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As mobile devices become more widespread and powerful, they store more sensitive data, which include not only personal user information but also data collected via sensors on the device. When mobile applications have access to this sensitive information, they may leak it accidentally or by malicious design. Google's Android operating system provides a permissions-based security model that restricts an application's access to sensitive data. Each application statically declares the sensitive data and functionality that it requires in a manifest, which is presented to the user for approval during installation. However, it is difficult to determine how sensitive data will be used once the application has been installed. To address this problem, we present AndroidLeaks, a static analysis framework for automatically finding potential leaks of sensitive information in Android applications on a massive scale. AndroidLeaks leverages Android's permission scheme to identify sources of private data, then performs taint-aware slicing to determine if private data will be leaked via a network sink. We evaluated AndroidLeaks on 24,350 Android applications from several Android markets. AndroidLeaks found 57,299 potential privacy leaks in 7,414 Android applications, of which we have manually verified that 2,342 applications leak private data, including phone information, GPS location, Wi-Fi data, and audio recorded with the microphone. While previous work, such as TaintDroid, has effectively analyzed the data leakage of a small set of applications, no previous Android analysis tool has been able to effectively evaluate the leakage of a large set of applications in a reasonable amount of time. AndroidLeaks examined these applications in 30 hours, which indicates that it is capable of scaling to the rate at which new applications are developed. As ad code makes up a substantial percentage of the overall leaks that we discovered, we further investigated thirteen ad libraries. We discovered that ad libraries will frequently attempt to access sensitive content beyond that which is required to target ads, such as a user's contact book or calendar. Further, we identified four ad libraries that introduce a vulnerability to any application in which they are included. By exploiting this vulnerability, an attacker can instruct a user's device to perform various actions including placing a phone call, sending an SMS or email, and modifying contact and calendar entries. We propose solutions to problems caused by the lack of privilege separation between application code and ad code and discuss difficulties in addressing the vulnerabilities we discovered.
Mobile technologies have become a staple in society for their accessibility and diverse range of applications that are continually growing and advancing. Users are increasingly using these devices for activities beyond simple communication including gaming and e-commerce and to access confidential information including banking accounts and medical records. While mobile devices are being so widely used and accepted in daily life, and subsequently housing more and more personal data, it is evident that the security of these devices is paramount. As mobile applications now create easy access to personal information, they can incorporate location tracking services, and data collection can happen discreetly behind the scenes. Hence, there needs to be more security and privacy measures enacted to ensure that mobile technologies can be used safely. Advancements in trust and privacy, defensive strategies, and steps for securing the device are important foci as mobile technologies are highly popular and rapidly developing. The Research Anthology on Securing Mobile Technologies and Applications discusses the strategies, methods, and technologies being employed for security amongst mobile devices and applications. This comprehensive book explores the security support that needs to be required on mobile devices to avoid application damage, hacking, security breaches and attacks, or unauthorized accesses to personal data. The chapters cover the latest technologies that are being used such as cryptography, verification systems, security policies and contracts, and general network security procedures along with a look into cybercrime and forensics. This book is essential for software engineers, app developers, computer scientists, security and IT professionals, practitioners, stakeholders, researchers, academicians, and students interested in how mobile technologies and applications are implementing security protocols and tactics amongst devices.
The Android application ecosystem has thrived, with hundreds of thousands of applications (apps) available to users; however, not all of them are safe or privacy-friendly. Analyzing these many apps for malicious behaviors is an important but challenging area of research as malicious apps tend to use prevalent stealth techniques, e.g., encryption, code transformation, and other obfuscation approaches to bypass detection. Academic researchers and security companies have realized that the traditional signature-based and static analysis methods are inadequate to deal with this evolvingthreat. In recent years, a number of static and dynamic code analysis proposals for analyzing Android apps have been introduced in academia and in the commercial world. Moreover, as a single detection approach may be ineffective against advanced obfuscation techniques, multiple frameworks for privacy leakage detection have been shown to yield better results when used in conjunction. In this dissertation, our contribution is two-fold. First, we organize 32 of the most recent and promising privacy-oriented proposals on Android apps analysis into two categories: static and dynamic analysis. For each category, we survey the state of-the-art proposals and provide a high-level overview of the methodology they rely on to detect privacy-sensitive leakages and app behaviors. Second, we choose one popular proposal from each category to analyze and detect leakages in 5,000 Android apps. Our toolchain setup consists of IntelliDroid (static) to find and trigger sensitive API (Application Program Interface) calls in target apps and leverages TaintDroid (dynamic) to detect leakages in these apps. We found that about 33%of the tested apps leak privacy-sensitive information over the network (e.g., IMEI, location, UDID), which is consistent with existing work. Furthermore, we highlight the efficiency of combining IntelliDroid and TaintDroid in comparison with Android Monkey and TaintDroid as used in most prior work. We report an overall increase in the frequency of leakage of identifiers. This increase may indicate that IntelliDroid is a better approach over Android Monkey.
This SpringerBrief explains the emerging cyber threats that undermine Android application security. It further explores the opportunity to leverage the cutting-edge semantics and context–aware techniques to defend against such threats, including zero-day Android malware, deep software vulnerabilities, privacy breach and insufficient security warnings in app descriptions. The authors begin by introducing the background of the field, explaining the general operating system, programming features, and security mechanisms. The authors capture the semantic-level behavior of mobile applications and use it to reliably detect malware variants and zero-day malware. Next, they propose an automatic patch generation technique to detect and block dangerous information flow. A bytecode rewriting technique is used to confine privacy leakage. User-awareness, a key factor of security risks, is addressed by automatically translating security-related program semantics into natural language descriptions. Frequent behavior mining is used to discover and compress common semantics. As a result, the produced descriptions are security-sensitive, human-understandable and concise.By covering the background, current threats, and future work in this field, the brief is suitable for both professionals in industry and advanced-level students working in mobile security and applications. It is valuable for researchers, as well.
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 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.
This book constitutes the revised selected papers of the Third International Conference on Information Systems Security and Privacy, ICISSP 2017, held in Porto, Portugal, in February 2017. The 13 full papers presented were carefully reviewed and selected from a total of 100 submissions. They are dealing with topics such as vulnerability analysis and countermeasures, attack patterns discovery and intrusion detection, malware classification and detection, cryptography applications, data privacy and anonymization, security policy analysis, enhanced access control, and socio-technical aspects of security.
This book constitutes the proceedings of the 11th International Conference on Network and System Security, NSS 2017, held in Helsinki, Finland, in August 2017. The 24 revised full papers presented in this book were carefully reviewed and selected from 83 initial submissions. The papers are organized in topical sections on Cloud and IoT Security; Network Security; Platform and Hardware Security; Crypto and Others; and Authentication and Key Management. This volume also contains 35 contributions of the following workshops: Security Measurements of Cyber Networks (SMCN-2017); Security in Big Data (SECBD-2017); 5G Security and Machine Learning (IW5GS-2017); of the Internet of Everything (SECIOE-2017).