Automatic Malware Analysis
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Automatic Malware Analysis
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Author : Heng Yin
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-09-14
Automatic Malware Analysis written by Heng Yin and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-14 with Computers categories.
Malicious software (i.e., malware) has become a severe threat to interconnected computer systems for decades and has caused billions of dollars damages each year. A large volume of new malware samples are discovered daily. Even worse, malware is rapidly evolving becoming more sophisticated and evasive to strike against current malware analysis and defense systems. Automatic Malware Analysis presents a virtualized malware analysis framework that addresses common challenges in malware analysis. In regards to this new analysis framework, a series of analysis techniques for automatic malware analysis is developed. These techniques capture intrinsic characteristics of malware, and are well suited for dealing with new malware samples and attack mechanisms.
Cuckoo Malware Analysis
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Author : Digit Oktavianto
language : en
Publisher: Packt Publishing Ltd
Release Date : 2013-10-16
Cuckoo Malware Analysis written by Digit Oktavianto and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-16 with Computers categories.
This book is a step-by-step, practical tutorial for analyzing and detecting malware and performing digital investigations. This book features clear and concise guidance in an easily accessible format.Cuckoo Malware Analysis is great for anyone who wants to analyze malware through programming, networking, disassembling, forensics, and virtualization. Whether you are new to malware analysis or have some experience, this book will help you get started with Cuckoo Sandbox so you can start analysing malware effectively and efficiently.
Data Science For Malware Analysis
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Author : Shane Molinari
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-12-15
Data Science For Malware Analysis written by Shane Molinari and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-15 with Computers categories.
Unlock the secrets of malware data science with cutting-edge techniques, AI-driven analysis, and international compliance standards to stay ahead of the ever-evolving cyber threat landscape Key Features Get introduced to three primary AI tactics used in malware and detection Leverage data science tools to combat critical cyber threats Understand regulatory requirements for using AI in cyber threat management Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIn today's world full of online threats, the complexity of harmful software presents a significant challenge for detection and analysis. This insightful guide will teach you how to apply the principles of data science to online security, acting as both an educational resource and a practical manual for everyday use. Data Science for Malware Analysis starts by explaining the nuances of malware, from its lifecycle to its technological aspects before introducing you to the capabilities of data science in malware detection by leveraging machine learning, statistical analytics, and social network analysis. As you progress through the chapters, you’ll explore the analytical methods of reverse engineering, machine language, dynamic scrutiny, and behavioral assessments of malicious software. You’ll also develop an understanding of the evolving cybersecurity compliance landscape with regulations such as GDPR and CCPA, and gain insights into the global efforts in curbing cyber threats. By the end of this book, you’ll have a firm grasp on the modern malware lifecycle and how you can employ data science within cybersecurity to ward off new and evolving threats.What you will learn Understand the science behind malware data and its management lifecycle Explore anomaly detection with signature and heuristics-based methods Analyze data to uncover relationships between data points and create a network graph Discover methods for reverse engineering and analyzing malware Use ML, advanced analytics, and data mining in malware data analysis and detection Explore practical insights and the future state of AI's use for malware data science Understand how NLP AI employs algorithms to analyze text for malware detection Who this book is for This book is for cybersecurity experts keen on adopting data-driven defense methods. Data scientists will learn how to apply their skill set to address critical security issues, and compliance officers navigating global regulations like GDPR and CCPA will gain indispensable insights. Academic researchers exploring the intersection of data science and cybersecurity, IT decision-makers overseeing organizational strategy, and tech enthusiasts eager to understand modern cybersecurity will also find plenty of useful information in this guide. A basic understanding of cybersecurity and information technology is a prerequisite.
Improving The Effectiveness Of Automatic Dynamic Android Malware Analysis
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Author : 沈穎志
language : en
Publisher:
Release Date : 2013
Improving The Effectiveness Of Automatic Dynamic Android Malware Analysis written by 沈穎志 and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.
It Convergence And Security 2012
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Author : Kuinam J. Kim
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-12
It Convergence And Security 2012 written by Kuinam J. Kim and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-12 with Technology & Engineering categories.
The proceedings approaches the subject matter with problems in technical convergence and convergences of security technology. This approach is new because we look at new issues that arise from techniques converging. The general scope of the proceedings content is convergence security and the latest information technology. The intended readership are societies, enterprises, and research institutes, and intended content level is mid- to highly educated personals. The most important features and benefits of the proceedings are the introduction of the most recent information technology and its related ideas, applications and problems related to technology convergence, and its case studies and finally an introduction of converging existing security techniques through convergence security. Overall, through the proceedings, authors will be able to understand the most state of the art information strategies and technologies of convergence security.
Network Intrusion Detection Using Deep Learning
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Author : Kwangjo Kim
language : en
Publisher: Springer
Release Date : 2018-09-25
Network Intrusion Detection Using Deep Learning written by Kwangjo Kim and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-25 with Computers categories.
This book presents recent advances in intrusion detection systems (IDSs) using state-of-the-art deep learning methods. It also provides a systematic overview of classical machine learning and the latest developments in deep learning. In particular, it discusses deep learning applications in IDSs in different classes: generative, discriminative, and adversarial networks. Moreover, it compares various deep learning-based IDSs based on benchmarking datasets. The book also proposes two novel feature learning models: deep feature extraction and selection (D-FES) and fully unsupervised IDS. Further challenges and research directions are presented at the end of the book. Offering a comprehensive overview of deep learning-based IDS, the book is a valuable reerence resource for undergraduate and graduate students, as well as researchers and practitioners interested in deep learning and intrusion detection. Further, the comparison of various deep-learning applications helps readers gain a basic understanding of machine learning, and inspires applications in IDS and other related areas in cybersecurity.
Convergence And Hybrid Information Technology
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Author : Geuk Lee
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-09-14
Convergence And Hybrid Information Technology written by Geuk Lee and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-14 with Computers categories.
This book constitutes the refereed proceedings of the 5th International Conference on Convergence and Hybrid Information Technology, ICHIT 2011, held in Daejeon, Korea, in September 2011. The 85 revised full papers presented were carefully reviewed and selected from 144 submissions. The papers are organized in topical sections on communications and networking; motion, video, image processing; security systems; cloud, RFID and robotics; industrial application of software systems; hardware and software engineering; healthcare, EEG and e-learning; HCI and data mining; software system and its applications.
Evaluating Tool Based Automated Malware Analysis Through Persistence Mechanism Detection
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Author : Matthew S. Webb
language : en
Publisher:
Release Date : 2018
Evaluating Tool Based Automated Malware Analysis Through Persistence Mechanism Detection written by Matthew S. Webb and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
Since 2014 there have been over 120 million new malicious programs registered every year. Due to the amount of new malware appearing every year, analysts have automated large sections of the malware reverse engineering process. Many automated analysis systems are created by re-implementing analysis techniques rather than automating existing tools that utilize the same techniques. New implementations take longer to create and do not have the same proven quality as a tool that evolved alongside malware for many years. The goal of this study is to assess the efficiency and effectiveness of using existing tools for the application of automated malware analysis. This study focuses on the problem of discovering how malware persists on an infected system. Six tools are chosen based on their usefulness in manual analysis for revealing different persistence techniques employed by malware. The functions of these tools are automated in a fashion that emulates how they can be manually utilized, resulting in information about a tested sample. These six tools are tested against a collection of actual malware samples, pulled from malware families that are known for employing various persistence techniques. The findings are then scanned for indicators of persistence. The results of these tests are used to determine the smallest tool subset that discovers the largest range of persistence mechanisms. For each tool, implementation difficulty is compared to the number of indicators discovered to reveal the effectiveness of similar tools for future analysis applications. The conclusion is that while the tools covered a wide range of persistence mechanisms, the standalone tools that were designed with scripting in mind were more effective than those with multiple system requirements or those with only a graphical interface. It was also discovered that the automation process limits functionality of some tools, as they are designed for analyst interaction. Regaining the tools' functionality lost from automation to use them for other reverse engineering applications could be cumbersome and could require necessary implementation overhauls. Finally, the more successful tools were able to detect a broader range of techniques, while some less successful tools could only detect a portion of the same techniques. This study concludes that while an analysis system can be created by automating existing tools, the characteristics of the tools chosen impact the workload required to automate them. A well-documented tool that is controllable through a command line interface that offers many configuration options will require less work for an analyst to automate than a tool with little documentation that can only be controlled through a graphical interface.
Applied Incident Response
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Author : Steve Anson
language : en
Publisher: John Wiley & Sons
Release Date : 2020-01-13
Applied Incident Response written by Steve Anson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-13 with Computers categories.
Incident response is critical for the active defense of any network, and incident responders need up-to-date, immediately applicable techniques with which to engage the adversary. Applied Incident Response details effective ways to respond to advanced attacks against local and remote network resources, providing proven response techniques and a framework through which to apply them. As a starting point for new incident handlers, or as a technical reference for hardened IR veterans, this book details the latest techniques for responding to threats against your network, including: Preparing your environment for effective incident response Leveraging MITRE ATT&CK and threat intelligence for active network defense Local and remote triage of systems using PowerShell, WMIC, and open-source tools Acquiring RAM and disk images locally and remotely Analyzing RAM with Volatility and Rekall Deep-dive forensic analysis of system drives using open-source or commercial tools Leveraging Security Onion and Elastic Stack for network security monitoring Techniques for log analysis and aggregating high-value logs Static and dynamic analysis of malware with YARA rules, FLARE VM, and Cuckoo Sandbox Detecting and responding to lateral movement techniques, including pass-the-hash, pass-the-ticket, Kerberoasting, malicious use of PowerShell, and many more Effective threat hunting techniques Adversary emulation with Atomic Red Team Improving preventive and detective controls
Malware Rootkits Botnets A Beginner S Guide
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Author : Christopher C. Elisan
language : en
Publisher: McGraw Hill Professional
Release Date : 2012-09-18
Malware Rootkits Botnets A Beginner S Guide written by Christopher C. Elisan and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-18 with Computers categories.
Provides information on how to identify, defend, and remove malware, rootkits, and botnets from computer networks.