Accéleration des traitements de la sécurité mobile avec le calcul parallèle

Abstract

Accelerating mobile security processing is becoming one of the most challenging problems. It is important to protect sensitive information in mobile phones through malware detection systems and data encryption to maintain a high security level. In fact, malware detection on mobile phones involves analyzing and matching large amount of data streams against a set of known malware signatures. Unfortunately, as the number of threats grows continuously, the number of malware signatures grows proportionally. This is time-consuming and leads to expensive computation costs, especially for mobile devices where memory, power and computation capabilities are limited. As the security threat level is getting worse, parallel computation capabilities for mobile phones is getting better with the evolution of mobile graphical processing units (GPUs). This thesis focuses on how we can get benefit from the evolving parallel processing capabilities of mobile devices in order to accelerate malware detection as well as cryptographic processing on Android mobile phones. For this purpose, we have designed and implemented a parallel architecture for mobile devices that exploits the computation capabilities of mobile GPUs and distributed processing on clusters. A series of computation and memory optimization techniques are proposed to increase the detection and processing throughput. The results suggest that mobile graphic cards can be used effectively to accelerate malware detection for mobile phones as well as cryptographic processing. The results show also that the local processing on mobile phones can be extended to cluster architecture in order to have more interesting processing acceleration rates when the mobile phone is busy.

Date	31 Mar 2016
Original language	French
Awarding Institution	École de technologie supérieure
Supervisor	Chamseddine Talhi (Supervisor) & Wahab Hamou-Lhadj (Co-supervisor)