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In this paper, we design a friendly jammer selection scheme for the social Internet of Things (IoT). A typical social IoT is composed of a cellular network with underlaying Device-to-Device (D2D) communications. In our scheme, we consider signal characteristics over a physical layer and social attribute information of an application layer simultaneously. Using signal characteristics, one of the D2D gadgets is selected as a friendly jammer to improve the secrecy performance of a cellular device. In return, the selected D2D gadget is allowed to reuse spectrum resources of the cellular device. Using social relationship, we analyze and quantify the social intimacy degree among the nodes in IoT to design an adaptive communication time threshold. Applying an artificial intelligence forecasting model, we further forecast and update the intimacy degree, and then screen and filter potential devices to effectively reduce the detection and calculation costs. Finally, we propose an optimal scheme to integrate the virtual social relationship with actual communication systems. To select the optimal D2D gadget as a friendly jammer, we apply Kuhn-Munkres (KM) algorithm to solve the maximization problem of social intimacy and cooperative jamming. Comprehensive numerical results are presented to validate the performance of our scheme.


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A Cross-Layer Cooperative Jamming Scheme for Social Internet of Things

Show Author's information Yan Huo( )Jingjing FanYingkun WenRuinian Li
School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China.
Department of Computer Science, Bowling Green State University, Bowling Green, OH 43403, USA.

Abstract

In this paper, we design a friendly jammer selection scheme for the social Internet of Things (IoT). A typical social IoT is composed of a cellular network with underlaying Device-to-Device (D2D) communications. In our scheme, we consider signal characteristics over a physical layer and social attribute information of an application layer simultaneously. Using signal characteristics, one of the D2D gadgets is selected as a friendly jammer to improve the secrecy performance of a cellular device. In return, the selected D2D gadget is allowed to reuse spectrum resources of the cellular device. Using social relationship, we analyze and quantify the social intimacy degree among the nodes in IoT to design an adaptive communication time threshold. Applying an artificial intelligence forecasting model, we further forecast and update the intimacy degree, and then screen and filter potential devices to effectively reduce the detection and calculation costs. Finally, we propose an optimal scheme to integrate the virtual social relationship with actual communication systems. To select the optimal D2D gadget as a friendly jammer, we apply Kuhn-Munkres (KM) algorithm to solve the maximization problem of social intimacy and cooperative jamming. Comprehensive numerical results are presented to validate the performance of our scheme.

Keywords: artificial intelligence, Internet of Things (IoT), Device-to-Device (D2D) communications, social network, cooperative jamming

References(47)

[1]
B. Khalfi, B. Hamdaoui, and M. Guizani, Extracting and exploiting inherent sparsity for efficient IoT support in 5G: Challenges and potential solutions, IEEE Wireless Communications, vol. 24, no. 5, pp. 68-73, 2017.
[2]
Y. Zhang, B. Wu, Y. Liu, and J. Lv, Local community detection based on network motifs, Tsinghua Science and Technology, vol. 24, no. 6, pp. 716-727, 2019.
[3]
Z. Cai and X. Zheng, A private and efficient mechanism for data uploading in smart cyber-physical systems, IEEE Transactions on Network Science and Engineering, vol. 7, no. 2, pp. 766-775, 2020.
[4]
J. Mao, Y. Zhang, P. Li, T. Li, Q. Wu, and J. Liu, A position-aware merkle tree for dynamic cloud data integrity verification, Soft Computing, vol. 21, no. 8, pp. 2151-2164, 2017.
[5]
M. Waqas, Y. Niu, Y. Li, M. Ahmed, D. Jin, S. Chen, and Z. Han, Mobility-aware device-to-device communications: Principles, practice and challenges, IEEE Communications Surveys & Tutorials, .
[6]
X. Zheng and Z. Cai, Privacy-preserved data sharing towards multiple parties in industrial IoTs, IEEE Journal on Selected Areas in Communications, vol. 38, no. 5, pp. 968-979, 2020.
[7]
F. Jameel, Z. Hamid, F. Jabeen, S. Zeadally, and M. A. Javed, A survey of device-to-device communications: Research issues and challenges, IEEE Communications Surveys & Tutorials, vol. 20, no. 3, pp. 2133-2168, 2018.
[8]
R. Ansari, C. Chrysostomou, S. A. Hassan, M. Guizani, S. Mumtaz, J. Rodriguez, and J. Rodrigues, 5G D2D networks: Techniques, challenges, and future prospects, IEEE Systems Journal, vol. 12, no. 4, pp. 3970-3984, 2018.
[9]
X. Xing, T. Jing, W. Cheng, Y. Huo, and X. Cheng, Spectrum prediction in cognitive radio networks, IEEE Wireless Communications, vol. 20, no. 2, pp. 90-96, 2013.
[10]
J. A. Stine and C. E. C. Bastidas, Enabling spectrum sharing via spectrum consumption models, IEEE Journal on Selected Areas in Communications, vol. 33, no. 4, pp. 725-735, 2015.
[11]
X. Zheng, Z. Cai, and Y. Li, Data linkage in smart internet of things systems: A consideration from a privacy perspective, IEEE Communications Magazine, vol. 56, no. 9, pp. 55-61, 2018.
[12]
Z. Cai and Z. He, Trading private range counting over big IoT data, in Proc. of IEEE 39th International Conference on Distributed Computing Systems, Dallas, TX, USA, 2019, pp. 144-153.
[13]
Y. Jia, Y. Chen, X. Dong, P. Saxena, J. Mao, and Z. Liang, Man-in-the-browser-cache: Persisting https attacks via browser cache poisoning, Computers & Security, vol. 55, pp. 62-80, 2015.
[14]
Y. Huo, Y. Tian, L. Ma, X. Cheng, and T. Jing, Jamming strategies for physical layer security, IEEE Wireless Communications, vol. 25, no. 1, pp. 148-153, 2018.
[15]
T. Qiu, B. Chen, A. K. Sangaiah, J. Ma, and R. Huang, A survey of mobile social networks: Applications, social characteristics, and challenges, IEEE Systems Journal, vol. 12, no. 4, pp. 3932-3947, 2018.
[16]
C. Kong, G. Luo, L. Tian, and X. Cao, Disseminating authorized content via data analysis in opportunistic social networks, Big Data Mining and Analytics, vol. 2, no. 1, pp. 12-24, 2019.
[17]
J. Mao, W. Tian, Y. Yang, and J. Liu, An efficient social attribute inference scheme based on social links and attribute relevance, IEEE Access, vol. 7, pp. 153074-153085, 2019.
[18]
Z. Cai, Z. He, X. Guan, and Y. Li, Collective data sanitization for preventing sensitive information inference attacks in social networks, IEEE Transactions on Dependable and Secure Computing, vol. 15, no. 4, pp. 577-590, 2018.
[19]
S. J. Taylor and B. Letham, Forecasting at scale, The American Statistician, vol. 72, no. 1, pp. 37-45, 2018.
[20]
J. S. He, M. Han, S. Ji, T. Du, and Z. Li, Spreading social influence with both positive and negative opinions in online networks, Big Data Mining and Analytics, vol. 2, no. 2, pp. 100-117, 2019.
[21]
X. Meng, G. Xu, T. Guo, Y. Yang, W. Shen, and K. Zhao, A novel routing method for social delay-tolerant networks, Tsinghua Science and Technology, vol. 24, no. 1, pp. 44-51, 2019.
[22]
E. Tekin and A. Yener, The general gaussian multipleaccess and two-way wiretap channels: Achievable rates and cooperative jamming, IEEE Transactions on Information Theory, vol. 54, no. 6, pp. 2735-2751, 2008.
[23]
Y. Choi and J. H. Lee, A new cooperative jamming technique for a two-hop amplify-and-forward relay network with an eavesdropper, IEEE Transactions on Vehicular Technology, vol. 67, no. 12, pp. 12447-12451, 2018.
[24]
G. Chen, Y. Gong, P. Xiao, and J. A. Chambers, Physical layer network security in the full-duplex relay system, IEEE Transactions on Information Forensics and Security, vol. 10, no. 3, pp. 574-583, 2015.
[25]
M. Nafea and A. Yener, Secure degrees of freedom for the MIMO wiretap channel with a multi-antenna cooperative jammer, IEEE Transactions on Information Theory, vol. 63, no. 11, pp. 7420-7441, 2017.
[26]
Q. Gao, Y. Huo, T. Jing, L. Ma, Y. Wen, and X. Xing, An intermittent cooperative jamming strategy for securing energy-constrained networks, IEEE Transactions on Communications, vol. 67, no. 11, pp. 7715-7726, 2019.
[27]
Z. Chu, H. X. Nguyen, T. A. Le, M. Karamanoglu, E. Ever, and A. Yazici, Secure wireless powered and cooperative jamming D2D communications, IEEE Transactions on Green Communications and Networking, vol. 2, no. 1, pp. 1-13, 2018.
[28]
Y. Huo, X. Fan, L. Ma, X. Cheng, Z. Tian, and D. Chen, Secure communications in tiered 5G wireless networks with cooperative jamming, IEEE Transactions on Wireless Communications, vol. 18, no. 6, pp. 3265-3280, 2019.
[29]
T. Shi, Z. Cai, J. Li, and H. Gao, CROSS: A crowdsourcing based sub-servers selection framework in D2D enhanced MEC architecture, in Proc. of IEEE 40th International Conference on Distributed Computing Systems, Singapore, 2020, pp. 1-11.
[30]
R. Zhang, X. Cheng, and L. Yang, Cooperation via spectrum sharing for physical layer security in device-to-device communications underlaying cellular networks, IEEE Transactions on Wireless Communications, vol. 15, no. 8, pp. 5651-5663, 2016.
[31]
H. Wang, B. Zhao, and T. Zheng, Adaptive full-duplex jamming receiver for secure D2D links in random networks, IEEE Transactions on Communications, vol. 67, no. 2, pp. 1254-1267, 2019.
[32]
Q. Li, P. Ren, Q. Du, D. Xu, and Y. Xie, Safeguarding NOMA enhanced cooperative D2D communications via friendly jamming, in Proc. of IEEE 90th Vehicular Technology Conference, Honolulu, HI, USA, 2019, pp. 1-5.
[33]
S. Zhu, W. Li, H. Li, L. Tian, G. Luo, and Z. Cai, Coin hopping attack in blockchain-based IoT, IEEE Internet of Things Journal, vol. 6, no. 3, pp. 4614-4626, 2019.
[34]
L. Wang, H. Wu, L. Liu, M. Song, and Y. Cheng, Secrecy-oriented partner selection based on social trust in device-to-device communications, in Proc. of IEEE International Conference on Communications, London, UK, 2015, pp. 7275-7279.
[35]
Y. Wen, Y. Huo, L. Ma, T. Jing, and Q. Gao, A scheme for trustworthy friendly jammer selection in cooperative cognitive radio networks, IEEE Transactions on Vehicular Technology, vol. 68, no. 4, pp. 3500-3512, 2019.
[36]
H. Wang, Y. Xu, K. Huang, Z. Han, and T. A. Tsiftsis, Cooperative secure transmission by exploiting social ties in random networks, IEEE Transactions on Communications, vol. 66, no. 8, pp. 3610-3622, 2018.
[37]
Y. Zhao, Y. Li, Y. Cao, T. Jiang, and N. Ge, Social-aware resource allocation for device-to-device communications underlaying cellular networks, IEEE Transactions on Wireless Communications, vol. 14, no. 12, pp. 6621-6634, 2015.
[38]
Y. Zhao and W. Song, Energy-aware incentivized data dissemination via wireless D2D communications with weighted social communities, IEEE Transactions on Green Communications and Networking, vol. 2, no. 4, pp. 945-957, 2018.
[39]
F. Wang, Y. Li, Z. Wang, and Z. Yang, Social-community-aware resource allocation for D2D communications underlaying cellular networks, IEEE Transactions on Vehicular Technology, vol. 65, no. 5, pp. 3628-3640, 2016.
[40]
Z. He, Z. Cai, and J. Yu, Latent-data privacy preserving with customized data utility for social network data, IEEE Transactions on Vehicular Technology, vol. 67, no. 1, pp. 665-673, 2018.
[41]
X. Zheng, Z. Cai, J. Yu, C. Wang, and Y. Li, Follow but no track: Privacy preserved profile publishing in cyber-physical social systems, IEEE Internet of Things Journal, vol. 4, no. 6, pp. 1868-1878, 2017.
[42]
J. Wang, Z. Cai, and J. Yu, Achieving personalized k-anonymity-based content privacy for autonomous vehicles in CPS, IEEE Transactions on Industrial Informatics, vol. 16, no. 6, pp. 4242-4251, 2020.
[43]
C. Yi, S. Huang, and J. Cai, An incentive mechanism integrating joint power, channel and link management for social-aware D2D content sharing and proactive caching, IEEE Transactions on Mobile Computing, vol. 17, no. 4, pp. 789-802, 2018.
[44]
D. Wu, L. Zhou, Y. Cai, H. Chao, and Y. Qian, Physical-social-aware D2D content sharing networks: A provider-demander matching game, IEEE Transactions on Vehicular Technology, vol. 67, no. 8, pp. 7538-7549, 2018.
[45]
Y. Sun, T. Wang, L. Song, and Z. Han, Efficient resource allocation for mobile social networks in D2D communication underlaying cellular networks, in Proc. of IEEE International Conference on Communications, Sydney, Australia, 2014, pp. 2466-2471.
[46]
M. Alwakeel and V. A. Aalo, A teletraffic performance study of mobile LEO-satellite cellular networks with Gamma distributed call duration, IEEE Transactions on Vehicular Technology, vol. 55, no. 2, pp. 583-596, 2006.
[47]
H. Zhang, Z. Wang, and Q. Du, Social-aware D2D relay networks for stability enhancement: An optimal stopping approach, IEEE Transactions on Vehicular Technology, vol. 67, no. 9, pp. 8860-8874, 2018.
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Publication history

Received: 22 April 2020
Revised: 11 June 2020
Accepted: 12 June 2020
Published: 04 January 2021
Issue date: August 2021

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© The author(s) 2021

Acknowledgements

The authors are very grateful to all reviewers who have helped improve the quality of this paper. This work was supported by the National Natural Science Foundation of China (Nos. 61871023 and 61931001) and Beijing Natural Science Foundation (No. 4202054).

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