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In this paper we investigate the risk of privacy leakage through mobile analytics services and demonstrate the ease with which an external adversary can extract individual's profile and mobile applications usage information, through two major mobile analytics services, i.e. Google Mobile App Analytics and Flurry. We also demonstrate that it is possible to exploit the vulnerability of analytics services, to influence the ads served to users' devices, by manipulating the profiles constructed by these services. Both attacks can be performed without the necessity of having an attacker controlled app on user's mobile device. Finally, we discuss potential countermeasures (from the perspectives of different parties) that may be utilized to mitigate the risk of individual's personal information leakage.

Abstract-Smart household appliances, ranging from lightbulbs and door-locks to power switches and smoke-alarms, are rapidly emerging in the marketplace, with predictions that over 2 billion devices will be installed within the next four years. However, security implementations vary widely across these devices, while privacy implications are unclear to users. In this paper we dissect the behavior of a few household devices, specifically the Phillips Hue light-bulb, the Belkin WeMo power switch, and the Nest smoke-alarm, and highlight the ease with which security and privacy can be compromised. We then propose a new solution to protect such devices by restricting access at the network-level. Our solution does not require changes from device manufacturers, reduces burden on the end-users, and allows security to be offered as an overlay service by the ISP or from a specialist provider in the cloud.

The increasing heterogeneity and asymmetry in wireless network environments makes QoS guarantees in terms of delays and throughput a challenging task. In this paper, we study a novel scheduling algorithm for multipath transport called Delay Aware Packet Scheduling (DAPS) which aims to reduce the receiver's buffer blocking time considered as a main parameter to enhance the QoS in wireless environments. We develop an analytical model of maximum receiver's buffer blocking time and extend the DAPS algorithm considering implementation issues. Performance evaluations based on ns-2 simulations highlight the enhanced QoS that DAPS can provide. With reference to the classical multipath transport protocol CMT-SCTP, we observe a significant reductions of the receiver's buffer occupancy, down by 77%, and the application delay, down by 63%.

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