A Blockchain Based Secure IoT System Using Device Identity Management

Sharing data securely and efficiently has been identified as an issue in IoT-based smart systems such as smart cities, smart agriculture, smart health, etc. A large number of IoT devices are used in these smart systems and they produce a large amount of data. IoT devices generally have limited storage and processing capabilities, and configuring any security techniques on these devices is a challenge. In this paper, we propose a novel device identity management approach for blockchain-based IoT systems that provides data security in two ways. Firstly, a lightweight time-based identification protocol that uses hub identification for validating data. Secondly, data storage is augmented with an effective blockchain application for providing easy access and immutability for data sharing among multiple parties. Our initial prototype implementation shows that: our identity management approach can be implemented in large scale settings, our system can be effectively implemented in blockchain platforms, and our performance evaluation result shows that the prototype fulfills system requirements adequately.

[1]  M. Conti,et al.  Eunomia: Anonymous and Secure Vehicular Digital Forensics Based on Blockchain , 2023, IEEE Transactions on Dependable and Secure Computing.

[2]  A. Juels,et al.  Strategic Latency Reduction in Blockchain Peer-to-Peer Networks , 2022, Proceedings of the ACM on Measurement and Analysis of Computing Systems.

[3]  S. Kanhere,et al.  Device Identification in Blockchain-Based Internet of Things , 2022, IEEE Internet of Things Journal.

[4]  Qiuyan Yao,et al.  Blockchain-Enabled Tripartite Anonymous Identification Trusted Service Provisioning in Industrial IoT , 2022, IEEE Internet of Things Journal.

[5]  Julian Jang,et al.  Entitlement-Based Access Control for Smart Cities Using Blockchain , 2021, Sensors.

[6]  Hamed Haddadi,et al.  Revisiting IoT Device Identification , 2021, TMA.

[7]  Christos Emmanouilidis,et al.  Internet of Things for System Integrity: A Comprehensive Survey on Security, Attacks and Countermeasures for Industrial Applications , 2021, Sensors.

[8]  Yuchen Fu,et al.  Blockchain-based IoT device identification and management in 5G smart grid , 2021, EURASIP J. Wirel. Commun. Netw..

[9]  Daniyal M. Alghazzawi,et al.  BCoT Sentry: A Blockchain-Based Identity Authentication Framework for IoT Devices , 2021, Inf..

[10]  Fan Zhang,et al.  CanDID: Can-Do Decentralized Identity with Legacy Compatibility, Sybil-Resistance, and Accountability , 2021, 2021 IEEE Symposium on Security and Privacy (SP).

[11]  Avleen Malhi,et al.  Automated IoT Device Identification Based on Full Packet Information Using Real-Time Network Traffic , 2021, Sensors.

[12]  Li Yang,et al.  IoT ETEI: End-to-End IoT Device Identification Method , 2021, 2021 IEEE Conference on Dependable and Secure Computing (DSC).

[13]  Jianqiang Li,et al.  Machine Learning for the Detection and Identification of Internet of Things Devices: A Survey , 2021, IEEE Internet of Things Journal.

[14]  Bhabendu Kumar Mohanta,et al.  DecAuth: Decentralized Authentication Scheme for IoT Device Using Ethereum Blockchain , 2019, TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON).

[15]  Quan Z. Sheng,et al.  IoT Device Identification via Network-Flow Based Fingerprinting and Learning , 2019, 2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE).

[16]  Ahmad-Reza Sadeghi,et al.  AuDI: Toward Autonomous IoT Device-Type Identification Using Periodic Communication , 2019, IEEE Journal on Selected Areas in Communications.

[17]  Lina Yao,et al.  Automatic Device Classification from Network Traffic Streams of Internet of Things , 2018, 2018 IEEE 43rd Conference on Local Computer Networks (LCN).

[18]  Indrajit Ray,et al.  Behavioral Fingerprinting of IoT Devices , 2018, ASHES@CCS.

[19]  Chao Wang,et al.  Research on Physical Layer Security of Cognitive Radio Network Based on RF-DNA , 2017, 2017 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C).

[20]  Fuchun Guo,et al.  Fuzzy Extractors for Biometric Identification , 2017, 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS).

[21]  Rashid Rashidzadeh,et al.  Wireless device identification using oscillator control voltage as RF fingerprint , 2017, 2017 IEEE 30th Canadian Conference on Electrical and Computer Engineering (CCECE).

[22]  Ahmad-Reza Sadeghi,et al.  IoT SENTINEL: Automated Device-Type Identification for Security Enforcement in IoT , 2016, 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS).

[23]  Trevor J. Bihl,et al.  Feature Selection for RF Fingerprinting With Multiple Discriminant Analysis and Using ZigBee Device Emissions , 2016, IEEE Transactions on Information Forensics and Security.

[24]  Rafail Ostrovsky,et al.  Fuzzy Extractors: How to Generate Strong Keys from Biometrics and Other Noisy Data , 2004, SIAM J. Comput..

[25]  Asif Nawaz,et al.  IoT with BlockChain: A Futuristic Approach in Agriculture and Food Supply Chain , 2021, Wirel. Commun. Mob. Comput..

[26]  Subhasis Thakur,et al.  Identification and Authentication in Healthcare Internet-of-Things Using Integrated Fog Computing Based Blockchain Model , 2021, Internet Things.