Policy Enforcement with Proactive Libraries

Software libraries implement APIs that deliver reusable functionalities. To correctly use these functionalities, software applications must satisfy certain correctness policies, for instance policies about the order some API methods can be invoked and about the values that can be used for the parameters. If these policies are violated, applications may produce misbehaviors and failures at runtime. Although this problem is general, applications that incorrectly use API methods are more frequent in certain contexts. For instance, Android provides a rich and rapidly evolving set of APIs that might be used incorrectly by app developers who often implement and publish faulty apps in the marketplaces. To mitigate this problem, we introduce the novel notion of proactive library, which augments classic libraries with the capability of proactively detecting and healing misuses at run- time. Proactive libraries blend libraries with multiple proactive modules that collect data, check the correctness policies of the libraries, and heal executions as soon as the violation of a correctness policy is detected. The proactive modules can be activated or deactivated at runtime by the users and can be implemented without requiring any change to the original library and any knowledge about the applications that may use the library. We evaluated proactive libraries in the context of the Android ecosystem. Results show that proactive libraries can automati- cally overcome several problems related to bad resource usage at the cost of a small overhead.Comment: O. Riganelli, D. Micucci and L. Mariani, "Policy Enforcement with Proactive Libraries" 2017 IEEE/ACM 12th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), Buenos Aires, Argentina, 2017, pp. 182-19

Program analysis for android security and reliability

The recent, widespread growth and adoption of mobile devices have revolutionized the way users interact with technology. As mobile apps have become increasingly prevalent, concerns regarding their security and reliability have gained significant attention. The ever-expanding mobile app ecosystem presents unique challenges in ensuring the protection of user data and maintaining app robustness. This dissertation expands the field of program analysis with techniques and abstractions tailored explicitly to enhancing Android security and reliability. This research introduces approaches for addressing critical issues related to sensitive information leakage, device and user fingerprinting, mobile medical score calculators, as well as termination-induced data loss. Through a series of comprehensive studies and employing novel approaches that combine static and dynamic analysis, this work provides valuable insights and practical solutions to the aforementioned challenges. In summary, this dissertation makes the following contributions: (1) precise identifier leak tracking via a novel algebraic representation of leak signatures, (2) identifier processing graphs (IPGs), an abstraction for extracting and subverting user-based and device-based fingerprinting schemes, (3) interval-based verification of medical score calculator correctness, and (4) identifying potential data losses caused by app termination

DETECTION AND PREVENTION OF MISUSE OF SOFTWARE COMPONENTS

Ph.DDOCTOR OF PHILOSOPH

Analyzing & designing the security of shared resources on smartphone operating systems

Smartphone penetration surpassed 80% in the US and nears 70% in Western Europe. In fact, smartphones became the de facto devices users leverage to manage personal information and access external data and other connected devices on a daily basis. To support such multi-faceted functionality, smartphones are designed with a multi-process architecture, which enables third-party developers to build smartphone applications which can utilize smartphone internal and external resources to offer creative utility to users. Unfortunately, such third-party programs can exploit security inefficiencies in smartphone operating systems to gain unauthorized access to available resources, compromising the confidentiality of rich, highly sensitive user data. The smartphone ecosystem, is designed such that users can readily install and replace applications on their smartphones. This facilitates users’ efforts in customizing the capabilities of their smartphones tailored to their needs. Statistics report an increasing number of available smartphone applications— in 2017 there were approximately 3.5 million third-party apps on the official application store of the most popular smartphone platform. In addition we expect users to have approximately 95 such applications installed on their smartphones at any given point. However, mobile apps are developed by untrusted sources. On Android—which enjoys 80% of the smartphone OS market share—application developers are identified based on self-sign certificates. Thus there is no good way of holding a developer accountable for a malicious behavior. This creates an issue of multi-tenancy on smartphones where principals from diverse untrusted sources share internal and external smartphone resources. Smartphone OSs rely on traditional operating system process isolation strategies to confine untrusted third-party applications. However this approach is insufficient because incidental seemingly harmless resources can be utilized by untrusted tenants as side-channels to bypass the process boundaries. Smartphones also introduced a permission model to allow their users to govern third-party application access to system resources (such as camera, microphone and location functionality). However, this permission model is both coarse-grained and does not distinguish whether a permission has been declared by a trusted or an untrusted principal. This allows malicious applications to perform privilege escalation attacks on the mobile platform. To make things worse, applications might include third- party libraries, for advertising or common recognition tasks. Such libraries share the process address space with their host apps and as such can inherit all the privileges the host app does. Identifying and mitigating these problems on smartphones is not a trivial process. Manual analysis on its own of all mobile apps is cumbersome and impractical, code analysis techniques suffer from scalability and coverage issues, ad-hoc approaches are impractical and susceptible to mistakes, while sometimes vulnerabilities are well hidden at the interplays between smartphone tenants and resources. In this work I follow an analytical approach to discover major security and privacy issues on smartphone platforms. I utilize the Android OS as a use case, because of its open-source nature but also its popularity. In particular I focus on the multi-tenancy characteristic of smartphones and identify the re- sources each tenant within a process, across processes and across devices can access. I design analytical tools to automate the discovery process, attacks to better understand the adversary models, and introduce design changes to the participating systems to enable robust fine-grained access control of resources. My approach revealed a new understanding of the threats introduced from third-party libraries within an application process; it revealed new capabilities of the mobile application adversary exploiting shared filesystem and permission resources; and shows how a mobile app adversary can exploit shared communication mediums to compromise the confidentiality of the data collected by external devices (e.g. fitness and medical accessories, NFC tags etc.). Moreover, I show how we can eradicate these problems following an architectural design approach to introduce backward-compatible, effective and efficient modifications in operating systems to achieve fine-grained application access to shared resources. My work has let to security changes in the official release of Android by Google

Power Consumption Analysis, Measurement, Management, and Issues:A State-of-the-Art Review of Smartphone Battery and Energy Usage

The advancement and popularity of smartphones have made it an essential and all-purpose device. But lack of advancement in battery technology has held back its optimum potential. Therefore, considering its scarcity, optimal use and efficient management of energy are crucial in a smartphone. For that, a fair understanding of a smartphone's energy consumption factors is necessary for both users and device manufacturers, along with other stakeholders in the smartphone ecosystem. It is important to assess how much of the device's energy is consumed by which components and under what circumstances. This paper provides a generalized, but detailed analysis of the power consumption causes (internal and external) of a smartphone and also offers suggestive measures to minimize the consumption for each factor. The main contribution of this paper is four comprehensive literature reviews on: 1) smartphone's power consumption assessment and estimation (including power consumption analysis and modelling); 2) power consumption management for smartphones (including energy-saving methods and techniques); 3) state-of-the-art of the research and commercial developments of smartphone batteries (including alternative power sources); and 4) mitigating the hazardous issues of smartphones' batteries (with a details explanation of the issues). The research works are further subcategorized based on different research and solution approaches. A good number of recent empirical research works are considered for this comprehensive review, and each of them is succinctly analysed and discussed

Overcoming the Intuition Wall: Measurement and Analysis in Computer Architecture

These are exciting times for computer architecture research. Today there is significant demand to improve the performance and energy-efficiency of emerging, transformative applications which are being hammered out by the hundreds for new computing platforms and usage models. This booming growth of applications and the variety of programming languages used to create them is challenging our ability as architects to rapidly and rigorously characterize these applications. Concurrently, hardware has become more complex with the emergence of accelerators, multicore systems, and heterogeneity caused by further divergence between processor market segments. No one architect can now understand all the complexities of many systems and reason about the full impact of changes or new applications. To that end, this dissertation presents four case studies in quantitative methods. Each case study attacks a different application and proposes a new measurement or analytical technique. In each case study we find at least one surprising or unintuitive result which would likely not have been found without the application of our method