Visible to the public Biblio

Filters: Author is Li, X. Y.  [Clear All Filters]
2017-12-12
Ullah, S., Li, X. Y., Zhang, L..  2017.  A Review of Signcryption Schemes Based on Hyper Elliptic Curve. 2017 3rd International Conference on Big Data Computing and Communications (BIGCOM). :51–58.

Now-a-days security is a challenging task in different types of networks, such as Mobile Networks, Wireless Sensor Networks (WSN) and Radio Frequency Identifications Systems (RFIS) etc, to overcome these challenges we use sincryption. Signcryption is a new public key cryptographic primitive that performs the functions of digital signature and encryption in single logical step. The main contribution of signcrytion scheme, it is more suitable for low constrained environment. Moreover some signcryption schemes based on RSA, Elliptic Curve (EC) and Hyper Elliptic Curve (HEC). This paper contains a critical review of signcryption schemes based on hyper elliptic curve, since it reduce communication and computational costs for low constrained devices. It also explores advantages and disadvantages of different signcryption schemes based on HEC.

2017-11-20
Du, H., Jung, T., Jian, X., Hu, Y., Hou, J., Li, X. Y..  2016.  User-Demand-Oriented Privacy-Preservation in Video Delivering. 2016 12th International Conference on Mobile Ad-Hoc and Sensor Networks (MSN). :145–151.

This paper presents a framework for privacy-preserving video delivery system to fulfill users' privacy demands. The proposed framework leverages the inference channels in sensitive behavior prediction and object tracking in a video surveillance system for the sequence privacy protection. For such a goal, we need to capture different pieces of evidence which are used to infer the identity. The temporal, spatial and context features are extracted from the surveillance video as the observations to perceive the privacy demands and their correlations. Taking advantage of quantifying various evidence and utility, we let users subscribe videos with a viewer-dependent pattern. We implement a prototype system for off-line and on-line requirements in two typical monitoring scenarios to construct extensive experiments. The evaluation results show that our system can efficiently satisfy users' privacy demands while saving over 25% more video information compared to traditional video privacy protection schemes.