Implementation of Secure Cloud Based IoT Communication Using Lightweight Cryptography

Authors

  • Archana D. Wankhade Research Scholar, Computer Science and Engineering Department, Government College of Engineering, Amravati, India
  • Kishor P. Wagh Assistant Professor, Computer Science and Engineering Department, Government College of Engineering, Amravati, India

Keywords:

AES (Advanced Encryption Standard), Fernet, IoT(Internet of Things), Lightweight Cryptography, MQTT protocol

Abstract

Internet of things consists of things having unique identification of each device and things are connected to the Internet. Traditional devices which are not associate with internet are now having capabilities to get connected with Internet called smart devices. The backbone to IoT network is internet. IoT devices which are connected to Internet called as resource constrained devices because of having low computing power, limited battery power, limited memory etc. Hence when this constrained devices having sensor transmits data over networks are prone to different types of attacks. To avoid attack on IoT network and maintain confidentiality of data over network, it requires cryptographic solution but due to resource constrained nature of devices in IoT comparing with traditional encryption method Lightweight cryptography is more effective. Hence to make cloud based IoT secure transmission we present Fernet Lightweight symmetric encryption based on AES-128 bit in a CBC mode algorithm and HMAC authentication using SHA256 Hash Algorithm. Comparing with other Lightweight Cryptographic algorithms Fernet is found to be best for securing cloud based IoT communication as it is having Keysize of 256 bits and it can perform both encryption and authentication. In this research paper, we implemented Fernet Lightweight cryptographic algorithm for Encryption, Authentication and Key generation to secure transmission of sensor data generated by IoT devices.

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References

M. Rana ,Q.Mamun, R. Islam "Lightweight cryptography in IoT networks: A survey", Journal Future Generation Computer Systems,Vol.129,pp.77-89,2022,doi.org/10.1016/j.future.2021.11.011

H. Tawalbeh , S. Hashish ,“Security in Wireless Sensor Networks Using Lightweight Cryptography”, in Journal of Information Assurance and Security, ISSN 1554-1010 ,Volume 12, pp. 118-123, 2017.

C. Silva, V. A. Cunha, J. P. Barraca, R. L. Aguiar “Analysis of the Cryptographic Algorithms in IoT Communications”,in Springer Information Systems Frontiers, doi: 10.1007/s10796-023-10383-9,2023.

A. Fotovvat, G. M. E. Rahman, S. S. Vedaei and K. A. Wahid, "Comparative Performance Analysis of Lightweight Cryptography Algorithms for IoT Sensor Nodes," in IEEE Internet of Things Journal, vol. 8, no. 10, pp. 8279-8290, 15 May15, 2021, doi: 10.1109/JIOT.2020.3044526.

V. A. Thakor, M. A. Razzaque and M. R. A. Khandaker, "Lightweight Cryptography Algorithms for Resource-Constrained IoT Devices: A Review, Comparison and Research Opportunities," in IEEE Access, vol. 9, pp. 28177-28193, 2021, doi: 10.1109/ACCESS.2021.3052867.

F. Hussain, R. Hussain, S. A. Hassan and E. Hossain, "Machine Learning in IoT Security: Current Solutions and Future Challenges," in IEEE Communications Surveys & Tutorials, vol. 22, no. 3, pp. 1686-1721, thirdquarter 2020, doi: 10.1109/COMST.2020.2986444.

Mishra, S.; Albarakati, A.; Sharma, S.K.,” Cyber Threat Intelligence for IoT Using Machine Learning”, Journal Processes,Vol.10,pp.2673 doi. 10.3390/pr10122673.

Sharma, R., Arya, R. Secure transmission technique for data in IoT edge computing infrastructure. Complex Intell. Syst. 8, 3817–3832 (2022). https://doi.org/10.1007/s40747-021-00576-7

Hsing-Chung Chen and Ilsun You and Chien-Erh Weng and Chia-Hsin Cheng and Yung-Fa Huang,"A security gateway application for End-to-End M2M communications", Computer Standards & Interfaces,Vol.44,pp.85-93,2016, doi.org/10.1016/j.csi.2015.09.001.

A. Makkar, S. Garg, N. Kumar, M. S. Hossain, A. Ghoneim and M. Alrashoud, "An Efficient Spam Detection Technique for IoT Devices Using Machine Learning," in IEEE Transactions on Industrial Informatics, vol. 17, no. 2, pp. 903-912, Feb. 2021, doi: 10.1109/TII.2020.2968927.

C. Liu, Y. Zhang, J. Xu, J. Zhao and S. Xiang, "Ensuring the Security and Performance of IoT Communication by Improving Encryption and Decryption With the Lightweight Cipher uBlock," in IEEE Systems Journal, vol. 16, no. 4, pp. 5489-5500, Dec. 2022, doi: 10.1109/JSYST.2022.3140850.

A. Jamalipour and S. Murali, "A Taxonomy of Machine-Learning-Based Intrusion Detection Systems for the Internet of Things: A Survey," in IEEE Internet of Things Journal, vol. 9, no. 12, pp. 9444-9466, 15 June15, 2022, doi: 10.1109/JIOT.2021.3126811.

A. K. Pathak, S. Saguna, K. Mitra and C. Åhlund, "Anomaly Detection using Machine Learning to Discover Sensor Tampering in IoT Systems," ICC 2021 - IEEE International Conference on Communications, Montreal, QC, Canada, 2021, pp. 1-6, doi: 10.1109/ICC42927.2021.9500825.

G. Said, A. Ghani, A. Ullah, M. Azeem, M. Bilal and K. S. Kwak, "Light-Weight Secure Aggregated Data Sharing in IoT-Enabled Wireless Sensor Networks," in IEEE Access, vol. 10, pp. 33571-33585, 2022, doi: 10.1109/ACCESS.2022.3160231.

R. Sivakumar, J. Jayapriya and N. Krishnan, "Comparison Study on SPN Type Light Weight Cryptography Algorithms for IoT," 2022 International Conference on Inventive Computation Technologies (ICICT), Nepal, 2022, pp. 1051-1055, doi: 10.1109/ICICT54344.2022.9850849.

A. I. Regla and E. D. Festijo, "Performance Analysis of Light-weight Cryptographic Algorithms for Internet of Things (IoT) Applications: A Systematic Review," 2022 IEEE 7th International conference for Convergence in Technology (I2CT), Mumbai, India, 2022, pp. 1-5, doi: 10.1109/I2CT54291.2022.9824108.

Elena Petrova, Predictive Analytics for Customer Churn in Telecommunications , Machine Learning Applications Conference Proceedings, Vol 1 2021.

Dhabliya, D. (2021). Feature Selection Intrusion Detection System for The Attack Classification with Data Summarization. Machine Learning Applications in Engineering Education and Management, 1(1), 20–25. Retrieved from http://yashikajournals.com/index.php/mlaeem/article/view/8

Anand, R., Ahamad, S., Veeraiah, V., Janardan, S.K., Dhabliya, D., Sindhwani, N., Gupta, A. Optimizing 6G wireless network security for effective communication (2023) Innovative Smart Materials Used in Wireless Communication Technology, pp. 1-20.

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Published

25.12.2023

How to Cite

Wankhade , A. D. ., & Wagh , K. P. . (2023). Implementation of Secure Cloud Based IoT Communication Using Lightweight Cryptography. International Journal of Intelligent Systems and Applications in Engineering, 12(1), 310–316. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3904

Issue

Vol. 12 No. 1 (2024)

Section

Research Article

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