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Wireless video sensor networks are anticipated to be deployed to monitor remote geographical areas. To save energy in bit transmissions/receptions over a video sensor network, the captured video content needs to be encoded before its transmission to the base station. However, video encoding is an inherently complex operation that can cause a major energy drain at battery-constrained sensors. Thus a systematic evaluation of different video encoding options is required to allow a designer to choose the most energy-efficient compression technique for a given video sensing application scenario. In this paper, we empirically evaluate the energy efficiencies of predictive and distributed video coding paradigms for deployment on real-life sensor motes. For predictive video coding, our results show that despite its higher compression efficiency, inter video coding always depletes much more energy than intra coding. Therefore, we propose to use image compression based intra coding to improve energy efficiency in the predictive video coding paradigm. For distributed video coding, our results show that the Wyner-Ziv encoder has consistently better energy efficiency than the PRISM encoder. We propose minor modifications to PRISM and Wyner-Ziv encoders which significantly reduce the energy consumption of these encoders. For all the video encoding configurations evaluated in this paper, our results reveal the counter-intuitive and important finding that the major source of energy drain in WSNs is local computations performed for video compression and not video transmission.

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Implicit authentication schemes are a secondary authentication mechanism that provides authentication by employing unique patterns of device use that are gathered from smartphone users without requiring deliberate actions. Contemporary implicit authentication schemes operate at the device level such that they neither discriminate between data from different applications nor make any assumption about the nature of the application that the user is currently using. In this paper, we challenge the device-centric approach to implicit authentication on smartphones. We argue that the conventional approach of misuse detection at the device level has inherent limitations for mobile platforms. To this end, we analyze and empirically evaluate the devicecentric nature of implicit authentication schemes to show their limitations in terms of detection accuracy, authentication overhead, and fine grained authentication control. To mitigate these limitations and for effective and pragmatic implicit authentication on the mobile platform, we propose a novel application-centric implicit authentication approach. We observe that for implicit authentication, an application knows best on when to authenticate and how to authenticate. Therefore, we delegate the implicit authentication task to the application and let the application provider decide when and how to authenticate a user in order to protect the owner's personal information. Our proposed applicationcentric implicit authentication approach improves accuracy and provides fine grained authentication control with low authentication overhead. Future research in this domain will benefit from our findings to provide pragmatic implicit authentication solutions.

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