Distributed Secure Computing for Smart Mobile IoT Networks [Editorial]

Editorial Distributed Secure Computing for Smart Mobile IoT Networks Vishal Sharma , 1 Daniel G. Reina , 2 Zengpeng Li , 3 Kathiravan Srinivasan , 4 Navuday Sharma , 5 and Vinod Karar 6 1 Queen’s University Belfast, Belfast, NI BT7 1NN, UK 2 University of Seville, Seville 41004, Spain 3 School of Cyber Science and Technology, Shandong University, Qingdao 266237, China 4 Vellore Institute of Technology, Vellore 632014, India 5 Ericsson, Tallinn 11415, Estonia 6 Central Scientific Instruments Organisation, Chandigarh 160030, India Correspondence should be addressed to Vishal Sharma; vishal_sharma20[email protected] Received 22 February 2022; Accepted 22 February 2022; Published 15 April 2022 Copyright ©2022 Vishal Sharma et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. With billions of devices operations as a part of the Internet of Things (IoT), the operational complexity of the networks increases to many folds. In terms of threat detection, it requires moving from a centralised detection model to decentralised and distributed formations. Distributed computing facilitates better services; however, it has multiple ownership issues, requiring better system management [1]. With distributed systems, security needs to be revisited to make them aloof from cyber threats with new solutions, like sound and data steganography for authentication [2], preventing stealthy adversaries [3], access control [4], or network anomaly detection [5]. New and advanced solutions are required to solve the computationally intensive problems with better offloading in distributed setup targeting smart mobile IoT. Another prominent issue in distributed IoT networks is the data-islands dilemma [6], which requires intelligent and secure mechanisms to handle data integrity and privacy. Different solutions can be adapted like the use of distributed ledger technologies, such as blockchain [7], to take authorisation and access control of many portable devices without letting the system fall short of decentralised attacks; Iota Tangle [8] can be used mainly for securing IoT environment, or gossip protocol-based Hashgraph [9] can be used for increased fairness and better security constraints without using block-based architecture. Understanding smart devices privacy, trust, and security with better authentication protocols is another side to explore [10]. Several key issues need to be addressed by covering the gap in the literature, which must help answer concerns related to achieving password-based authentication, keeping data privacy, outsourcing security, and intelligent security solutions using machine learning. In this special issue (SI), a total of ten articles were selected following a rigorous review process where the articles were handled without any competing conflict of interest. The articles in this SI cover a wide range of security and privacy issues in distributed computing related to IoT, blockchain, resource manipulation, industrial control systems, credit cards, smart homes, and aerial networks. Some of the highlights include the following: In [11], the authors proposed an A 2 chain that uses an edge computing setup to decentralise the services. This article relies on the usage of sidechain technologies to securely share the identity verification of IoT devices. The authors used the proposed blockchain setup to authenticate the 5G-enabled IoTdevices. Overall, this approach reduces the authentication time and communication cost whereby consuming less storage space. In [12], the authors focused their work on user authorisation, where the primary task was to detect credit card frauds from imbalanced data logs. The authors relied on the machine learning models and suggested that RUSBoost be a more appropriate model when imbalanced records need to be evaluated for fraud detection. The authors used datasets to show the efficacy of their proposed solution. Their results showed a possibility of high precision between 94.20 and 99.30 for three different credit card datasets. Hindawi Mobile Information Systems Volume 2022, Article ID 9864846, 2 pages https://doi.org/10.1155/2022/9864846 In the direction of distributed security, rogue devices can be much harmful in any setup. These devices can be silent attackers that use the system’s weak defence to launch attacks. The authors considered this area of research in [13], where they proposed a blockchain-based access control for mitigating rogue devices in IoT. The authors aimed at removing the centralised mode of detection by replacing architecture with the blockchain, which offers secure device registration using smart contracts. The access control mechanism prohibits unregistered devices, and the approach is evaluated using a case study and in-depth performance evaluations. Furthermore, in [14], the authors focused on secure deployment in flying ad hoc networks using identitybased generalised signcryption. Their proposed work used Mobile Edge Computing (MEC), where UAVs act as a MEC node with the role of offloading in the network. The proposed security scheme is based on a hyperelliptic curve. The authors formally verified their proposed security scheme using the AVISPA tool and compared it with five relevant security schemes against security functionalities. Through its collection of diverse articles on distributed security, we believe that this special issue will benefit the research community. Conflicts of Interest The guest editors declare that they have no conflicts of interest regarding the publication of this special issue. Vishal Sharma Daniel G. Reina Zengpeng Li Kathiravan Srinivasan Navuday Sharma Vinod Karar Acknowledgments The guest editors appreciate the high-quality submissions from the authors and the timely support of reviewers. References [1] S. Jiang, T. Jiang, and L. Wang, “Secure and efficient cloud data deduplication with ownership management,” IEEE Transactions on Services Computing, vol. 13, no. 6, p. 1, 2017. [2] D. Datta, L. Garg, K. Srinivasan et al., “An efficient sound and data steganography based secure authentication system,” Computers, Materials & Continua, vol. 67, no. 1, pp. 723–751, 2021. [3] G. Park, C. Lee, H. Shim, Y. Eun, and K. H. Johansson, “Stealthy adversaries against uncertain cyber-physical systems: threat of robust zero-dynamics attack,” IEEE Transactions on Automatic Control, vol. 64, no. 12, pp. 4907–4919, 2019. [4] V. C. Hu, D. R. Kuhn, and D. F. Ferraiolo, “Access control for emerging distributed systems,” Computer, vol. 51, no. 10, pp. 100–103, 2018. [5] D. Patel, K. Srinivasan, C.-Y. Chang, T. Gupta, and A. Kataria, “Network anomaly detection inside consumer networks-A hybrid approach,” Electronics, vol. 9, no. 6, p. 923, 2020. [6] Z. Li, V. Sharma, and S. P. Mohant, “Preserving data privacy via federated learning: challenges and solutions,” IEEE Consumer Electronics Magazine, vol. 9, no. 3, pp. 8–16, 2020. [7] Y. Xu, G. Wang, J. Yang, J. Ren, Y. Zhang, and C. Zhang, “Towards secure network computing services for lightweight clients using blockchain,” Wireless Communications and Mobile Computing, vol. 201812 pages, 2018, https://doi.org/10. 1155/2018/2051693, Article ID 2051693. [8] W. F. Silvano and R. Marcelino, “Iota Tangle: a cryptocurrency to communicate Internet-of-Things data,” Future Generation Computer Systems, vol. 112, pp. 307–319, 2020. [9] A. A. Zahoor, M. M. Khan, and J. Arshad, “A comparative study of distributed ledger technologies,” in Blockchain for Cybersecurity and Privacy, pp. 29–55, CRC Press, Boca Raton, FL, USA, 2020. [10] V. Sharma, I. You, K. Andersson, F. Palmieri, M. H. Rehmani, and J. Lim, “Security, privacy and trust for smart mobileinternet of things (M-IoT): a survey,” IEEE Access, vol. 8, pp. 167123–167163, 2020. [11] X. Jia, N. Hu, S. Yin, Y. Zhao, C. Zhang, and X. Cheng, “A 2 chain: a blockchain-based decentralized authentication scheme for 5G-enabled IoT,” Mobile Information Systems, vol. 2020, Article ID 8889192, 19 pages, 2020. [12] V. Arora, R. S. Leekha, K. Lee, and A. Kataria, “Facilitating user authorization from imbalanced data logs of credit cards using artificial intelligence,” Mobile Information Systems, vol. 2020, Article ID 8885269, 9 pages, 2020. [13] U. Javaid, F. Jameel, U. Javaid, M. T. Raza Khan, and R. J¨ antti, “Rogue device mitigation in the internet of things: a blockchain-based access control approach,” Mobile Information Systems, vol. 2020, Article ID 8831976, 8 pages, 2020. [14] M. A. Khan, I. Ullah, S. Nisar et al., “Multiaccess edge computing empowered flying ad hoc networks with secure deployment using identity-based generalized signcryption,” Mobile Information Systems, vol. 202011 pages, 2020, https:// doi.org/10.1155/2020/8861947, Article ID 8861947. 2Mobile Information Systems