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AKA-PLA: Enhanced AKA Based on Physical Layer Authentication
( Jing Yang ),( Xinsheng Ji ),( Kaizhi Huang ),( Ming Yi ),( Yajun Chen ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.7
Existing authentication mechanisms in cellular mobile communication networks are realized in the upper layer by employing cryptographic techniques. Authentication data are broadcasted over the air in plaintext, enabling attackers to completely eavesdrop on the authentication and get some information about the shared secret key between legitimate nodes. Therefore, reusing the same secret key to authenticate several times results in the secret key`s information leakage and high attacking rate. In this paper, we consider the most representative authentication mechanism, Authentication and Key Agreement (AKA), in cellular communication networks and propose an enhanced AKA scheme based on Physical Layer Authentication (AKA-PLA). Authentication responses generated by AKA are no longer transmitted in plaintext but masked by wireless channel characteristics, which are not available to adversaries, to generate physical layer authentication responses by a fault-tolerant hash method. The authenticator sets the threshold according to the authentication requirement and channel condition, further verifies the identity of the requester based on the matching result of the physical layer authentication responses. The performance analyses show that the proposed scheme can achieve lower false alarm rate and missing rate, which are a pair of contradictions, than traditional AKA. Besides, it is well compatible with AKA.
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Image Stitching with Robust Principal Component Analysis
Wei Tao,Zhang Yongxin,Yuan Yating,Ji Xinsheng 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.12
An image stitching algorithm based on the robustness of principal component analysis (RPCA) is proposed in an effort to suppress the influence of noise in the image stitching quality. This algorithm represents high dimensional feature data by utilizing a lower dimensional linear subspace, and converts the image stitching problem into a principal component matrix matching problem. Through the use of a low rank matrix, the extraction of salient image characteristics is recovered and the noise interference is reduced during the enhancement process. Together, with the advantages of the RPCA algorithm, the algorithm improves the PSNR of the image while maintaining its strong matching ability. Experimental results show that the proposed scheme is able to significantly inhibit the noise and improve the stitching quality in comparison to the other existing stitching methods.
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( Chen Yajun ),( Yi Ming ),( Zhong Zhou ),( Ma Keming ),( Huang Kaizhi ),( Ji Xinsheng ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.10
In this paper, a secure transmission scheme based on the artificial noise is proposed for D2D communications underlaying the full-duplex cellular network, and a secure power allocation scheme to maximize the overall secrecy rate of both the cellular user and D2D transmitter node is presented. Firstly, the full-duplex base station transmits the artificial noise to guarantee the secure communications when it receives signals of cellular uplinks. Under this secure framework, it is found that improving the transmission power of the cellular user or the D2D transmitter node will degrade the secrecy rate of the other, although will improve itself secrecy rate obviously. Hence, a secure power allocation scheme to maximize the overall secrecy rate is presented subject to the security requirement of the cellular user. However, the original power optimization problem is non-convex. To efficiently solve it, we recast the original problem into a convex program problem by utilizing the proper relaxation and the successive convex approximation algorithm. Simulation results evaluate the effectiveness of the proposed scheme.
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Traffic Forecast Assisted Adaptive VNF Dynamic Scaling
Hang Qiu,Hongbo Tang,Yu Zhao,Wei You,Xinsheng Ji 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.11
NFV realizes flexible and rapid software deployment and management of network functions in the cloud network, and provides network services in the form of chained virtual network functions (VNFs). However, using VNFs to provide quality guaranteed services is still a challenge because of the inherent difficulty in intelligently scaling VNFs to handle traffic fluctuations. Most existing works scale VNFs with fixed-capacity instances, that is they take instances of the same size and determine a suitable deployment location without considering the cloud network resource distribution. This paper proposes a traffic forecasted assisted proactive VNF scaling approach, and it adopts the instance capacity adaptive to the node resource. We first model the VNF scaling as integer quadratic programming and then propose a proactive adaptive VNF scaling (PAVS) approach. The approach employs an efficient traffic forecasting method based on LSTM to predict the upcoming traffic demands. With the obtained traffic demands, we design a resource-aware new VNF instance deployment algorithm to scale out under-provisioning VNFs and a redundant VNF instance management mechanism to scale in over-provisioning VNFs. Trace-driven simulation demonstrates that our proposed approach can respond to traffic fluctuation in advance and reduce the total cost significantly.
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