Darshan Vishwasrao Medhane

TL;DR: A method for conserving position confidentiality of roaming PBSs users using machine learning techniques is proposed and it is confirmed that the proposed method achieved above 90% of the position confidentiality in PBSs.

TL;DR: The results obtained show that the proposed security framework can efficiently and effectively meet the data confidentiality challenges introduced by the integration of blockchain, edge cloud, and SDN paradigm.

TL;DR: An energy-aware green adversary model that runs on real-time anticipatory position-based query scheduling in order to minimize the communication and computation cost for each query, thus, facilitating energy consumption minimization.

TL;DR: The proposed SSMOEA algorithm is good and competitive in comparison to the existing EMO algorithms from the viewpoint of finding a scattered and estimated solution set in multi-objective optimization problems and can achieve a good trade-off between search space convergence and search space diversity in the appropriate experimental setup.

TL;DR: PCCA, a novel position confidentiality conserving algorithm for content protection in e-Governance is proposed by means of rule-based approach from computational intelligence and users current position information and evaluation demonstrates that PCCA can efficiently conserve roaming users position confidentiality while accomplishing better performance, guaranteed position confidentiality, and better quality of service in e.Governance.