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This book constitutes the refereed post-conference proceedings of the 18th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2021, which was held in November 2021. The conference was held virtually due to the COVID-19 pandemic.The 37 full papers were carefully reviewed and selected from 79 submissions and present discussions, interaction and exchange of experiences that will designate future research efforts and directions. Topics addressed by the conference include systems, applications, social networks, middleware, networking, sensing, data management, data processing and services, all with special focus on mobile and ubiquitous computing.
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.
With the rapid evolution of technology, identifying new risks is a constantly moving target. The metaverse is a virtual space that is interconnected with cloud computing and with companies, organizations, and even countries investing in virtual real estate. The questions of what new risks will become evident in these virtual worlds and in augmented reality and what real-world impacts they will have in an ever-expanding internet of things (IoT) need to be answered. Within continually connected societies that require uninterrupted functionality, cyber security is vital, and the ability to detect potential risks and ensure the security of computing systems is crucial to their effective use and success. Proper utilization of the latest technological advancements can help in developing more efficient techniques to prevent cyber threats and enhance cybersecurity. Risk Detection and Cyber Security for the Success of Contemporary Computing presents the newest findings with technological advances that can be utilized for more effective prevention techniques to protect against cyber threats. This book is led by editors of best-selling and highly indexed publications, and together they have over two decades of experience in computer science and engineering. Featuring extensive coverage on authentication techniques, cloud security, and mobile robotics, this book is ideally designed for students, researchers, scientists, and engineers seeking current research on methods, models, and implementation of optimized security in digital contexts.
This book constitutes the refereed proceedings of the Second International Conference on Big Data and Security, ICBDS 2020, held in Singapore, Singapore, in December 2020. The 44 revised full papers and 8 short papers were carefully reviewed and selected out of 153 submissions. The papers included in this book are organized according to the topical sections on cybersecurity and privacy, big data, blockchain and internet of things, and artificial intelligence/ machine learning security.
This book constitutes the refereed conference proceedings of the 20th International Symposium on Research in Attacks, Intrusions, and Defenses, RAID 2017, held in Atlanta, GA, USA, in September 2017. The 21 revised full papers were selected from 105 submissions. They are organized in the following topics: software security, intrusion detection, systems security, android security, cybercrime, cloud security, network security.
This two-volume set LNICST 304-305 constitutes the post-conference proceedings of the 15thInternational Conference on Security and Privacy in Communication Networks, SecureComm 2019, held in Orlando, FL, USA, in October 2019. The 38 full and 18 short papers were carefully reviewed and selected from 149 submissions. The papers are organized in topical sections on blockchains, internet of things, machine learning, everything traffic security communicating covertly, let’s talk privacy, deep analysis, systematic theory, bulletproof defenses, blockchains and IoT, security and analytics, machine learning, private, better clouds, ATCS workshop.
This book constitutes the revised selected papers from the 12th International Conference on Risk and Security of Internet and Systems, CRISIS 2017, held in Dinard, France, in September 2017.The 12 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 42 submissions. They cover diverse research themes, ranging from classic topics, such as vulnerability analysis and classification; apps security; access control and filtering; cloud security; cyber-insurance and cyber threat intelligence; human-centric security and trust; and risk analysis.
This volume comprises the select peer-reviewed proceedings of the International Conference on Advances and Applications of Artificial Intelligence and Machine Learning 2022 (ICAAAIML 2022). It aims to provide a comprehensive and broad-spectrum picture of state-of-the-art research and development in the areas of artificial intelligence, machine learning, deep learning, and their advanced applications in computer vision and blockchain. It also covers research in core concepts of computers, intelligent system design and deployment, real-time systems, WSN, sensors and sensor nodes, software engineering, image processing, and cloud computing. This volume will provide a valuable resource for those in academia and industry.