Analysis and Detection of Anomalies in Mobile Devices

• Main Author: de Lima, António Carlos Lagarto Cabral Bastos
• Format: Dissertation
• Language: English
• Published: ProQuest Dissertations & Theses 01-01-2017
• Subjects: Architecture; Artificial intelligence; Batch processing; Computer science; Events planning; Global positioning systems; GPS; Internet of Things; Machine learning; Operating systems; Random access memory; Virtual private networks; Web Studies
• ISBN: 9798841539438

Organizations are often faced with the need to manage large numbers of mobile device assets, including tight control over aspects such as usage profiles, customization, applications and security. Moreover, the rise of the Bring Your Own Device (BYOD) paradigm has further contributed to hamper these requirements, making it difficult to strike a balance between corporate regulations and freedom of usage.In this scope, security is one of the main requirements both for individual and corporate usage. Device and information protection on mobile ecosystems is quite different from securing other assets such as laptops or desktops, due to specific characteristics and restrictions. For instance, the resource consumption overhead of security mechanisms, which is less relevant for desktop/laptop environments, is critical for mobile devices which frequently have less computing power and must keep power consumption as low as possible.Security mechanisms for mobile devices combine preventive tools (e.g. Trusted Execution Environments and sandboxed applications), monitoring solutions and reactive and mitigation techniques. In this thesis we start by overviewing these security solutions, presenting a survey on the technologies, frameworks and use cases for mobile device security monitoring and management, with an emphasis on the associated open challenges and benefits, from both the end-user and the corporate points-of-view.Having analyzed the technological state of the art, we showcase our attempt at analyzing and detecting anomalies in mobile devices on an enterprise scenario, the contemplated and solved implementation ordeals, and the employed development details to achieve it. The described system is comprised of: an Android application, intended to be installed on the target devices; lightweight Message Brokers; a Central Aggregator, serving as the core of the system, processing and managing the collected data from the mobile assets; a Monitoring Dashboard, enabling the system to be altered at runtime by supervising humans.Lastly, we evaluate the project, exhibiting the preliminary results obtained through the developed system, examining the implications that the results warrant, assessing the current state of the project's proposed tasks and requirements, and proposing the course of action for future work.