Biblio

Filters: Author is J. Zhang  [Clear All Filters]
2018-05-14
J. Zhang, Z. Chu, L. Sankar, O. Kosut.  2017.  Can Attackers with Limited Information Exploit Historical Data to Mount Successful False Data Injection Attacks on Power Systems? IEEE Transactions on Power Systems.

submitted

Z. Chu, J. Zhang, O. Kosut, L. Sankar.  2017.  Vulnerability Assessment of Power Systems to False Data Injection Attacks. IEEE Transactions on Smart Grid.

under review

J. Zhang, Z. Chu, L. Sankar, O. Kosut.  2016.  False data injection attacks on power system state estimation with limited information. 2016 IEEE Power and Energy Society General Meeting (PESGM). :1-5.
J. Zhang, L. Sankar.  2016.  Physical System Consequences of Unobservable State-and-Topology Cyber-Physical Attacks. IEEE Transactions on Smart Grid. 7:2016-2025.
Z. Chu, J. Zhang, O. Kosut, L. Sankar.  2016.  Evaluating power system vulnerability to false data injection attacks via scalable optimization. 2016 IEEE International Conference on Smart Grid Communications (SmartGridComm). :260-265.
2017-02-23
J. Zhang.  2015.  "Semantic-Based Searchable Encryption in Cloud: Issues and Challenges". 2015 First International Conference on Computational Intelligence Theory, Systems and Applications (CCITSA). :163-165.

Searchable encryption is a new developing information security technique and it enables users to search over encrypted data through keywords without having to decrypt it at first. In the last decade, many researchers are engaging in the field of searchable encryption and have proposed a series of efficient search schemes over encrypted cloud data. It is the time to survey this field to conclude a comprehensive framework by analyzing individual contributions. This paper focuses on the searchable encryption schemes in cloud. We firstly summarize the general model and threat model in searchable encryption schemes, and then present the privacy-preserving issues in these schemes. In addition, we compare the efficiency and security between semantic search and preferred search in detail. At last, some open issues and research challenges in the future are proposed.