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A robust and trusted framework for IoT networks

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Abstract

In the optimistic era of the internet, connected devices have the capability to communicate and share information with each other. The implementation of the Internet of Things (IoT) is not possible until the security-related issues of managing a huge amount of data with reduced latency have been resolved. In contrast to traditional cryptographic techniques, trust establishment schemes among sensor nodes are found to be secure, reliable, and easily manageable. Therefore, in this paper, we propose a novel hybrid trust estimation approach that calculates the trust value of devices both at the device layer (Short-Term Trust) and at the edge layer (Long-Term Trust) depending upon their resource capabilities. Short-Term Trust (STT) uses the Markov model and considers only the current trust state for the evaluation of trust value whereas Long-Term Trust (LTT) uses the voluminous historical data for trust value prediction. Further, both LTT and STT are then alternatively referred to after every periodic interval leading to the evolution of the hybrid trust model. The healthcare simulation of the proposed work when compared with the available state of arts viz. ConTrust, BTEM, and Entropy gained a 17%, 10%, and 11% increase in the level of trustworthiness respectively. In addition, on average; the simulation results provide a 7% higher detection rate and 36% lower false-positive rate when compared to BTEM and Entropy trust models presented in the literature. Besides, the proposed scheme scores only 0.69% of computational overhead; which is observed to be suitable for resource constraint IoT devices.

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References

  • Aanchal KS, Kaiwartya O, Abdullah AH (2017) Green computing for wireless sensor networks: Optimization and Huffman coding approach. Peer-to-Peer Netw Appl 10:592–609. https://doi.org/10.1007/s12083-016-0511-y

    Article  Google Scholar 

  • Al-Fuqaha A, Guizani M, Mohammadi M et al (2015) Internet of things: a survey on enabling technologies, protocols, and applications. IEEE Commun Surv Tutorials 17:2347–2376. https://doi.org/10.1109/COMST.2015.2444095

    Article  Google Scholar 

  • Alexopoulos N, Habib SM, Mühlhäuser M (2018) Towards secure distributed trust management on a global scale. In: Proceedings of the 2018 Workshop on IoT Security and Privacy. ACM, New York, NY, USA, pp 49–54

  • Almolhis N, Alashjaee AM, Duraibi S, et al (2020) The Security Issues in IoT - Cloud: A Review. In: 2020 16th IEEE International Colloquium on Signal Processing & Its Applications (CSPA). IEEE, pp 191–196

  • Alshehri MD, Hussain FK (2019) A fuzzy security protocol for trust management in the internet of things (Fuzzy-IoT). Computing 101:791–818. https://doi.org/10.1007/s00607-018-0685-7

    Article  MathSciNet  Google Scholar 

  • Alshehri MD, Hussain FK, Hussain OK (2018) Clustering-driven intelligent trust management methodology for the internet of things (CITM-IoT). Mob Networks Appl 23:419–431. https://doi.org/10.1007/s11036-018-1017-z

    Article  Google Scholar 

  • Anwar RW, Zainal A, Outay F et al (2019) BTEM: belief based trust evaluation mechanism for Wireless Sensor Networks. Fut Gen Comput Syst 96:605–616. https://doi.org/10.1016/j.future.2019.02.004

    Article  Google Scholar 

  • Awan KA, Ud Din I, Almogren A et al (2019) RobustTrust – a pro-privacy robust distributed trust management mechanism for internet of things. IEEE Access 7:62095–62106. https://doi.org/10.1109/ACCESS.2019.2916340

    Article  Google Scholar 

  • Azad MA, Bag S, Hao F, Shalaginov A (2020) Decentralized self-enforcing trust management system for social internet of things. IEEE Internet Things J 7:2690–2703. https://doi.org/10.1109/JIOT.2019.2962282

    Article  Google Scholar 

  • Bonetto R, Bui N, Lakkundi V, et al (2012) Secure communication for smart IoT objects: Protocol stacks, use cases and practical examples. 2012 IEEE Int Symp a World Wireless, Mob Multimed Networks, WoWMoM 2012 - Digit Proc. https://doi.org/10.1109/WoWMoM.2012.6263790

  • Caminha J, Perkusich A, Perkusich M (2018) A smart trust management method to detect on-off attacks in the internet of things. Secur Commun Netw 2018:1–10. https://doi.org/10.1155/2018/6063456

    Article  Google Scholar 

  • De Donno M, Donaire Felipe JM, Dragoni N (2019) ANTIBIOTIC 2.0: a fog-based anti-malware for internet of things. In: 2019 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW). IEEE, pp 11–20

  • Dofe J, Frey J, Yu Q (2016) Hardware security assurance in emerging IoT applications. In: 2016 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, pp 2050–2053

  • Esposito C, Tamburis O, Su X, Choi C (2020) Robust decentralised trust management for the internet of things by using game theory. Inf Process Manag 57:102308. https://doi.org/10.1016/j.ipm.2020.102308

    Article  Google Scholar 

  • Faizullah S, Khan MA, Alzahrani A, Khan I (2020) Permissioned Blockchain-Based Security for SDN in IoT Cloud Networks. In: 2019 International Conference on Advances in the Emerging Computing Technologies (AECT). IEEE, pp 1–6

  • Fang W, Zhang C, Shi Z et al (2016) BTRES: beta-based trust and reputation evaluation system for wireless sensor networks. J Netw Comput Appl 59:88–94. https://doi.org/10.1016/j.jnca.2015.06.013

    Article  Google Scholar 

  • Feng R, Xu X, Zhou X, Wan J (2011) A trust evaluation algorithm for wireless sensor networks based on node behaviors and D-S evidence theory. Sensors 11:1345–1360. https://doi.org/10.3390/s110201345

    Article  Google Scholar 

  • Fosler-lussier E (1998) Markov models and hidden markov models: a brief tutorial

  • Gupta N, Naik V, Sengupta S (2017) A firewall for Internet of Things. 2017 9th Int Conf Commun Syst Networks. COMSNETS 2017:411–412. https://doi.org/10.1109/COMSNETS.2017.7945418

    Article  Google Scholar 

  • Gupta SP (2014) Statistical inference- tests of hypotheses, 44th edn. Sultan Chand & Sons

  • Hameed S, Khan FI, Hameed B (2019) Understanding security requirements and challenges in internet of things (IoT): a review. J Comput Networks Commun 2019:1–14. https://doi.org/10.1155/2019/9629381

    Article  Google Scholar 

  • Hema Kumar M, Mohanraj V, Suresh Y et al (2021) Trust aware localized routing and class based dynamic block chain encryption scheme for improved security in WSN. J Ambient Intell Humaniz Comput 12:5287–5295. https://doi.org/10.1007/s12652-020-02007-w

    Article  Google Scholar 

  • Huang Q, Wang L, Yang Y (2018) DECENT: Secure and fine-grained data access control with policy updating for constrained IoT devices. World Wide Web 21:151–167. https://doi.org/10.1007/s11280-017-0462-0

    Article  Google Scholar 

  • Jangid A, Chauhan P (2019) A Survey and Challenges in IoT Networks. In: 2019 International Conference on Intelligent Sustainable Systems (ICISS). IEEE, pp 516–521

  • Kasirajan P, Larsen C, Jagannathan S (2012) A new data aggregation scheme via adaptive compression for wireless sensor networks. ACM Trans Sens Netw 9:1–26. https://doi.org/10.1145/2379799.2379804

    Article  Google Scholar 

  • Li D, Deng L, Liu W, Su Q (2020) Improving communication precision of IoT through behavior-based learning in smart city environment. Fut Gener Comput Syst 108:512–520. https://doi.org/10.1016/j.future.2020.02.053

    Article  Google Scholar 

  • Liu Z, Choo K-KR, Grossschadl J (2018) Securing edge devices in the post-quantum internet of things using lattice-based cryptography. IEEE Commun Magn 56:158–162. https://doi.org/10.1109/MCOM.2018.1700330

    Article  Google Scholar 

  • Mahmud M, Kaiser MS, Rahman MM et al (2018) A brain-inspired trust management model to assure security in a cloud based IoT framework for neuroscience applications. Cognit Comput 10:864–873. https://doi.org/10.1007/s12559-018-9543-3

    Article  Google Scholar 

  • Malik S, Dedeoglu V, Kanhere SS, Jurdak R (2019) Trustchain: trust management in blockchain and iot supported supply chains. In: 2019 IEEE International Conference on Blockchain (Blockchain). IEEE, pp 184–193

  • Mendoza CVL, Kleinschmidt JH (2018) A distributed trust management mechanism for the internet of things using a multi-service approach. Wirel Pers Commun 103:2501–2513. https://doi.org/10.1007/s11277-018-5942-8

    Article  Google Scholar 

  • Miettinen M, Marchal S, Hafeez I, et al (2017) IoT SENTINEL: automated device-type identification for security enforcement in IoT. In: 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS). IEEE, pp 2177–2184

  • Mirzamohammadi S, Chen JA, Sani AA, et al (2017) Ditio : trustworthy auditing of sensor activities in mobile & IoT devices. In: Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems. ACM, New York, NY, USA, pp 1–14

  • Puar VH, Bhatt CM, Hoang DM, Le DN (2018) Communication in internet of things. Springer, Singapore

  • Rahman FH, Au T-W, Newaz SHS et al (2020) Find my trustworthy fogs: a fuzzy-based trust evaluation framework. Fut Gener Comput Syst 109:562–572. https://doi.org/10.1016/j.future.2018.05.061

    Article  Google Scholar 

  • Rani R, Katti CP (2018) End-to-End Security in Delay Tolerant Mobile Social Network. In: Communications in Computer and Information Science. Springer, Singapore, pp 45–54

  • Sathyaraj P, Rukmani Devi D (2021) Designing the routing protocol with secured IoT devices and QoS over Manet using trust-based performance evaluation method. J Ambient Intell Humaniz Comput 12:6987–6995. https://doi.org/10.1007/s12652-020-02358-4

    Article  Google Scholar 

  • Sicari S, Rizzardi A, Miorandi D, Coen-Porisini A (2018) A risk assessment methodology for the Internet of Things. Comput Commun 129:67–79. https://doi.org/10.1016/j.comcom.2018.07.024

    Article  Google Scholar 

  • Suryani V, Sulistyo S, Widyawan W (2017) ConTrust: a trust model to enhance the privacy in internet of things. Int J Intell Eng Syst 10:30–37. https://doi.org/10.22266/ijies2017.0630.04

  • Talbi S, Bouabdallah A (2020) Interest-based trust management scheme for social internet of things. J Ambient Intell Hum Comput 11:1129–1140. https://doi.org/10.1007/s12652-019-01256-8

    Article  Google Scholar 

  • Tao H, Bhuiyan MZA, Rahman MA et al (2020) TrustData: trustworthy and secured data collection for event detection in industrial cyber-physical system. IEEE Trans Ind Inf 16:3311–3321. https://doi.org/10.1109/TII.2019.2950192

    Article  Google Scholar 

  • Vitevitch MS, Chan KY, Roodenrys S (2012) Complex network structure influences processing in long-term and short-term memory. J Mem Lang 67:30–44. https://doi.org/10.1016/j.jml.2012.02.008

    Article  Google Scholar 

  • Wang T, Qiu L, Sangaiah AK et al (2019a) Edge-computing-based trustworthy data collection model in the internet of things. IEEE Internet Things J 7:4218–4227. https://doi.org/10.1109/JIOT.2020.2966870

    Article  Google Scholar 

  • Wang T, Zhang G, Liu A et al (2019b) A secure IoT service architecture with an efficient balance dynamics based on cloud and edge computing. IEEE Internet Things J 6:4831–4843. https://doi.org/10.1109/JIOT.2018.2870288

    Article  Google Scholar 

  • Xiong J, Chen L, Bhuiyan MZA et al (2020) A secure data deletion scheme for IoT devices through key derivation encryption and data analysis. Fut Gen Comput Syst 111:741–753. https://doi.org/10.1016/j.future.2019.10.017

    Article  Google Scholar 

  • Xu L, O’Hare G, Collier R (2017) A smart and balanced energy-efficient multihop clustering algorithm (Smart-BEEM) for MIMO IoT systems in future networks †. Sensors 17:1574. https://doi.org/10.3390/s17071574

    Article  Google Scholar 

  • Yin X, Li S (2019) Trust evaluation model with entropy-based weight assignment for malicious node’s detection in wireless sensor networks. EURASIP J Wirel Commun Netw 2019:198. https://doi.org/10.1186/s13638-019-1524-z

    Article  Google Scholar 

  • Zhang C, Green R (2015) Communication security in internet of thing: Preventive measure and avoid DDoS attack over IoT network. Simul Ser 47:8–15

    Google Scholar 

  • Zhao W, Shahriar H, Clincy V, Bhuiyan ZA (2020) Security and Privacy Analysis of Mhealth Application: A Case Study. In: 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). IEEE, pp 1882–1887

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  1. Computer Science and Engineering, School of Information and Communication Technology (ICT), Gautam Buddha University, Greater Noida, Uttar Pradesh, 201308, India

    Gamini Joshi & Vidushi Sharma

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  1. Gamini Joshi
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  2. Vidushi Sharma
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Correspondence to Vidushi Sharma.

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Joshi, G., Sharma, V. A robust and trusted framework for IoT networks. J Ambient Intell Human Comput 14, 9001–9019 (2023). https://doi.org/10.1007/s12652-022-04403-w

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