About this book
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.
Cybersecurity Binary Code Analysis Digital Forensics Reverse Engineering Software Fingerprinting Malware Analysis Vulnerability Research Compiler Provenance Fingerprinting Program Provenance Analysis Function Fingerprinting Library Function Identification Vulnerability Fingerprinting Free Open-source Software Fingerprinting Function Clone Detection Reused Function Identification Authorship Attribution Static Binary Analysis
- DOI https://doi.org/10.1007/978-3-030-34238-8
- Copyright Information Springer Nature Switzerland AG 2020
- Publisher Name Springer, Cham
- eBook Packages Computer Science
- Print ISBN 978-3-030-34237-1
- Online ISBN 978-3-030-34238-8
- Series Print ISSN 1568-2633
- Series Online ISSN 2512-2193
- Buy this book on publisher's site