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LEVERAGING THE TAIL TIME FOR BATCHING AND PREFETCHING TO REDUCE ENERGY CONSUMPTION IN CELLULAR NETWORKS

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In cellular networks, inactivity timers are used to control the release of radio resources. However, considerable radio resources and battery energy are wasted in the tail time. In this abstract, we proposed TailTheft, which leverages the tail time for batching and pre fetching. Our work is the first to consider using rather than eliminating the […]

LOCX: A NOVEL APPROACH FOR PRESERVING LOCATION PRIVACY IN GEOSOCIAL APPLICATIONS

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In this abstract, we propose LocX (short for location to index mapping), a novel approach to achieving user privacy while maintaining full accuracy in location-based social applications (LBSAs from here on-ward). Our insight is that many services do not need to resolve distance-based queries between arbitrary pairs of users, but only between friends interested in […]

LOCATION PRIVACY PRESERVING IN GEOSOCIAL APPLICATIONS

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In this abstract, we introduce LocX, a novel alternative that provides significantly improved location privacy without adding uncertainty into query results or relying on strong assumptions about server security. Our key insight is to apply secure user-specific, distance-preserving coordinate transformations to all location data shared with the server. The friends of a user share this […]

LOCX: A NOVEL APPROACH FOR PRESERVING LOCATION PRIVACY IN GEOSOCIAL APPLICATIONS

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In this abstract, we propose LocX (short for location to index mapping), a novel approach to achieving user privacy while maintaining full accuracy in location-based social applications (LBSAs from here on-ward). Our insight is that many services do not need to resolve distance-based queries between arbitrary pairs of users, but only between friends interested in […]

TAILTHEFT SCHEME FOR REDUCE ENERGY CONSUMPTION IN CELLULAR NETWORKS

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Inactivity timers in cellular networks are used to balance the trade-offs between resource efficiency for enhanced user experience and low management overhead. However, considerable radio resources and battery energy are wasted in the tail time. In this abstract, we proposed TailTheft, which leverages the tail time for batching and pre fetching. Our work is the […]

PUBLIC SENTIMENT VARIATIONS ANALYZING ON TWITTER

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Twitter has become a social site where millions of users can exchange their opinion. Sentiment analysis on Twitter data has provided an economical and effective way to expose public opinion timely, which is critical for decision making in various domains. In this work, we move one step further to interpret sentiment variations. We observed that […]

HARD AI PROBLEMS BASED CAPTCHA AS GRAPHICAL PASSWORDS SECURITY PRIMITIVE

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In this abstract, we introduce a new security primitive based on hard AI problems, namely, a novel family of graphical pass-word systems integrating Captcha technology, which we call CaRP (Captcha as gRaphical Passwords). CaRP is click-based graphical passwords, where a sequence of clicks on an image is used to derive a password. Unlike other click-based […]

TRACKING AND ANALYZING THE PUBLIC SENTIMENT VARIATIONS ON TWITTER

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In this abstract, we analyze public sentiment variations on Twitter and mine possible reasons behind such variations. To track public sentiment, we combine two state-of-the-art sentiment analysis tools to obtain sentiment information towards interested targets (e.g., “Obama”) in each tweet. Based on the sentiment label obtained for each tweet, we can track the public sentiment […]

CARP SCHEME FOR SECURITY PRIMITIVE BASED ON HARD AI PROBLEMS

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Using hard AI (Artificial Intelligence) problems for security is an exciting new paradigm. Under this paradigm, the most notable primitive invented is Captcha, which distinguishes human users from computers by presenting a challenge, i.e., a puzzle, beyond the capability of computers but easy for humans. Captcha is now a standard Internet security technique to protect […]

COOPERATIVE SPECTRUM SHARING BETWEEN ONE PRIMARY USER AND MULTIPLE SECONDARY USERS UNDER INCOMPLETE INFORMATION

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Contract theory is effective in designing incentive compatible mechanisms in a monopoly market under incomplete information, where the employer needs to sign a contract with employees before fully knowing their private information. The key idea is to offer the right contract items so that all agents have the incentive to truthfully reveal their private information. […]