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.
Malware Detection
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.
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.
Malware Detection
Author: Priyanka Nandal
Publisher: Anchor Academic Publishing
ISBN: 396067208X
Category : Computers
Languages : en
Pages : 72
Book Description
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 into an unknown group. The classifiers used in this research are k-Nearest Neighbors (kNN), J48 Decision Tree, and n-grams.
Publisher: Anchor Academic Publishing
ISBN: 396067208X
Category : Computers
Languages : en
Pages : 72
Book Description
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 into an unknown group. The classifiers used in this research are k-Nearest Neighbors (kNN), J48 Decision Tree, and n-grams.
Intelligent Mobile Malware Detection
Author: Tony Thomas
Publisher: CRC Press
ISBN: 1000824977
Category : Computers
Languages : en
Pages : 191
Book Description
The popularity of Android mobile phones has caused more cybercriminals to create malware applications that carry out various malicious activities. The attacks, which escalated after the COVID-19 pandemic, proved there is great importance in protecting Android mobile devices from malware attacks. Intelligent Mobile Malware Detection will teach users how to develop intelligent Android malware detection mechanisms by using various graph and stochastic models. The book begins with an introduction to the Android operating system accompanied by the limitations of the state-of-the-art static malware detection mechanisms as well as a detailed presentation of a hybrid malware detection mechanism. The text then presents four different system call-based dynamic Android malware detection mechanisms using graph centrality measures, graph signal processing and graph convolutional networks. Further, the text shows how most of the Android malware can be detected by checking the presence of a unique subsequence of system calls in its system call sequence. All the malware detection mechanisms presented in the book are based on the authors' recent research. The experiments are conducted with the latest Android malware samples, and the malware samples are collected from public repositories. The source codes are also provided for easy implementation of the mechanisms. This book will be highly useful to Android malware researchers, developers, students and cyber security professionals to explore and build defense mechanisms against the ever-evolving Android malware.
Publisher: CRC Press
ISBN: 1000824977
Category : Computers
Languages : en
Pages : 191
Book Description
The popularity of Android mobile phones has caused more cybercriminals to create malware applications that carry out various malicious activities. The attacks, which escalated after the COVID-19 pandemic, proved there is great importance in protecting Android mobile devices from malware attacks. Intelligent Mobile Malware Detection will teach users how to develop intelligent Android malware detection mechanisms by using various graph and stochastic models. The book begins with an introduction to the Android operating system accompanied by the limitations of the state-of-the-art static malware detection mechanisms as well as a detailed presentation of a hybrid malware detection mechanism. The text then presents four different system call-based dynamic Android malware detection mechanisms using graph centrality measures, graph signal processing and graph convolutional networks. Further, the text shows how most of the Android malware can be detected by checking the presence of a unique subsequence of system calls in its system call sequence. All the malware detection mechanisms presented in the book are based on the authors' recent research. The experiments are conducted with the latest Android malware samples, and the malware samples are collected from public repositories. The source codes are also provided for easy implementation of the mechanisms. This book will be highly useful to Android malware researchers, developers, students and cyber security professionals to explore and build defense mechanisms against the ever-evolving Android malware.
Android Malware Detection using Machine Learning
Author: ElMouatez Billah Karbab
Publisher: Springer Nature
ISBN: 303074664X
Category : Computers
Languages : en
Pages : 212
Book Description
The authors develop a malware fingerprinting framework to cover accurate android malware detection and family attribution in this book. The authors emphasize the following: (1) the scalability over a large malware corpus; (2) the resiliency to common obfuscation techniques; (3) the portability over different platforms and architectures. First, the authors propose an approximate fingerprinting technique for android packaging that captures the underlying static structure of the android applications in the context of bulk and offline detection at the app-market level. This book proposes a malware clustering framework to perform malware clustering by building and partitioning the similarity network of malicious applications on top of this fingerprinting technique. Second, the authors propose an approximate fingerprinting technique that leverages dynamic analysis and natural language processing techniques to generate Android malware behavior reports. Based on this fingerprinting technique, the authors propose a portable malware detection framework employing machine learning classification. Third, the authors design an automatic framework to produce intelligence about the underlying malicious cyber-infrastructures of Android malware. The authors then leverage graph analysis techniques to generate relevant intelligence to identify the threat effects of malicious Internet activity associated with android malware. The authors elaborate on an effective android malware detection system, in the online detection context at the mobile device level. It is suitable for deployment on mobile devices, using machine learning classification on method call sequences. Also, it is resilient to common code obfuscation techniques and adaptive to operating systems and malware change overtime, using natural language processing and deep learning techniques. Researchers working in mobile and network security, machine learning and pattern recognition will find this book useful as a reference. Advanced-level students studying computer science within these topic areas will purchase this book as well.
Publisher: Springer Nature
ISBN: 303074664X
Category : Computers
Languages : en
Pages : 212
Book Description
The authors develop a malware fingerprinting framework to cover accurate android malware detection and family attribution in this book. The authors emphasize the following: (1) the scalability over a large malware corpus; (2) the resiliency to common obfuscation techniques; (3) the portability over different platforms and architectures. First, the authors propose an approximate fingerprinting technique for android packaging that captures the underlying static structure of the android applications in the context of bulk and offline detection at the app-market level. This book proposes a malware clustering framework to perform malware clustering by building and partitioning the similarity network of malicious applications on top of this fingerprinting technique. Second, the authors propose an approximate fingerprinting technique that leverages dynamic analysis and natural language processing techniques to generate Android malware behavior reports. Based on this fingerprinting technique, the authors propose a portable malware detection framework employing machine learning classification. Third, the authors design an automatic framework to produce intelligence about the underlying malicious cyber-infrastructures of Android malware. The authors then leverage graph analysis techniques to generate relevant intelligence to identify the threat effects of malicious Internet activity associated with android malware. The authors elaborate on an effective android malware detection system, in the online detection context at the mobile device level. It is suitable for deployment on mobile devices, using machine learning classification on method call sequences. Also, it is resilient to common code obfuscation techniques and adaptive to operating systems and malware change overtime, using natural language processing and deep learning techniques. Researchers working in mobile and network security, machine learning and pattern recognition will find this book useful as a reference. Advanced-level students studying computer science within these topic areas will purchase this book as well.
Data Mining Tools for Malware Detection
Author: Mehedy Masud
Publisher: CRC Press
ISBN: 1439854556
Category : Computers
Languages : en
Pages : 450
Book Description
Although the use of data mining for security and malware detection is quickly on the rise, most books on the subject provide high-level theoretical discussions to the near exclusion of the practical aspects. Breaking the mold, Data Mining Tools for Malware Detection provides a step-by-step breakdown of how to develop data mining tools for malware d
Publisher: CRC Press
ISBN: 1439854556
Category : Computers
Languages : en
Pages : 450
Book Description
Although the use of data mining for security and malware detection is quickly on the rise, most books on the subject provide high-level theoretical discussions to the near exclusion of the practical aspects. Breaking the mold, Data Mining Tools for Malware Detection provides a step-by-step breakdown of how to develop data mining tools for malware d
Detection of Intrusions and Malware, and Vulnerability Assessment
Author: Magnus Almgren
Publisher: Springer
ISBN: 3319205501
Category : Computers
Languages : en
Pages : 351
Book Description
This book constitutes the refereed proceedings of the 12th International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment, DIMVA 2015, held in Milan, Italy, in July 2015. The 17 revised full papers presented were carefully reviewed and selected from 75 submissions. The papers are organized in topical sections on attacks, attack detection, binary analysis and mobile malware protection, social networks and large-scale attacks, Web and mobile security, and provenance and data sharing.
Publisher: Springer
ISBN: 3319205501
Category : Computers
Languages : en
Pages : 351
Book Description
This book constitutes the refereed proceedings of the 12th International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment, DIMVA 2015, held in Milan, Italy, in July 2015. The 17 revised full papers presented were carefully reviewed and selected from 75 submissions. The papers are organized in topical sections on attacks, attack detection, binary analysis and mobile malware protection, social networks and large-scale attacks, Web and mobile security, and provenance and data sharing.
Detection of Intrusions and Malware, and Vulnerability Assessment
Author: Ulrich Flegel
Publisher: Springer
ISBN: 3642373003
Category : Computers
Languages : en
Pages : 243
Book Description
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 sections on malware, mobile security, secure design, and intrusion detection systems (IDS).
Publisher: Springer
ISBN: 3642373003
Category : Computers
Languages : en
Pages : 243
Book Description
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 sections on malware, mobile security, secure design, and intrusion detection systems (IDS).
Malware Intrusion Detection
Author: Morton G. Swimmer
Publisher: Lulu.com
ISBN: 3833434368
Category :
Languages : en
Pages : 283
Book Description
Publisher: Lulu.com
ISBN: 3833434368
Category :
Languages : en
Pages : 283
Book Description
Detection of Intrusions and Malware, and Vulnerability Assessment
Author: Juan Caballero
Publisher: Springer
ISBN: 3319406671
Category : Computers
Languages : en
Pages : 441
Book Description
This book constitutes the refereed proceedings of the 13th International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment, DIMVA 2016, held in San Sebastián, Spain, in July 2016. The 19 revised full papers and 2 extended abstracts presented were carefully reviewed and selected from 66 submissions. They present the state of the art in intrusion detection, malware analysis, and vulnerability assessment, dealing with novel ideas, techniques, and applications in important areas of computer security including vulnerability detection, attack prevention, web security, malware detection and classification, authentication, data leakage prevention, and countering evasive techniques such as obfuscation.
Publisher: Springer
ISBN: 3319406671
Category : Computers
Languages : en
Pages : 441
Book Description
This book constitutes the refereed proceedings of the 13th International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment, DIMVA 2016, held in San Sebastián, Spain, in July 2016. The 19 revised full papers and 2 extended abstracts presented were carefully reviewed and selected from 66 submissions. They present the state of the art in intrusion detection, malware analysis, and vulnerability assessment, dealing with novel ideas, techniques, and applications in important areas of computer security including vulnerability detection, attack prevention, web security, malware detection and classification, authentication, data leakage prevention, and countering evasive techniques such as obfuscation.
Detection of Intrusions and Malware, and Vulnerability Assessment
Author: Michalis Polychronakis
Publisher: Springer
ISBN: 3319608762
Category : Computers
Languages : en
Pages : 414
Book Description
This book constitutes the refereed proceedings of the 14th International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment, DIMVA 2017, held in Bonn, Germany, in July 2017. The 18 revised full papers included in this book were carefully reviewed and selected from 67 submissions. They present topics such as enclaves and isolation; malware analysis; cyber-physical systems; detection and protection; code analysis; and web security.
Publisher: Springer
ISBN: 3319608762
Category : Computers
Languages : en
Pages : 414
Book Description
This book constitutes the refereed proceedings of the 14th International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment, DIMVA 2017, held in Bonn, Germany, in July 2017. The 18 revised full papers included in this book were carefully reviewed and selected from 67 submissions. They present topics such as enclaves and isolation; malware analysis; cyber-physical systems; detection and protection; code analysis; and web security.