Adaptive context-aware security for android and IoT smart applications

Abstract

The notion of Context-Awareness of mobile applications is drawing more attention, where many applications need to adapt to physical environments of users and devices, such as location, time, connectivity, resources, etc. Also, predicting context-aware activities using machine learning techniques is evolving to become more readily available as a major driver of the growth of IoT applications to match the needs of the future smart autonomous environments. However, with today’s increasing security risks in emerging cloud technologies, sharing massive data capabilities, imposing regulations requirements on privacy, and the emergence of new technologies of multi-users, multi-profiles, multi-devices, there is a growing need for new approaches to address the new challenges of autonomous context-awareness and its fine-grained security enforcement models. Recently, many research interests have been drawn targeting different aspects of Context Awareness in Android security and in IoT smart environments. Yet, none of the existing works fulfills our real scenarios requirements for automated creation of context-aware policies, and the automated encryption according to these auto-generated policies. From these premises, this dissertation fills the lack of the existing research outcomes. Particularly, the contributions of this thesis are threefold: (1) Providing a policy enforcement framework for Inter-App communication between Android applications to mitigate privacy leakage. (2) Defining a formal context-aware policy specification language that effectively describe users defined consents. (3) Providing a novel secure dynamic creation of context aware policies, which has been achieved through smart learning techniques that leverages Attribute-Based Encryption (ABE) for dynamic encryption. Various prototypes have been developed and evaluated via extensive experiments through which the results have proved the efficiency of the proposed solutions. Finally, the solution fulfils the new imposed privacy regulations and leverages full power of IoT smart environments.

Date	9 Aug 2023
Original language	American English
Awarding Institution	École de technologie supérieure
Supervisor	Chamseddine Talhi (Supervisor)