Hardback : HK$1,188.00
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.
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.
1 Introduction.- 2 Binary Analysis Overview.- 3 Compiler Provenance Attribution.- 4 Library Function Identification.- 5 Identifying Reused Functions in Binary Code.- 6 Function Fingerprinting.- 7 Free Open-Source Software Fingerprinting.- 8 Clone Detection.- 9 Authorship Attribution.- 10 Conclusion.
Saed Alrabaee is an Assistant Professor at the Department of
Information Systems and Security in United Arab Emirates University
(UAEU). Prior to joining UAEU, Dr. Alrabaee was a Visiting
Assistant Professor at the Department of Electrical and Computer
Engineering and Computer Science at the University of New Haven
(UNH), US. Dr. Alrabaee holds a Ph.D. degree in information system
engineering from Concordia University in Montreal, Canada, which
was executed under the supervision of Prof. Mourad Debbabi and
Prof. Lingyu Wang. His research interests focus on the broad area
of cybersecurity, reverse engineering, including, binary authorship
attribution and characterization, malware analysis, and function
fingerprinting.
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.
PariaShirani is a PhD candidate at the Concordia Institute
for Information Systems Engineering (CIISE) at Concordia University
under the supervision of Dr. Mourad Debbabi and Dr. Lingyu Wang.
Paria received the National Science and Engineering Research
Council (NSERC) Postdoctoral Fellowships, the most prominent
postdoctoral award. During her PhD, she was awarded with Fonds de
recherche du Québec – Nature et technologies (FRQNT) Scholarship.
Paria is currently a member at the Security Research Center at
Concordia University, and has been actively working on different
topics of cybersecurity, such as software fingerprinting for
automated malicious code analysis and smart grid security. Her
research interests are in the fields of malware analysis, IoT
security, vulnerability detection, network security, and big data
analysis.
Lingyu Wang is a Professor at the Concordia Institute for
Information Systems Engineering (CIISE) at Concordia University,
Montreal,Canada. He received his Ph.D. degree in Information
Technology in 2006 from George Mason University. His research
interests include cloud computing security, SDN/NFV security,
security metrics, software security, and privacy. He has
co-authored five books, two patents, and over 120 refereed
conference and journal articles at reputable venues including TOPS,
TIFS, TDSC, TMC, JCS, S&P, CCS, NDSS, ESORICS, PETS, ICDT,
etc.
Amr Youssef is a professor at the Concordia Institute for
Information Systems Engineering (CIISE). He received his B.Sc. and
M.Sc. degrees from the Department of Electronics and Communications
Engineering, Cairo University, Egypt, in 1990 and 1993,
respectively, and the Ph.D. degree from the Electrical and Computer
Engineering Department, Queens University, Canada, in 1997. Before
joining Concordia in 2004, Dr. Youssef worked for Nortel Networks,
the Center for Applied Cryptographic Research at the University of
Waterloo, IBM, and Cairo University. His main research interests
are in the area of cryptology and network security. Dr. Youssef has
co-edited 4 books and co/authored about 200 referred papers. Dr.
Youssef has served on the Technical Program Committee of more than
60 international conferences and co-chaired the workshop on
Selected Areas in Cryptography (SAC) twice. Dr. Youssef is a
registered professional engineer (P.Eng.) in Ontario and an IEEE
senior member.
Ashkan Rahimian is a Senior Lead in security analytics at
Omnia AI, Deloitte Canada's AI practice. He has 10+ years of
experience leading productionalized security research and
development. He leads the Cyber AI product portfolio and works as a
cybersecurity and machine learning specialist. Ashkan's focus is on
the design and development of intelligence-driven security models
for predictive analytics, UEBA, and proactive threat hunting. Mr.
Rahimian holds two Master's degrees in Information Systems
Securityand Artificial Intelligence and Robotics. He conducted his
research under the supervision of Prof. Mourad Debbabi at Concordia
University, Montreal, Canada.
Lina Nouh is a Business Analyst at Deloitte Digital Middle
East, Riyadh, Saudi Arabia. She received her MAsc in Information
Systems Security in 2017 from Concordia University, Montreal,
Canada under the supervision of Prof. Mourad Debbabi and Dr. Aiman
Hanna. Lina also received her Bachelor of Science in Software
Engineering in 2014 from Concordia University, Montreal, Canada.
Lina has been always an outstanding student, which has been
recognized by receiving the prestigious Dean’s list award during
all her Bachelor’s studies.
Djedjiga Mouheb is an Assistant Professor at the Department
of Computer Science, College of Sciences at University of Sharjah,
UAE. Dr. Mouheb holds a Ph.D. degree in information system
engineering from Concordia University in Montreal, Canada, which
was executed under the supervision of Prof. Mourad Debbabi and
Prof. Lingyu Wang. Her research interests focus on cybersecurity,
including social networking security, malware analysis, software
fingerprinting, cyber-threat intelligence, secure software and
systems engineering.
He Huang is currently a software engineer at the Moody’s
Analytics Canada. He received his MAsc in Information Systems
Security from Concordia University, Montreal, Canada under the
supervision of Prof. Mourad Debbabi and Prof. Amr Youssef, and his
Bachelor of Science in Information Security from Huazhong
University of Science and Technology.
Aiman Hanna is a Professor at the Department of Computer
Science and Software Engineering at the Gina Cody School of
Engineering and Computer Science, Concordia University, Montreal,
Canada, where he has been teaching for nearly 30 years. He has been
the recipient of multiple Excellence and Outstanding Contribution
Awards, as well as the OCTAS'2009 Award, Fédération de
l'Informatique du Québec (FIQ), 2009. He has additionally been
nominated for the Prix du Ministre de l'Éducation de Quebec in
2016. Dr. Hanna is a registered Professional Engineer, and a member
of Professional Engineers Ontario (PEO), Canada. He has many years
of industrial experience working for some of the largest Canadian
firms including Bell Canada/Bell Sygma & CGI. Dr. Hanna holds Ph.D.
and M.Sc. degrees in Computer Science from Concordia University,
Montreal, Canada. His research focus is on the areas of software
security, cybersecurity, software fingerprinting, big-data and
container’s security, video conferencing, and networking and data
communications.
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