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Over recent years, mobile devices, such as smartphones and tablets, have become feature-rich computing devices with networking opportunities that often surpass those of traditional PCs. Moreover, the smartphone market alone is now bigger than the PC market and, consequently, we see an exponential growth in the amount of mobile malware developed. Compared to traditional malware, mobile malware exhibits unique properties which require extensive studies to effectively protect the user. This dissertation identifies propagation vectors of mobile malware and examines characteristics of its propagation along with the effectiveness of various defense strategies. I focus on the propagation of mobile malware when spread through direct pairwise communication mechanisms (e.g., Bluetooth). I evaluate, both theoretically and by simulation, the effect of user mobility on propagation, and find that malware can infect the entire susceptible population in days for a campus size area. Proximity malware propagation is "invisible" to the network operator and defending against it is particularly challenging. I explore three defense strategies that span the spectrum from simple local detection to a globally coordinated defense. I find that local proximity-based dissemination of signatures can limit malware propagation, while the globally coordinated strategies that rely upon infrastructure within the mobile operator network can be even more effective. Furthermore, I study the effect of user social behavior on malware propagation. In a particular area I identify frequent and transient visitors and compare propagation using either set or all devices. My analysis indicates that transient visitors, previously considered unimportant, play an important role in propagation. Because direct pair-wise device encounters significantly impact proximity malware propagation, I study the strengths and limitations of deploying static scanners for inferring such encounters that are difficult to observe. By comparing direct and "virtual"-scanner-inferred encounters, I indicate significant statistical differences between the two categories, and find that malware propagation appears slower using inferred compared to actual encounters. The results from our analyses give us a better understanding of the effect of different parameters in mobile malware propagation and defense against it. Our results also pinpoint limitations of using encounters inferred from static scanners for malware and, generally, any data dissemination.
Malware has gone mobile, and the security landscape is changing quickly with emerging attacks on cell phones, PDAs, and other mobile devices. This first book on the growing threat covers a wide range of malware targeting operating systems like Symbian and new devices like the iPhone. Examining code in past, current, and future risks, protect your banking, auctioning, and other activities performed on mobile devices. * Visual Payloads View attacks as visible to the end user, including notation of variants. * Timeline of Mobile Hoaxes and Threats Understand the history of major attacks and horizon for emerging threates. * Overview of Mobile Malware Families Identify and understand groups of mobile malicious code and their variations. * Taxonomy of Mobile Malware Bring order to known samples based on infection, distribution, and payload strategies. * Phishing, SMishing, and Vishing Attacks Detect and mitigate phone-based phishing (vishing) and SMS phishing (SMishing) techniques. * Operating System and Device Vulnerabilities Analyze unique OS security issues and examine offensive mobile device threats. * Analyze Mobile Malware Design a sandbox for dynamic software analysis and use MobileSandbox to analyze mobile malware. * Forensic Analysis of Mobile Malware Conduct forensic analysis of mobile devices and learn key differences in mobile forensics. * Debugging and Disassembling Mobile Malware Use IDA and other tools to reverse-engineer samples of malicious code for analysis. * Mobile Malware Mitigation Measures Qualify risk, understand threats to mobile assets, defend against attacks, and remediate incidents. Understand the History and Threat Landscape of Rapidly Emerging Mobile Attacks Analyze Mobile Device/Platform Vulnerabilities and Exploits Mitigate Current and Future Mobile Malware Threats
Malware has gone mobile, and the security landscape is changing quickly with emerging attacks on cell phones, PDAs, and other mobile devices. This first book on the growing threat covers a wide range of malware targeting operating systems like Symbian and new devices like the iPhone. Examining code in past, current, and future risks, protect your banking, auctioning, and other activities performed on mobile devices. * Visual Payloads View attacks as visible to the end user, including notation of variants. * Timeline of Mobile Hoaxes and Threats Understand the history of major attacks and horizon for emerging threates. * Overview of Mobile Malware Families Identify and understand groups of mobile malicious code and their variations. * Taxonomy of Mobile Malware Bring order to known samples based on infection, distribution, and payload strategies. * Phishing, SMishing, and Vishing Attacks Detect and mitigate phone-based phishing (vishing) and SMS phishing (SMishing) techniques. * Operating System and Device Vulnerabilities Analyze unique OS security issues and examine offensive mobile device threats. * Analyze Mobile Malware Design a sandbox for dynamic software analysis and use MobileSandbox to analyze mobile malware. * Forensic Analysis of Mobile Malware Conduct forensic analysis of mobile devices and learn key differences in mobile forensics. * Debugging and Disassembling Mobile Malware Use IDA and other tools to reverse-engineer samples of malicious code for analysis. * Mobile Malware Mitigation Measures Qualify risk, understand threats to mobile assets, defend against attacks, and remediate incidents. * Understand the History and Threat Landscape of Rapidly Emerging Mobile Attacks * Analyze Mobile Device/Platform Vulnerabilities and Exploits * Mitigate Current and Future Mobile Malware Threats.
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.
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.
This book provides the foundational aspects of malware attack vectors and appropriate defense mechanisms against malware. The book equips readers with the necessary knowledge and techniques to successfully lower the risk against emergent malware attacks. Topics cover protections against malware using machine learning algorithms, Blockchain and AI technologies, smart AI-based applications, automated detection-based AI tools, forensics tools, and much more. The authors discuss theoretical, technical, and practical issues related to cyber malware attacks and defense, making it ideal reading material for students, researchers, and developers.
bull; Real-world tools needed to prevent, detect, and handle malicious code attacks. bull; Computer infection from viruses, worms, Trojan Horses etc., collectively known as malware is a growing cost problem for businesses. bull; Discover how attackers install malware and how you can peer through their schemes to keep systems safe. bull; Bonus malware code analysis laboratory.
The conference topics address different theoretical and practical aspects, and implementing solutions for intelligent systems and informatics disciplines including bioinformatics, computer science, medical informatics, biology, social studies, as well as robotics research. The conference also discuss and present solutions to the cloud computing and big data mining which are considered hot research topics. The conference papers discussed different topics – techniques, models, methods, architectures, as well as multi aspect, domain-specific, and new solutions for the above disciplines. The accepted papers have been grouped into five parts: Part I—Intelligent Systems and Informatics, addressing topics including, but not limited to, medical application, predicting student performance, action classification, and detection of dead stained microscopic cells, optical character recognition, plant identification, rehabilitation of disabled people. Part II—Hybrid Intelligent Systems, addressing topics including, but not limited to, EMG signals, text classification, geomagnetic inverse problem, email filtering. Part III—Multimedia Computing and Social Networks, addressing topics including, but not limited to, augmented reality, telepresence robot, video flash matting, community detection, quality images, face thermal image extraction, MRI tumor segmentation. Part V—Cloud Computing and Big Data Mining, discussing topics including, but not limited to, mining on microblogs, query optimization, big data classification, access control, friendsourcing, and assistive technology. Part VI—Swarm Optimization and Its Applications, addressing topics including, but not limited to, solving set covering problem, adaptive PSO for CT liver segmentation, water quality assessment, attribute reduction, fish detection, solving manufacturing cell design problem.
This book gathers and analyzes the latest attacks, solutions, and trends in mobile networks. Its broad scope covers attacks and solutions related to mobile networks, mobile phone security, and wireless security. It examines the previous and emerging attacks and solutions in the mobile networking worlds, as well as other pertinent security issues. The many attack samples present the severity of this problem, while the delivered methodologies and countermeasures show how to build a truly secure mobile computing environment.