Details of Research Outputs

Status已发表Published
TitleArtificial intelligence aware and security-enhanced traceback technique in mobile edge computing
Creator
Date Issued2020-09-01
Source PublicationComputer Communications
ISSN0140-3664
Volume161Pages:375-386
Abstract

Sensor network, as one component of mobile edge computing (MEC), is a promising platform to provide services for users. With the development of artificial intelligence (AI) applications, the integration of mobile edge computing and AI unlocks unlimited possibilities in people's daily lives. However, AI techniques and mechanisms specifically designed for the devices and servers operating in the mobile edge computing environment face secure challenge. To improve the security of wireless network, a security-enhanced traceback (SET) scheme is proposed. Firstly, the network is divided into three areas, nodes in different areas adopt different marking probability. Nodes in the area far from the sink adopt higher marking probability, nodes in the area nearest to the sink adopt lower marking probability to save energy. Secondly, the marking tuple of data packets is not only stored in nodes, but also is migrated to nodes far from the sink to balance the storage space of nodes. The results of both theoretical analysis and extensive experimental simulations indicate that the network performance of SET scheme is better than the existing traceback scheme.

KeywordArtificial intelligence Lifetime Mobile computing Probability marking and migrating Traceback
DOI10.1016/j.comcom.2020.08.006
URLView source
Indexed BySCIE
Language英语English
WOS Research AreaComputer Science ; Engineering ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS IDWOS:000575729300012
Scopus ID2-s2.0-85089410050
Citation statistics
Cited Times:29[WOS]   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/7115
CollectionResearch outside affiliated institution
Corresponding AuthorLiu, Xiao
Affiliation
1.School of Computer Science and Engineering, Central South University, ChangSha, 410083, China
2.College of Computer Science and Technology, Huaqiao University, Xiamen, 361021, China
3.School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, 411201, China
4.School of Electronic and Information Engineering, South China University of Technology, Guangzhou, 510641, China
Recommended Citation
GB/T 7714
Liu, Yuxin,Wang, Tian,Zhang, Shaoboet al. Artificial intelligence aware and security-enhanced traceback technique in mobile edge computing[J]. Computer Communications, 2020, 161: 375-386.
APA Liu, Yuxin, Wang, Tian, Zhang, Shaobo, Liu, Xuxun, & Liu, Xiao. (2020). Artificial intelligence aware and security-enhanced traceback technique in mobile edge computing. Computer Communications, 161, 375-386.
MLA Liu, Yuxin,et al."Artificial intelligence aware and security-enhanced traceback technique in mobile edge computing". Computer Communications 161(2020): 375-386.
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