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Mr.Sidharth Sharma
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Abstract : An increasing number of enterprises are using generative artificial intelligence (AI) to improve their cyber security and threat intelligence. Generative AI is a type of AI that generates new data independently of preexisting data or expert knowledge. One emerging cyberthreat to systems that has been increasing is adversarial attacks. By generating fictitious accounts and transactions, adversarial attacks can interfere with and take advantage of decentralized apps that operate on the Ethereum network. Because fraudulent materials (such as accounts and transactions) used as malicious payloads can be mistaken for legitimate data, detecting adversarial attacks can be difficult. This paper suggests a paradigm for cyber threat hunting in the Ethereum blockchain that makes use of Generative Adversarial Networks (GAN) and Deep Recurrent Neural Networks (RNN). By considering a variety of sources and data points, this technology enables decision support systems to automatically and rapidly identify threats posed by hackers or other harmful actors. The likelihood of a successful assault can be further decreased by using generative AI to find weaknesses in an organization's infrastructure. Because security operations centers (SOCs) need to quickly identify threats and take defensive action, this technology is particularly well-suited for them. Generative AI can give businesses an extra line of defense against increasingly complex threats by integrating intriguing and useful data items that would have otherwise gone unnoticed
Keyword Artificial intelligence, Threat intelligent, machine learning, threat hunting, deep learning, autonomous treat intelligent, Generative Adversarial Networks (GAN), Deep Recurrent Neural Networks (RNN).
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 Intelligence, 37(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 Systems, 9(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 Mathematics, 118(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 International, 44(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.

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