solve binary code fingerprinting problems, which are highly relevant to cybersecurity and digital forensics applications. The above-mentioned techniques are cautiously designed to gain satisfactory levels of efficiency and accuracy.
Researchers working in academia, industry and governmental agencies focusing on Cybersecurity will want to purchase this book. Software engineers and advanced-level students studying computer science, computer engineering and software engineering will also want to purchase this book.