Attack-detection and multi-clock source cooperation-based accurate time synchronization for PLC-AIoT in smart parks

Abstract

Power Line Communications-Artificial Intelligence of Things (PLC-AIoT) combines the low cost and high coverage of PLC with the learning ability of Artificial Intelligence (AI) to provide data collection and transmission capabilities for PLC-AIoT devices in smart parks. With the development of smart parks, their emerging services require secure and accurate time synchronization of PLC-AIoT devices. However, the impact of attackers on the accuracy of time synchronization cannot be ignored. To solve the aforementioned problems, we propose a tampering attack-aware Deep Q-Network (DQN)-based time synchronization algorithm. First, we construct an abnormal clock source detection model. Then, the abnormal clock source is detected and excluded by comparing the time synchronization information between the device and the gateway. Finally, the proposed algorithm realizes the joint guarantee of high accuracy and low delay for PLC-AIoT in smart parks by intelligently selecting the multi-clock source cooperation strategy and timing weights. Simulation results show that the proposed algorithm has better time synchronization delay and accuracy performance.

Keywords

Smart park / Power line communications / Artificial intelligence of things / Tampering attack awareness / Abnormal clock source detection / Multi-clock source cooperation

References

[1] A.M. Rocchi, E.S. Fernández, J.R. Vega, A double-auction mechanism for distribu-tion of electrical supply capacities among enterprises of an industrial park, IEEE Lat. Am. Trans. 19 (02) (2021) 269-279.

[2] M. Choobineh, S. Mohagheghi, Robust optimal energy pricing and dispatch for a multi-microgrid industrial park operating based on just-in-time strategy, IEEE Trans. Ind. Appl. 55 (4) (2019) 3321-3330.

[3] C.S. Qin Wei, P. Mugen, Recent advances in industrial Internet: insights and chal-lenges, Digit. Commun. Netw. 6(1) (2020) 1-13.

[4] Z. Zhou, X. Chen, H. Liao, Z. Gan, F. Xiao, Q. Tu, W. Sun, Y. Liu, S. Mumtaz, M. Guizani, Collaborative learning-based network resource scheduling and route management for multi-mode green IoT, Trans. Green Commun. Netw. 7(2) (2023) 928-939.

[5] Y. Liu, K. Wang, Y. Lin, W. Xu, 𝖫𝗂𝗀𝗁𝗍𝖢𝗁𝖺𝗂𝗇: a lightweight blockchain system for industrial Internet of things, IEEE Trans. Ind. Inform. 15 (6) (2019) 3571-3581.

[6] H. Liao, Z. Zhou, N. Liu, Y. Zhang, G. Xu, Z. Wang, S. Mumtaz, Cloud-edge-device collaborative reliable and communication-efficient digital twin for low-carbon elec-trical equipment management, IEEE Trans. Ind. Inform. 19 (2) (2023) 1715-1724.

[7] C. Wang, X. Yu, L. Xu, Z. Wang, W. Wang, Multimodal semantic communication ac-celerated bidirectional caching for 6G MEC, Future Gener. Comput. Syst. 140 (2023) 225-237.

[8] R. Luo, N. Hua, X. Zheng, B. Zhou, High-reliability sub-nanosecond network time synchronization method enabled by double-frequency distributed time synchroniza-tion, J. Opt. Commun. Netw. 11 (1) (2019) A40-A51.

[9] J. Peng, Y. Sun, H. Chen, T. Xu, Z. Li, Q. Zhang, J. Zhang, High-precision and low-complexity symbol synchronization algorithm based on dual-threshold amplitude decision for real-time IMDD OFDM-PON, IEEE Photonics J. 11 (1) (2019) 1-14.

[10] F. Khan, M.A. Jan, A. u. Rehman, S. Mastorakis, M. Alazab, P. Watters, A secured and intelligent communication scheme for IIoT-enabled pervasive edge computing, IEEE Trans. Ind. Inform. 17 (7) (2021) 5128-5137.

[11] H. Liao, Z. Wang, Z. Zhou, Y. Wang, H. Zhang, S. Mumtaz, M. Guizani, Blockchain and semi-distributed learning-based secure and low-latency computation offloading in space-air-ground-integrated power IoT, IEEE J. Sel. Top. Signal Process. 16 (3)(2022) 381-394.

[12] X. Wu, X. Liu, Y. A, Key technologies of artificial intelligence in electric power customer service, Glob. Energy Interconnect. 4(6) (2021) 631-640.

[13] C. Wang, X. Yu, L. Xu, W. Wang, Energy-efficient task scheduling based on traffic mapping in heterogeneous mobile-edge computing: a green IoT perspective, IEEE Trans. Green Commun. Netw. 7(2) (2023) 972-982.

[14] P. Jia, X. Wang, K. Zheng, Distributed clock synchronization based on intelligent clustering in local area industrial IoT systems, IEEE Trans. Ind. Inform. 16 (6) (2020) 3697-3707.

[15] Y. Mi, C. Liu, J. Yang, H. Zhang, Q. Wu, Low-carbon generation expansion plan-ning considering uncertainty of renewable energy at multi-time scales, Glob. Energy Interconnect. 4(3) (2021) 261-272.

[16] K.M. Rabie, B. Adebisi, H. Gacanin, G. Nauryzbayev, A. Ikpehai, Performance eval-uation of multi-hop relaying over non-Gaussian PLC channels, J. Commun. Netw. 19 (5) (2017) 531-538.

[17] G. Si, Z. Dou, Y. Lin, L. Qi, M. Wang, Relay selection and secure connectivity analysis in energy harvesting multi-hop D2D networks, IEEE Commun. Lett. 26 (6) (2022) 1245-1248.

[18] M.A. Jan, F. Khan, S. Mastorakis, M. Adil, A. Akbar, N. Stergiou, LightIoT: lightweight and secure communication for energy-efficient IoT in health informat-ics, IEEE Trans. Green Commun. Netw. 5(3) (2021) 1202-1211.

[19] J. Li, C. Sun, Q. Su, Analysis of cascading failures of power cyber-physical systems considering false data injection attacks, Glob. Energy Interconnect. 4(2) (2021) 204-213.

[20] V. Srivatsa, A.P. Chavan, D. Mourya, Design of low power & high performance multi source H-tree clock distribution network, in: 2020 IEEE VLSI Device Circuit and System (VLSI DCS), 2020, pp. 468-473.

[21] S. Wang, Y. Hua, Y. Xiang, C. Huang, Y. Gao, X. Zhao, Optimal weighting method for reducing digital satellite TV differential timing error, Chin. J. Electron. 29 (2)(2020) 128-132.

[22] A. Leva, F. Terraneo, L. Rinaldi, A.V. Papadopoulos, M. Maggio, High-precision low-power wireless nodes’ synchronization via decentralized control, IEEE Trans. Control Syst. Technol. 24 (4) (2016) 1279-1293.

[23] Z. Zhou, C. Liu, Z. Wang, L. Lv, L. Zhang, X. Li, X. Wang, W. Sun, G. He, Y. Liu, DRL-assisted topology identification and time synchronization for PIoT-empowered distributed renewable resource dispatch, IEEE Internet Things Mag. 5(2) (2022) 13-19.

[24] M.S. Allahham, A.A. Abdellatif, N. Mhaisen, A. Mohamed, A. Erbad, M. Guizani, Multi-agent reinforcement learning for network selection and resource allocation in heterogeneous multi-rat networks, IEEE Trans. Cognit. Commun. Netw. 8(2) (2022) 1287-1300.

[25] J. Wang, W. Tu, L.C. Hui, S. Yiu, E.K. Wang, Detecting time synchronization at-tacks in cyber-physical systems with machine learning techniques, in: 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS), 2017, pp. 2246-2251.

[26] B. Moussa, M. Debbabi, C. Assi, A detection and mitigation model for PTP delay attack in an IEC 61850 substation, IEEE Trans. Smart Grid 9(5) (2018) 3954-3965.

[27] Q. Lu, X. Feng, C. Zhou, A detection and weakening method for GNSS time-synchronization attacks, IEEE Sens. J. 21 (17) (2021) 19069-19077.

[28] T. Qiu, X. Liu, M. Han, H. Ning, D.O. Wu, A secure time synchronization protocol against fake timestamps for large-scale Internet of things, IEEE Int. Things J. 4(6)(2017) 1879-1889.

[29] N. Papandreou, T. Antonakopoulos, Resource allocation management for indoor power-line communications systems, IEEE Trans. Power Deliv. 22 (2) (2007) 893-903.

[30] N. Rozic, P. Banelli, D. Begusic, J. Radic, GMM-based symbol error rate analysis for multicarrier systems with impulsive noise suppression, IEEE Trans. Veh. Technol. 71 (12) (2022) 13060-13076.

[31] X. Huan, K.S. Kim, S. Lee, E.G. Lim, A. Marshall, Improving multi-hop time synchro-nization performance in wireless sensor networks based on packet-relaying gateways with per-hop delay compensation, IEEE Trans. Commun. 69 (9) (2021) 6093-6105.

[32] B. Moussa, M. Kassouf, R. Hadjidj, M. Debbabi, C. Assi, An extension to the precision time protocol (PTP) to enable the detection of cyber attacks, IEEE Trans. Ind. Inform. 16 (1) (2020) 18-27.

[33] B. Moon, Diffusion-based time synchronization in large-scale distributed sensor net-works, Int. J. Multimed. Ubiquitous Eng. 9(6) (2014) 283-300.

[34] J. He, P. Cheng, L. Shi, J. Chen, SATS: secure average-consensus-based time syn-chronization in wireless sensor networks, IEEE Trans. Signal Process. 61 (24) (2013) 6387-6400.

[35] X. Hu, T. Park, K.G. Shin, Attack-tolerant time-synchronization in wireless sensor networks, in: IEEE INFOCOM 2008 -the 27th Conference on Computer Communi-cations, 2008, pp. 41-45.

[36] C. Xu, J. Feng, Z. Zhou, J. Wu, C. Perera, Cross-layer optimization for cooperative content distribution in multihop device-to-device networks, IEEE Int. Things J. 6(1)(2019) 278-287.

[37] H. Li, D. Li, X. Zhang, G. Shou, Y. Hu, Y. Liu, A security management architecture for time synchronization towards high precision networks, IEEE Access 9 (2021) 117542-117553.

[38] M. Leng, Y.C. Wu, Low-complexity maximum-likelihood estimator for clock syn-chronization of wireless sensor nodes under exponential delays, IEEE Trans. Signal Process. 59 (10) (2011) 4860-4870.

[39] B. Nikfar, A.J. Han Vinck, Relay selection in cooperative power line communication: a multi-armed bandit approach, J. Commun. Netw. 19 (1) (2017) 1-9.