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A Formally Validated Authentication Algorithm for Secure Message Forwarding in Smart Home Networks

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Abstract

The many devices connected in smart homes increase the attack surfaces from which adversaries can invade the network. In addition, majority of these smart devices have numerous vulnerabilities that can be exploited to wreck havoc in smart homes. As such, a myriad of security schemes have been presented based on technologies such as bilinear pairing operations, public key infrastructure, blockchains and elliptic curve cryptosystems. However, some of these protocols are not robust against conventional smart home attacks. In addition, some of the deployed techniques inadvertently result in excessive processing at the smart devices. It is, therefore, imperative that provably secure protocols be developed to offer efficiency and sufficient protection to the exchanged packets. In this paper, an elliptic curve symmetric key-based algorithm for secure message forwarding is presented. Formal security verification is executed using the Burrows–Abadi–Needham (BAN) logic which demonstrates strong mutual authentication and session negotiation among the communicating entities. In addition, the informal security analysis carried out shows the robustness of this scheme under the Canetti–Krawczyk threat model. Moreover, it is relatively efficient in terms of storage, communication, energy and computation requirements.

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References

  1. Alam MR, St-Hilaire M, Kunz T. Peer-to-peer energy trading among smart homes. Appl Energy. 2019;238:1434–43.

    Article  Google Scholar 

  2. Shuai M, Yu N, Wang H, Xiong L. Anonymous authentication scheme for smart home environment with provable security. Comput Secur. 2019;86:132–46.

    Article  Google Scholar 

  3. Park JH, Salim MM, Jo JH, Sicato JCS, Rathore S, Park JH. CIoT-Net: a scalable cognitive IoT based smart city network architecture. Human Compu Inf Sci. 2019;9(1):1–29.

    Article  Google Scholar 

  4. Ringel M, Laidi R, Djenouri D. Multiple benefits through smart home energy management solutions—a simulation-based case study of a single-family-house in algeria and Germany. Energies. 2019;12:1537.

    Article  Google Scholar 

  5. Gonçalves I, Gomes A, Antunes CH. Optimizing the management of smart home energy resources under different power cost scenarios. Appl Energy. 2019;242:351–63.

    Article  Google Scholar 

  6. Bakar U, Ghayvat H, Hasanm S, Mukhopadhyay S. Activity and anomaly detection in smart home: a survey, next generation sensors and systems. Berlin: Springer; 2016. p. 191–220.

    Google Scholar 

  7. Nyangaresi VO. ECC based authentication scheme for smart homes. In 2021 International Symposium (ELMAR), 5–10, IEEE, 2021.

  8. Dang TLN, Nguyen MS. An approach to data privacy in smart home using blockchain technology. In: 2018 International Conference on Advanced Computing and Applications (ACOMP), 58–64, IEEE, 2018.

  9. Gu K, Yang L, Yin B. Location data record privacy protection based on differential privacy mechanism. Inf Technol Control. 2018;47(4):639–54.

    Google Scholar 

  10. Ramapatruni S, Narayanan SN, Mittal S, Joshi A, Joshi K. Anomaly detection models for smart home security. In 2019 IEEE 5th International Conference on Big Data Security on Cloud (BigDataSecurity), IEEE International Conference on High Performance and Smart Computing,(HPSC) and IEEE Internationl Conference on Intelligent Data and Security (IDS), 19–24, IEEE, 2019.

  11. Singh S, Sharma PK, Park JH. SH-SecNet: an enhanced secure network architecture for the diagnosis of security threats in a smart home. Sustainability. 2017;9:1–19.

    Google Scholar 

  12. Nyangaresi VO, Ogundoyin SO. Certificate based authentication scheme for smart homes. In: 2021 3rd Global Power, Energy and Communication Conference (GPECOM), 202–207, IEEE, 2021.

  13. Moniruzzaman M, Khezr S, Yassine A, Benlamri R. Blockchain for smart homes: Review of current trends and research challenges. Comput Electr Eng. 2020;83: 106585.

    Article  Google Scholar 

  14. Jia Y, Xiao Y, Yu J, Cheng X, Liang Z, Wan Z. A novel graph-based mechanism for identifying traffic vulnerabilities in smart home IoT. In: IEEE INFOCOM 2018-IEEE Conference on Computer Communications, 1493–1501, IEEE, 2018.

  15. Fahad LG, Tahir SF. Activity recognition and anomaly detection in smart homes. Neurocomputing. 2021;423:362–72.

    Article  Google Scholar 

  16. Forkan ARM, Khalil I, Tari Z, Foufou S, Bouras A. A context-aware approach for long-term behavioural change detection and abnormality prediction in ambient assisted living. Pattern Recogn. 2015;48(3):628–41.

    Article  Google Scholar 

  17. Saqaeeyan S, Amirkhani H. Anomaly detection in smart homes using bayesian networks. KSII Trans Internet Inf Syst (TIIS). 2020;14(4):1796–816.

    Google Scholar 

  18. Zhu C, Sheng W, Liu M. Wearable sensor-based behavioral anomaly detection in smart assisted living systems. IEEE Trans Autom Sci Eng. 2015;12(4):1225–34.

    Article  Google Scholar 

  19. Sivanathan A, Sherratt D, Gharakheili HH, Sivaraman V, Vishwanath A. Low-cost flow-based security solutions for smart home IOT devices. In: 2016 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), 1–6, IEEE, 2016.

  20. Anton K, Aleksandr N, Catherine B, Denis N, Aleksei S, Aleksandr E, Kseniia N. Anomaly detection in wireless sensor network of the smart home system. In: 2017 20th Conference of Open Innovations Association (FRUCT), 118–124, IEEE, 2017.

  21. Spanos G, Giannoutakis KM, Votis K, Tzovaras D. Combining statistical and machine learning techniques in IoT anomaly detection for smart homes. In: 2019 IEEE 24th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), 1–6, IEEE, 2019.

  22. Zeng Y, Meikang Q, Zhong M, Meiqin L. Senior2local: a machine learning based intrusion detection method for vanets. In: International conference on smart computing and communication. Berlin: Springer; 2018. p. 417–26.

    Chapter  Google Scholar 

  23. Challa S, Das AK, Odelu V, Kumar N, Kumari S, Khan MK, Vasilakos AV. An efficient ECC-based provably secure three-factor user authentication and key agreement protocol for wireless healthcare sensor networks. Comput Electr Eng. 2018;69:534–54.

    Article  Google Scholar 

  24. Sureshkumar V, Amin R, Vijaykumar V, Sekar SR. Robust secure communication protocol for smart healthcare system with fpga implementation. Future Gener Comput Syst. 2019;100:938–51.

    Article  Google Scholar 

  25. Kaur D, Kumar D. Cryptanalysis and improvement of a two-factor user authentication scheme for smart home. J Inf Secur Appl. 2021;58: 102787.

    Google Scholar 

  26. AbuNaser M, Alkhatib AA. Advanced survey of blockchain for the internet of things smart home. In: 2019 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT), 58–62, IEEE, 2019.

  27. Lee Y, Rathore S, Park JH, Park JH. A blockchain-based smart home gateway architecture for preventing data forgery. HCIS. 2020;10(1):1–14.

    Google Scholar 

  28. Almadhoun R, Kadadha M, Alhemeiri M, Alshehhi M, Salah K. A user authentication scheme of IoT devices using blockchain-enabled fog nodes. In: 2018 IEEE/ACS 15th international conference on computer systems and applications (AICCSA), 1–8, IEEE, 2018.

  29. Bahga A, Madisetti VK. Blockchain platform for industrial internet of things. J Softw Eng Appl. 2016;9(10):533–46.

    Article  Google Scholar 

  30. Dorri A, Kanhere SS, Jurdak R, Gauravaram P. Blockchain for ToT security and privacy: The case study of a smart home. In: 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), 618–23, IEEE, 2017.

  31. Dwivedi AD, Srivastava G, Dhar S, Singh R. A decentralized privacy-preserving healthcare blockchain for IoT. Sensors. 2019;19(2):326.

    Article  Google Scholar 

  32. Nyangaresi, VO, Abduljabbar, ZA, Al Sibahee, MA, Abduljaleel IQ, Abood EW. Towards Security and Privacy Preservation in 5G Networks. In: 2021 29th Telecommunications Forum (TELFOR),1–4, IEEE, 2021.

  33. Ba Z, Piao S, Fu X, Koutsonikolas D, Mohaisen A, Ren K. ABC: enabling smartphone authentication with built-in camera. In: Network and Distributed System Security Symposium, 18–21, 2018.

  34. Nimmy K, Sankaran S, Achuthan K, Calyam P. Lightweight and privacy-preserving remote user authentication for smart homes. IEEE Access. 2021;10:176–90.

    Article  Google Scholar 

  35. Yu S, Das AK, Park Y. Comments on “ALAM: anonymous lightweight authentication mechanism for SDN enabled smart homes. IEEE Access. 2021;9:49154–9.

    Article  Google Scholar 

  36. Santoso FK, Vun NCH. Securing IoT for smart home system. In 2015 international symposium on consumer electronics (ISCE), 1–2, IEEE, 2015.

  37. Parne BL, Gupta S, Chaudhari NS. Pse-aka: performance and security enhanced authentication key agreement protocol for iot enabled lte/lte-a networks. Peer-to-Peer Netw Appl. 2019;12(5):1156–77.

    Article  Google Scholar 

  38. Shen J, Yang H, Wang A, Zhou T, Wang C. Lightweight authentication and matrix-based key agreement scheme for healthcare in fog computing. Peer-to-Peer Netw Appl. 2019;12(4):924–33.

    Article  Google Scholar 

  39. Wazid M, Das AK, Odelu V, Kumar N, Susilo W. Secure remote user authenticated key establishment protocol for smart home environment. IEEE Trans Dependable Secure Comput. 2020;17(2):391–406.

    Article  Google Scholar 

  40. Sankaran S. Lightweight security framework for IoTs using identity based cryptography. In: 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), IEEE, 2016, pp. 880–6.

  41. Nyangaresi VO. Provably secure protocol for 5G HetNets. In: 2021 IEEE International Conference on Microwaves, Antennas, Communications and Electronic Systems (COMCAS), IEEE, 2021, pp. 17–22.

  42. Kumar P, Gurtov A, Iinatti J, Ylianttila M, Sain M. Lightweight and secure session-key establishment scheme in smart home environments. IEEE Sens J. 2016;16(1):254–64.

    Article  Google Scholar 

  43. Fakroon M, Alshahrani M, Gebali F, Traore I. Secure remote anonymous user authentication scheme for smart home environment. Internet of Things. 2020;9: 100158.

    Article  Google Scholar 

  44. Nikravan M, Reza A. A multi-factor user authentication and key agreement protocol based on bilinear pairing for the internet of things. Wirel Pers Commun. 2020;111(1):463–94.

    Article  Google Scholar 

  45. Nyangaresi VO, Rodrigues AJ, Abeka SO. Machine learning protocol for secure 5G handovers. Int J Wirel Inf Netw. 2022. https://doi.org/10.1007/s10776-021-00547-2.

    Article  Google Scholar 

  46. Tewari A, Gupta B. A lightweight mutual authentication protocol based on elliptic curve cryptography for IoT devices. Int J Adv Intell Paradigms. 2017;9(2–3):111–21.

    Article  Google Scholar 

  47. Mo J, Chen H. A lightweight secure user authentication and key agreement protocol for wireless sensor networks. Secur Commun Netw. 2019. https://doi.org/10.1155/2019/2136506.

    Article  Google Scholar 

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  1. Faculty of Biological and Physical Sciences, Tom Mboya University College, Homabay, 40300, Kenya

    Vincent Omollo Nyangaresi

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Nyangaresi, V.O. A Formally Validated Authentication Algorithm for Secure Message Forwarding in Smart Home Networks. SN COMPUT. SCI. 3, 364 (2022). https://doi.org/10.1007/s42979-022-01269-9

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