Automatic Malware Analysis

This book PDF is perfect for those who love Computers genre, written by Heng Yin and published by Springer Science & Business Media which was released on 14 September 2012 with total hardcover pages 73. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Automatic Malware Analysis books below.

Automatic Malware Analysis
Author : Heng Yin
File Size : 42,7 Mb
Publisher : Springer Science & Business Media
Language : English
Release Date : 14 September 2012
ISBN : 9781461455233
Pages : 73 pages
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Automatic Malware Analysis by Heng Yin Book PDF Summary

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.

Automatic Malware Analysis

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

Get Book
Cuckoo Malware Analysis

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

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Malware Analysis Techniques

Analyze malicious samples, write reports, and use industry-standard methodologies to confidently triage and analyze adversarial software and malware Key FeaturesInvestigate, detect, and respond to various types of malware threatUnderstand how to use what you've learned as an analyst to produce actionable IOCs and reportingExplore complete solutions, detailed walkthroughs, and case

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Malware Analysis Using Artificial Intelligence and Deep Learning

​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

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Botnet Detection

Botnets have become the platform of choice for launching attacks and committing fraud on the Internet. A better understanding of Botnets will help to coordinate and develop new technologies to counter this serious security threat. Botnet Detection: Countering the Largest Security Threat consists of chapters contributed by world-class leaders in

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Convergence and Hybrid Information Technology

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

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Detection of Intrusions and Malware  and Vulnerability Assessment

This book constitutes the refereed post-proceedings of the 9th International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment, DIMVA 2012, held in Heraklion, Crete, Greece, in July 2012. The 10 revised full papers presented together with 4 short papers were carefully reviewed and selected from 44 submissions. The papers are organized in topical

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Malware Detection

In the present work the behavior of malicious software is studied, the security challenges are understood, and an attempt is made to detect the malware behavior automatically using dynamic approach. Various classification techniques are studied. Malwares are then grouped according to these techniques and malware with unknown characteristics are clustered

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