Volume no :
|
Issue no :
Article Type :
Author :
Mr.Sidharth Sharma
Published Date :
Publisher :
Page No: 18 - 24
Abstract : The rapid proliferation of Internet of Things (IoT) devices in smart cities has introduced numerous benefits, enhancing urban efficiency, sustainability, and automation. However, these interconnected systems also pose significant cybersecurity challenges, including data breaches, unauthorized access, and cyberattacks that can compromise critical infrastructure. This paper explores various cybersecurity strategies tailored for IoT environments in smart cities, focusing on encryption techniques, secure authentication mechanisms, network security protocols, and blockchain-based security models. Additionally, it discusses machine learning-based anomaly detection systems to identify potential cyber threats in real time. By analyzing existing security frameworks and emerging solutions, this study provides a comprehensive approach to safeguarding IoT devices in smart urban ecosystems. The findings emphasize the need for a multi-layered security model and proactive threat mitigation strategies to ensure the resilience and integrity of smart city infrastructures.
Keyword IoT security, smart cities, cybersecurity strategies, blockchain, machine learning, encryption, network security, authentication, cyber threats, intrusion detection.
Reference:
  1. Jasper Gnana Chandran, J., Karthick, R., Rajagopal, R., & Meenalochini, P. (2023). Dual-channel capsule generative adversarial network optimized with golden eagle optimization for pediatric bone age assessment from hand X-ray image. International Journal of Pattern Recognition and Artificial Intelligence37(02), 2354001.
  2. Karthick, R., Prabha, M., Sabapathy, S. R., Jiju, D., & Selvan, R. S. (2023, October). Inspired by social-spider behavior for microwave filter optimization, swarm optimization algorithm. In 2023 International Conference on New Frontiers in Communication, Automation, Management and Security (ICCAMS) (Vol. 1, pp. 1-4). IEEE.
  3. Vijayalakshmi, S., Sivaraman, P. R., Karthick, R., & Ali, A. N. (2020, September). Implementation of a new Bi-Directional Switch multilevel Inverter for the reduction of harmonics. In IOP Conference Series: Materials Science and Engineering (Vol. 937, No. 1, p. 012026). IOP Publishing.
  4. Kiruthiga, B., Karthick, R., Manju, I., & Kondreddi, K. (2024). Optimizing harmonic mitigation for smooth integration of renewable energy: A novel approach using atomic orbital search and feedback artificial tree control. Protection and Control of Modern Power Systems9(4), 160-176.
  5. Sulthan Alikhan, J., Miruna Joe Amali, S., & Karthick, R. (2024). Deep Siamese domain adaptation convolutional neural network-based quaternion fractional order Meixner moments fostered big data analytical method for enhancing cloud data security. Network: Computation in Neural Systems, 1-28.
  6. Sakthi, P., Bhavani, R., Arulselvam, D., Karthick, R., Selvakumar, S., & Sudhakar, M. (2022, September). Energy efficient cluster head selection and routing protocol for WSN. In AIP Conference Proceedings (Vol. 2518, No. 1). AIP Publishing.
  7. Aravindaguru, I., Arulselvam, D., Kanagavalli, N., Ramkumar, V., & Karthick, R. (2022, September). Space cloud in cubesat-Consigning expert system to space. In AIP Conference Proceedings (Vol. 2518, No. 1). AIP Publishing.
  8. Karthick, R., Prabaharan, A. M., & Selvaprasanth, P. (2019). A Dumb-Bell shaped damper with magnetic absorber using ferrofluids. International Journal of Recent Technology and Engineering (IJRTE)8.
  9. Selvan, R. S., Wahidabanu, R. S. D., Karthick, B., Sriram, M., & Karthick, R. (2020). Development of Secure Transport System Using VANET. TEM (H-Index)82.
  10. Karthick, R., & Sundararajan, M. (2018). Optimization of MIMO Channels Using an Adaptive LPC Method. International Journal of Pure and Applied Mathematics118(10), 131-135.
  11. Lopez, S., Sarada, V., Praveen, R. V. S., Pandey, A., Khuntia, M., & Haralayya, D. B. (2024). Artificial intelligence challenges and role for sustainable education in india: Problems and prospects. Sandeep Lopez, Vani Sarada, RVS Praveen, Anita Pandey, Monalisa Khuntia, Bhadrappa Haralayya (2024) Artificial Intelligence Challenges and Role for Sustainable Education in India: Problems and Prospects. Library Progress International44(3), 18261-18271.
  12. Kumar, N., Kurkute, S. L., Kalpana, V., Karuppannan, A., Praveen, R. V. S., & Mishra, S. (2024, August). Modelling and Evaluation of Li-ion Battery Performance Based on the Electric Vehicle Tiled Tests using Kalman Filter-GBDT Approach. In 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS) (pp. 1-6). IEEE.
  13. Sharma, S., Vij, S., Praveen, R. V. S., Srinivasan, S., Yadav, D. K., & VS, R. K. (2024, October). Stress Prediction in Higher Education Students Using Psychometric Assessments and AOA-CNN-XGBoost Models. In 2024 4th International Conference on Sustainable Expert Systems (ICSES) (pp. 1631-1636). IEEE.
  14. Yamuna, V., Praveen, R. V. S., Sathya, R., Dhivva, M., Lidiya, R., & Sowmiya, P. (2024, October). Integrating AI for Improved Brain Tumor Detection and Classification. In 2024 4th International Conference on Sustainable Expert Systems (ICSES) (pp. 1603-1609). IEEE.
  15. Anuprathibha, T., Praveen, R. V. S., Jayanth, H., Sukumar, P., Suganthi, G., & Ravichandran, T. (2024, October). Enhancing Fake Review Detection: A Hierarchical Graph Attention Network Approach Using Text and Ratings. In 2024 Global Conference on Communications and Information Technologies (GCCIT) (pp. 1-5). IEEE.