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Author: Mark Stamp Publisher: Springer Nature ISBN: 3030625826 Category : Computers Languages : en Pages : 651
Book Description
This book is focused on the use of deep learning (DL) and artificial intelligence (AI) as tools to advance the fields of malware detection and analysis. The individual chapters of the book deal with a wide variety of state-of-the-art AI and DL techniques, which are applied to a number of challenging malware-related problems. DL and AI based approaches to malware detection and analysis are largely data driven and hence minimal expert domain knowledge of malware is needed. This book fills a gap between the emerging fields of DL/AI and malware analysis. It covers a broad range of modern and practical DL and AI techniques, including frameworks and development tools enabling the audience to innovate with cutting-edge research advancements in a multitude of malware (and closely related) use cases.
Author: Mark Stamp Publisher: Springer Nature ISBN: 3030625826 Category : Computers Languages : en Pages : 651
Book Description
This book is focused on the use of deep learning (DL) and artificial intelligence (AI) as tools to advance the fields of malware detection and analysis. The individual chapters of the book deal with a wide variety of state-of-the-art AI and DL techniques, which are applied to a number of challenging malware-related problems. DL and AI based approaches to malware detection and analysis are largely data driven and hence minimal expert domain knowledge of malware is needed. This book fills a gap between the emerging fields of DL/AI and malware analysis. It covers a broad range of modern and practical DL and AI techniques, including frameworks and development tools enabling the audience to innovate with cutting-edge research advancements in a multitude of malware (and closely related) use cases.
Author: Mihai Christodorescu Publisher: Springer Science & Business Media ISBN: 0387445994 Category : Computers Languages : en Pages : 307
Book Description
This book captures the state of the art research in the area of malicious code detection, prevention and mitigation. It contains cutting-edge behavior-based techniques to analyze and detect obfuscated malware. The book analyzes current trends in malware activity online, including botnets and malicious code for profit, and it proposes effective models for detection and prevention of attacks using. Furthermore, the book introduces novel techniques for creating services that protect their own integrity and safety, plus the data they manage.
Author: Dr.B.Balakumar Publisher: SK Research Group of Companies ISBN: 9395341084 Category : Computers Languages : en Pages : 259
Book Description
Dr.B.Balakumar, Assistant Professor, Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, Abhishekapatti, Tirunelveli, Tamil Nadu, India. Dr.J.Syed Nizamudeen Ahmed, Assistant Professor Temp, Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, Abhishekapatti, Tirunelveli, Tamil Nadu, India. Mrs.V.S.Jeyalakshmi, Researcher, Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, Abhishekapatti, Tirunelveli, Tamil Nadu, India. Dr.S.Vijayalakshmi, Assistant Professor Temp, Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, Abhishekapatti, Tirunelveli, Tamil Nadu, India. Mrs.S.Kowsalya , Researcher, Centre for Information Technology and Engineering, Manonmaniam Sundaranar University, Abhishekapatti, Tirunelveli, Tamil Nadu, India.
Author: Brij Gupta Publisher: ISBN: 9781799877905 Category : Computer networks Languages : en Pages : 305
Book Description
"This book describes some of the recent notable advances in threat-detection using machine-learning and artificial-intelligence with a focus on malwares, covering the current trends in ML/statistical approaches to detecting, clustering or classification of cyber-threats extensively"--
Author: Joshua Saxe Publisher: No Starch Press ISBN: 1593278594 Category : Computers Languages : en Pages : 274
Book Description
Malware Data Science explains how to identify, analyze, and classify large-scale malware using machine learning and data visualization. Security has become a "big data" problem. The growth rate of malware has accelerated to tens of millions of new files per year while our networks generate an ever-larger flood of security-relevant data each day. In order to defend against these advanced attacks, you'll need to know how to think like a data scientist. In Malware Data Science, security data scientist Joshua Saxe introduces machine learning, statistics, social network analysis, and data visualization, and shows you how to apply these methods to malware detection and analysis. You'll learn how to: - Analyze malware using static analysis - Observe malware behavior using dynamic analysis - Identify adversary groups through shared code analysis - Catch 0-day vulnerabilities by building your own machine learning detector - Measure malware detector accuracy - Identify malware campaigns, trends, and relationships through data visualization Whether you're a malware analyst looking to add skills to your existing arsenal, or a data scientist interested in attack detection and threat intelligence, Malware Data Science will help you stay ahead of the curve.
Author: Mamoun Alazab Publisher: Springer ISBN: 3030130576 Category : Computers Languages : en Pages : 246
Book Description
Cybercrime remains a growing challenge in terms of security and privacy practices. Working together, deep learning and cyber security experts have recently made significant advances in the fields of intrusion detection, malicious code analysis and forensic identification. This book addresses questions of how deep learning methods can be used to advance cyber security objectives, including detection, modeling, monitoring and analysis of as well as defense against various threats to sensitive data and security systems. Filling an important gap between deep learning and cyber security communities, it discusses topics covering a wide range of modern and practical deep learning techniques, frameworks and development tools to enable readers to engage with the cutting-edge research across various aspects of cyber security. The book focuses on mature and proven techniques, and provides ample examples to help readers grasp the key points.
Author: Kanad Ray Publisher: Springer ISBN: 9811305897 Category : Technology & Engineering Languages : en Pages : 729
Book Description
The book focuses on soft computing and its applications to solve real-world problems occurring in different domains ranging from medicine and healthcare, and supply chain management to image processing and cryptanalysis. It includes high-quality papers presented in the International Conference on Soft Computing: Theories and Applications (SoCTA 2017), organized by Bundelkhand University, Jhansi, India. Offering significant insights into soft computing for teachers and researchers alike, the book inspires more researchers to work in the field of soft computing.
Author: Mark Stamp Publisher: Springer Nature ISBN: 3030970876 Category : Computers Languages : en Pages : 388
Book Description
This book explores new and novel applications of machine learning, deep learning, and artificial intelligence that are related to major challenges in the field of cybersecurity. The provided research goes beyond simply applying AI techniques to datasets and instead delves into deeper issues that arise at the interface between deep learning and cybersecurity. This book also provides insight into the difficult "how" and "why" questions that arise in AI within the security domain. For example, this book includes chapters covering "explainable AI", "adversarial learning", "resilient AI", and a wide variety of related topics. It’s not limited to any specific cybersecurity subtopics and the chapters touch upon a wide range of cybersecurity domains, ranging from malware to biometrics and more. Researchers and advanced level students working and studying in the fields of cybersecurity (equivalently, information security) or artificial intelligence (including deep learning, machine learning, big data, and related fields) will want to purchase this book as a reference. Practitioners working within these fields will also be interested in purchasing this book.
Author: Christopher C. Elisan Publisher: McGraw Hill Professional ISBN: 0071819754 Category : Computers Languages : en Pages : 464
Book Description
A one-of-a-kind guide to setting up a malware research lab, using cutting-edge analysis tools, and reporting the findings Advanced Malware Analysis is a critical resource for every information security professional's anti-malware arsenal. The proven troubleshooting techniques will give an edge to information security professionals whose job involves detecting, decoding, and reporting on malware. After explaining malware architecture and how it operates, the book describes how to create and configure a state-of-the-art malware research lab and gather samples for analysis. Then, you’ll learn how to use dozens of malware analysis tools, organize data, and create metrics-rich reports. A crucial tool for combatting malware—which currently hits each second globally Filled with undocumented methods for customizing dozens of analysis software tools for very specific uses Leads you through a malware blueprint first, then lab setup, and finally analysis and reporting activities Every tool explained in this book is available in every country around the world
Author: Chiheb Chebbi Publisher: Packt Publishing Ltd ISBN: 178899311X Category : Language Arts & Disciplines Languages : en Pages : 264
Book Description
Become a master at penetration testing using machine learning with Python Key Features Identify ambiguities and breach intelligent security systems Perform unique cyber attacks to breach robust systems Learn to leverage machine learning algorithms Book Description 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. 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 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.
Author: Mark Stamp
Author: Mark Stamp
Author: Mihai Christodorescu
Author: Dr.B.Balakumar
Author: Brij Gupta
Author: Joshua Saxe
Author: Mamoun Alazab
Author: Kanad Ray
Author: Mark Stamp
Author: Christopher C. Elisan
Author: Chiheb Chebbi