LEADER 03672nam 2200457 450 001 9910818966703321 005 20200520144314.0 010 $a1-78899-311-X 035 $a(CKB)4100000004975138 035 $a(Au-PeEL)EBL5439458 035 $a(OCoLC)1043629671 035 $a(CaSebORM)9781788997409 035 $a(MiAaPQ)EBC5439458 035 $a(PPN)23339690X 035 $a(EXLCZ)994100000004975138 100 $a20180721d2018 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMastering machine learning for penetration testing $edevelop an extensive skill set to break self-learning systems using Python /$fChiheb Chebbi 205 $a1st edition 210 1$aBirmingham :$cPackt,$d2018. 215 $a1 online resource (264 pages) 311 $a1-78899-740-9 320 $aIncludes bibliographical references. 330 $aBecome a master at penetration testing using machine learning with Python About This Book Identify ambiguities and breach intelligent security systems Perform unique cyber attacks to breach robust systems Learn to leverage machine learning algorithms Who This Book Is For This book is for pen testers and security professionals who are interested in learning techniques to break an intelligent security system. Basic knowledge of Python is needed, but no prior knowledge of machine learning is necessary. What You Will Learn Take an in-depth look at machine learning Get to know natural language processing (NLP) Understand malware feature engineering Build generative adversarial networks using Python libraries Work on threat hunting with machine learning and the ELK stack Explore the best practices for machine learning In Detail Cyber security is crucial for both businesses and individuals. As systems are getting smarter, we now see machine learning interrupting computer security. With the adoption of machine learning in upcoming security products, it's important for pentesters and security researchers to understand how these systems work, and to breach them for testing purposes. This book begins with the basics of machine learning and the algorithms used to build robust systems. Once you've gained a fair understanding of how security products leverage machine learning, you'll dive into the core concepts of breaching such systems. Through practical use cases, you'll see how to find loopholes and surpass a self-learning security system. As you make your way through the chapters, you'll focus on topics such as network intrusion detection and AV and IDS evasion. We'll also cover the best practices when identifying ambiguities, and extensive techniques to breach an intelligent system. By the end of this book, you will be well-versed with identifying loopholes in a self-learning security system and will be able to efficiently breach a machine learning system. Style and approach This book takes a step-by-step approach to identify the loop holes in a self-learning security system. You will be able to efficiently breach a machine learning system with the help of best practices towards the end of the book. 606 $aPython (Computer program language) 606 $aPenetration testing (Computer security) 615 0$aPython (Computer program language) 615 0$aPenetration testing (Computer security) 676 $a005.133 700 $aChebbi$b Chiheb$01653240 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910818966703321 996 $aMastering machine learning for penetration testing$94079669 997 $aUNINA