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"Android Forensics" covers an open source mobile device platform based on the Linux 2.6 kernel and managed by the Open Handset Alliance. This book provides a thorough review of the Android platform including supported hardware devices, the structure of the Android development project, and implementation of core services (wireless communication, data storage, and other low-level functions).
This book presents state-of-the-art contributions from both scientists and practitioners working in intrusion detection and prevention for mobile networks, services, and devices. It covers fundamental theory, techniques, applications, as well as practical experiences concerning intrusion detection and prevention for the mobile ecosystem. It also includes surveys, simulations, practical results and case studies.
This book includes papers in the research area of artificial intelligence, robotics and automation, IoT smart agriculture, data analysis and cloud computing, communication and technology, and signal and natural language processing. The book is a collection of research papers presented at the First International Conference on Fourth Industrial Revolution and Beyond (IC4IR 2021) organized by University Grants Commission of Bangladesh in association with IEEE Computer Society Bangladesh Chapter and Bangladesh Computer Society during December 10–11, 2021.
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.
This incisive Research Handbook identifies and assesses the emerging trends in competition enforcement, investigating how such changes impact the enforcement approach of competition authorities and the behaviour of companies in an ever-evolving business and regulatory environment.
This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence, and data analytics, along with advances in network technologies. The book is a collection of peer-reviewed research papers presented at Sixth International Conference on Data Management, Analytics and Innovation (ICDMAI 2022), held virtually during January 14–16, 2022. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
This book presents best selected research papers presented at the International Conference on Computer Networks, Big Data and IoT (ICCBI 2021), organized by Vaigai College Engineering, Madurai, Tamil Nadu, India, during December 9–10, 2021. The book covers original papers on computer networks, network protocols and wireless networks, data communication technologies and network security. The book is a valuable resource and reference for researchers, instructors, students, scientists, engineers, managers and industry practitioners in those important areas.
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.
The goal of this book is to crystallize the emerging mobile computing technologies and trends into positive efforts to focus on the most promising solutions in services computing. Many toys built today are increasingly using these technologies together and it is important to understand the various research and practical issues. The book will provide clear proof that mobile technologies are playing an ever increasing important and critical role in supporting toy computing, which is a new research discipline in computer science. It is also expected that the book will further research new best practices and directions in toy computing. The goal of this book is to bring together academics and practitioners to describe the use and synergy between the above-mentioned technologies. This book is mainly intended for researchers and students working in computer science and engineering, and for toy industry technology providers, having particular interests in mobile services. The wide range of authors of this book will help the various communities understand both specific and common problems. This book facilities software developers and researchers to become more aware of this challenging research opportunity. As well, the book is soliciting shall provide valuable strategic outlook on the emerging toy industry.