Visible to the public Biblio

Filters: Author is Han, Xu  [Clear All Filters]
2022-05-06
Peng, Zheng, Han, Xu, Ye, Yun.  2021.  Enhancing Underwater Sensor Network Security with Coordinated Communications. ICC 2021 - IEEE International Conference on Communications. :1—6.
In recent years, the underwater sensor network has emerged as a promising solution for a wide range of marine applications. The underwater wireless sensors are usually designed to operate in open water, where eavesdropping can be a serious issue. Existing work either utilizes cryptography that is computationally intensive or requires expensive hardware. In this paper, we present a coordinated multi-point transmission based protocol to improve network security. The proposed protocol dynamically pairs sensors for coordinated communications to undermine the eavesdroppers’ capability. Our preliminary results indicate that the underwater sensor network security can be enhanced using the proposed method, especially in applications where cryptography or special hardware are not suitable.
2020-09-28
Han, Xu, Liu, Yanheng, Wang, Jian.  2018.  Modeling and analyzing privacy-awareness social behavior network. IEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). :7–12.
The increasingly networked human society requires that human beings have a clear understanding and control over the structure, nature and behavior of various social networks. There is a tendency towards privacy in the study of network evolutions because privacy disclosure behavior in the network has gradually developed into a serious concern. For this purpose, we extended information theory and proposed a brand-new concept about so-called “habitual privacy” to quantitatively analyze privacy exposure behavior and facilitate privacy computation. We emphasized that habitual privacy is an inherent property of the user and is correlated with their habitual behaviors. The widely approved driving force in recent modeling complex networks is originated from activity. Thus, we propose the privacy-driven model through synthetically considering the activity impact and habitual privacy underlying the decision process. Privacy-driven model facilitates to more accurately capture highly dynamical network behaviors and figure out the complex evolution process, allowing a profound understanding of the evolution of network driven by privacy.
2019-01-21
Han, Xu, Tian, Daxin, Duan, Xuting, Sheng, Zhengguo, Wang, Yunpeng, Leung, Victor C.M..  2018.  Optimized Anonymity Updating in VANET Based on Information and Privacy Joint Metrics. Proceedings of the 8th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications. :63–69.
With the continuous development of the vehicular ad hoc network (VANET), many challenges related to network security have come one after another, among which privacy issues are particularly prominent. To help each network user decide when and where to protect their privacy, we suggest creating a user-centric privacy computing system in VANET. A risk assessment function and a set of decision weights are proposed to simulate the driver's decision-making intent in the vehicle network. Besides, proposed information and privacy joint metrics are used as the key indicators for dynamic selection of Mix-zone. Finally, by considering three influencing factors: maximum road capacity, user-centric quantitative privacy and attacker information measurement, defined mixzone creation mechanism to achieve privacy protection in VANET.