PiMiCo: Privacy Preservation via Migration in Collaborative Mobile Clouds

Abstract

The proliferation of mobile devices and mobile clouds coupled with a multitude of their sensing abilities is creating interesting possibilities; the sensing capabilities are creating different types and fidelities of data in a geographically distributed manner that can be used to build new kinds of peer-topeer applications. However, the data generated by these mobile devices can be personal and of a highly confidential nature. While very interesting possibilities exist for collaborating on the diverse, shared data in real time, privacy policies on the data sharing, transport, as well as usage must be clearly specified and respected. The goal of this work is to introduce a privacy preserving data centric programming model for building collaborative applications in large scale mobile clouds and discuss its design.Our work introduces several concepts and leverages privacy annotations and a transparent execution migration framework to achieve our goals. We also present an evaluation using several applications demonstrating that overheads are minimal and can be used in a real-time setting.

Mobile edge computing, Fog et al.: A survey and analysis of security threats and challenges

“…Besides, there is a multitude of data privacy mechanisms specifically developed for the mobile cloud computing paradigm. These mechanisms tackle several challenges such as enforcing privacy policies when migrating code and data amongst collaborating mobile devices [115], and concealing the location of a set of clients that are located in the same geographical area by means of establishing a peer-to-peer network [116]. These mechanisms are designed for a collaborative cloud of local devices, yet they only require that all devices are interconnected and know their physical location.…”

A novel trust model for fog computing using fuzzy neural networks and weighted weakest link

“…Attacks' consequences could be similar to traditional cyber-attacks; however, new attacks with serious impacts might be orchestrated, such as injection of manipulated information during a collaboration session, the deployment of disguised services and searching for victims with specific vulnerabilities. Multiple security facets have been discussed, including identity and authentication (Toosi et al, 2014;Touceda et al, 2015), access control systems (McCarthy et al, 2015;Huang et al, 2014;Vassilakis et al, 2016;Dsouza et al, 2014), protocol and network security (Kreutz et al, 2015;Li and Chen, 2015;Chen et al, 2016), intrusion detection systems (Mtibaa et al, 2015;Gai et al, 2016;Shi et al, 2015) and privacy (Ravichandran et al, 2015;Zhang et al, 2015;Huang et al, 2016). This paper focuses on trust, however, these topics have been briefly referred-to when necessary.…”