Download Full eBooks in PDF
Android Malware Detection And Adversarial Methods Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Android Malware Detection And Adversarial Methods book. This book definitely worth reading, it is an incredibly well-written.
Author : Weina Niu
Publisher : Springer Nature
Page : 197 pages
File Size : 54,5 Mb
Release : 2024-06-30
Category : Electronic
ISBN : 9789819714599
Author : Xuxian Jiang,Yajin Zhou
Publisher : Springer Science & Business Media
Page : 50 pages
File Size : 47,9 Mb
Release : 2013-06-13
Category : Computers
ISBN : 9781461473947
Mobile devices, such as smart phones, have achieved computing and networking capabilities comparable to traditional personal computers. Their successful consumerization has also become a source of pain for adopting users and organizations. In particular, the widespread presence of information-stealing applications and other types of mobile malware raises substantial security and privacy concerns. Android Malware presents a systematic view on state-of-the-art mobile malware that targets the popular Android mobile platform. Covering key topics like the Android malware history, malware behavior and classification, as well as, possible defense techniques.
Author : Mihai Christodorescu,Somesh Jha,Douglas Maughan,Dawn Song,Cliff Wang
Publisher : Springer Science & Business Media
Page : 307 pages
File Size : 55,7 Mb
Release : 2007-03-06
Category : Computers
ISBN : 9780387445991
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 : ElMouatez Billah Karbab,Mourad Debbabi,Abdelouahid Derhab,Djedjiga Mouheb
Publisher : Springer Nature
Page : 212 pages
File Size : 48,5 Mb
Release : 2021-07-10
Category : Computers
ISBN : 9783030746643
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.
Author : G. Ranganathan,Xavier Fernando,Fuqian Shi,Youssouf El Allioui
Publisher : Springer Nature
Page : 944 pages
File Size : 40,5 Mb
Release : 2021-10-25
Category : Technology & Engineering
ISBN : 9789811653018
This book features selected papers from the International Conference on Soft Computing for Security Applications (ICSCS 2021), held at Dhirajlal Gandhi College of Technology, Tamil Nadu, India, during June 2021. It covers recent advances in the field of soft computing techniques such as fuzzy logic, neural network, support vector machines, evolutionary computation, machine learning and probabilistic reasoning to solve various real-time challenges. The book presents innovative work by leading academics, researchers, and experts from industry.
Author : Josip Lorincz,Antonio Capone,Luca Chiaraviglio,JinsongWu
Publisher : MDPI
Page : 382 pages
File Size : 46,9 Mb
Release : 2020-01-21
Category : Technology & Engineering
ISBN : 9783039280384
The book Green, Energy-Efficient and Sustainable Networks provides insights and solutions for a range of problems in the field of obtaining greener, energy-efficient, and sustainable networks. The book contains the outcomes of the Special Issue on “Green, Energy-Efficient and Sustainable Networks” of the Sensors journal. Seventeen high-quality papers published in the Special Issue have been collected and reproduced in this book, demonstrating significant achievements in the field. Among the published papers, one paper is an editorial and one is a review, while the remaining 15 works are research articles. The published papers are self-contained peer-reviewed scientific works that are authored by more than 75 different contributors with both academic and industry backgrounds. The editorial paper gives an introduction to the problem of information and communication technology (ICT) energy consumption and greenhouse gas emissions, presenting the state of the art and future trends in terms of improving the energy-efficiency of wireless networks and data centers, as the major energy consumers in the ICT sector. In addition, the published articles aim to improve energy efficiency in the fields of software-defined networking, Internet of things, machine learning, authentication, energy harvesting, wireless relay systems, routing metrics, wireless sensor networks, device-to-device communications, heterogeneous wireless networks, and image sensing. The last paper is a review that gives a detailed overview of energy-efficiency improvements and methods for the implementation of fifth-generation networks and beyond. This book can serve as a source of information in industrial, teaching, and/or research and development activities. The book is a valuable source of information, since it presents recent advances in different fields related to greening and improving the energy-efficiency and sustainability of those ICTs particularly addressed in this book
Author : Sabu M. Thampi,Guojun Wang,Danda B. Rawat,Ryan Ko,Chun-I Fan
Publisher : Springer Nature
Page : 314 pages
File Size : 52,8 Mb
Release : 2021-02-09
Category : Computers
ISBN : 9789811604225
This book constitutes revised selected papers of the 8th International Symposium on Security in Computing and Communications, SSCC 2020, held in Chennai, India, in October 2020. Due to the COVID-19 pandemic the conference was held online. The 13 revised full papers and 8 revised short papers presented were carefully reviewed and selected from 42 submissions. The papers cover wide research fields including cryptography, database and storage security, human and societal aspects of security and privacy.
Author : Gang Wang,Arridhana Ciptadi,Ali Ahmadzadeh
Publisher : Springer Nature
Page : 163 pages
File Size : 47,5 Mb
Release : 2021-09-24
Category : Computers
ISBN : 9783030878399
This book constitutes selected and extended papers from the Second International Workshop on Deployable Machine Learning for Security Defense, MLHat 2021, held in August 2021. Due to the COVID-19 pandemic the conference was held online. The 6 full papers were thoroughly reviewed and selected from 7 qualified submissions. The papers are organized in topical sections on machine learning for security, and malware attack and defense.
Author : Chunhua Su,Dimitris Gritzalis,Vincenzo Piuri
Publisher : Springer Nature
Page : 643 pages
File Size : 47,5 Mb
Release : 2022-11-18
Category : Computers
ISBN : 9783031212802
This book constitutes the refereed proceedings of the 17th International Conference on Information Security Practice and Experience, ISPEC 2022, held in Taipei, Taiwan, in November 2022. The 33 full papers together with 2 invited papers included in this volume were carefully reviewed and selected from 87 submissions. The main goal of the conference is to promote research on new information security technologies, including their applications and their integration with IT systems in various vertical sectors.
Author : Petros Nicopolitidis,Sudip Misra,Laurence T. Yang,Bernard Zeigler,Zhaolng Ning
Publisher : Springer Nature
Page : 812 pages
File Size : 53,9 Mb
Release : 2022-03-03
Category : Computers
ISBN : 9783030870492
This book presents new research contributions in the above-mentioned fields. Information and communication technologies (ICT) have an integral role in today’s society. Four major driving pillars in the field are computing, which nowadays enables data processing in unprecedented speeds, informatics, which derives information stemming for processed data to feed relevant applications, networking, which interconnects the various computing infrastructures and cybersecurity for addressing the growing concern for secure and lawful use of the ICT infrastructure and services. Its intended readership covers senior undergraduate and graduate students in Computer Science and Engineering and Electrical Engineering, as well as researchers, scientists, engineers, ICT managers, working in the relevant fields and industries.
Author : Qian Han,Salvador Mandujano,Sebastian Porst,V.S. Subrahmanian,Sai Deep Tetali
Publisher : No Starch Press
Page : 330 pages
File Size : 51,7 Mb
Release : 2023-11-07
Category : Computers
ISBN : 9781718503311
Written by machine-learning researchers and members of the Android Security team, this all-star guide tackles the analysis and detection of malware that targets the Android operating system. This groundbreaking guide to Android malware distills years of research by machine learning experts in academia and members of Meta and Google’s Android Security teams into a comprehensive introduction to detecting common threats facing the Android eco-system today. Explore the history of Android malware in the wild since the operating system first launched and then practice static and dynamic approaches to analyzing real malware specimens. Next, examine machine learning techniques that can be used to detect malicious apps, the types of classification models that defenders can implement to achieve these detections, and the various malware features that can be used as input to these models. Adapt these machine learning strategies to the identifica-tion of malware categories like banking trojans, ransomware, and SMS fraud. You’ll: Dive deep into the source code of real malware Explore the static, dynamic, and complex features you can extract from malware for analysis Master the machine learning algorithms useful for malware detection Survey the efficacy of machine learning techniques at detecting common Android malware categories The Android Malware Handbook’s team of expert authors will guide you through the Android threat landscape and prepare you for the next wave of malware to come.
Author : Mamoun Alazab,MingJian Tang
Publisher : Springer
Page : 246 pages
File Size : 42,7 Mb
Release : 2019-08-14
Category : Computers
ISBN : 9783030130572
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 : Jing Sun,Meng Sun
Publisher : Springer
Page : 474 pages
File Size : 47,8 Mb
Release : 2018-11-05
Category : Computers
ISBN : 9783030024505
This book constitutes the refereed proceedings of the 20th International Conference on Formal Engineering Methods, ICFEM 2018, held in Gold Coast, QLD, Australia, in November 2018. The 22 revised full papers presented together with 14 short papers were carefully reviewed and selected from 66 submissions. The conference focuses on all areas related to formal engineering methods, such as verification; network systems; type theory; theorem proving; logic and semantics; refinement and transition systems; and emerging applications of formal methods.
Author : Lejla Batina,Thomas Bäck,Ileana Buhan,Stjepan Picek
Publisher : Springer Nature
Page : 365 pages
File Size : 48,7 Mb
Release : 2022-04-07
Category : Computers
ISBN : 9783030987954
AI has become an emerging technology to assess security and privacy, with many challenges and potential solutions at the algorithm, architecture, and implementation levels. So far, research on AI and security has looked at subproblems in isolation but future solutions will require sharing of experience and best practice in these domains. The editors of this State-of-the-Art Survey invited a cross-disciplinary team of researchers to a Lorentz workshop in 2019 to improve collaboration in these areas. Some contributions were initiated at the event, others were developed since through further invitations, editing, and cross-reviewing. This contributed book contains 14 invited chapters that address side-channel attacks and fault injection, cryptographic primitives, adversarial machine learning, and intrusion detection. The chapters were evaluated based on their significance, technical quality, and relevance to the topics of security and AI, and each submission was reviewed in single-blind mode and revised.
Author : Mark Stamp,Mamoun Alazab,Andrii Shalaginov
Publisher : Springer Nature
Page : 651 pages
File Size : 54,5 Mb
Release : 2020-12-20
Category : Computers
ISBN : 9783030625825
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.
