It is a challenging concern in data collecting, publishing, and mining when personal information is controlled by untrustworthy cloud services with unpredictable risks for privacy leakages. In this paper, we formulate an information-theoretic model for privacy protection and present a concrete solution to theoretical architecture in privacy computing from the perspectives of quantification and optimization. Thereinto, metrics of privacy and utility for randomized response (RR) which satisfy differential privacy are derived as average mutual information and average distortion rate under the information-theoretic model. Finally, a discrete multiobjective particle swarm optimization (MOPSO) is proposed to search optimal RR distorted matrices. To the best of our knowledge, our proposed approach is the first solution to optimize RR distorted matrices using discrete MOPSO. In detail, particles’ position and velocity are redefined in the problem-guided initialization and velocity updating mechanism. Two mutation strategies are introduced to escape from local optimum. The experimental results illustrate that our approach outperforms existing state-of-the-art works and can contribute optimal Pareto solutions of extensive RR schemes to future study.

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A method based on the leader-follower algorithm is proposed for transformation among the formations. The introduction of the greedy algorithm, behavior-based control and virtual structure help realize the region division and the calculation of the distribution of the leaders and followers in target formation. Collision detection and collision avoidance are proposed to solve path conflicts with error free feedback and effectively maintain the stability of motion. The modeling of transformation is simulated by the shape from a line to a wedged, in which the formation is adjusted by the distance difference obtained by feedback. The experimental results show that it is feasible and effective to implement the formation conversion and formation control, and the system possess a better robustness and stability.

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