Adaptive noise injection techniques for optimizing deep learning models under adversarial attacks
*Araddhana Arvind DeshmukhCorresponding authoraadeshmukhskn@gmail.comDepartment of Computer Science & Information Technology (Cyber Security)Symbiosis Skill and Professional UniversityPune, Maharashtra, 412101, IndiaView full profile → , Priyanka S. Dhumalpriyanka.dhumal@dypvp.edu.inDepartment of Electronics and TelecommunicationPimpriDr. D.Y. Patil Institute of TechnologyPune, Maharashtra, 411018, IndiaView full profile → , Shankar M. Patilsmpatil2k@gmail.comDepartment of Computer EngineeringSmt Indira Gandhi College of EngineeringNavi Mumbai, Maharashtra, 411005, IndiaView full profile → , Samir N. Ajanisamir.ajani@gmail.comSchool of Computer Science and EngineeringRamdeobaba University (RBU)Nagpur, Maharashtra, 440013, IndiaView full profile → , Gaurav Gondhalekargg.ycce@gmail.comDepartment of Electrical EngineeringYeshwatrao Chavan College of EngineeringNagpur, Maharashtra, 441110, IndiaView full profile → , Ajay Kumar Mehtaajaymehta7684@gmail.comDepartment of Computer Science and EngineeringJECRC UniversityJaipur, Rajasthan, 303905, IndiaView full profile → , Saurabh Bhattacharyas.bhattacharya@galgotiasuniversity.edu.inSchool of Computer Science & EngineeringGalgotias UniversityGreater Noida, Uttar Pradesh, 203201, IndiaView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 14 Oct 2024
- Published Online:
- 31 May 2025
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIOS-1899
- Pages:
- 1153–1163
Abstract
Keywords
Subject Classifications
References
[1] C.-H. H. Yang, Z. Zhang, J. Li, P.-Y. Chen, and C.-J. Hsieh, “Enhanced Adversarial Strategically-Timed Attacks Against Deep Reinforcement Learning,” ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, Spain, pp. 3407-3411 (2020).
[2] F. Spasiano, G. Gennaro and S. Scardapane, “Evaluating Adversarial Attacks and Defences in Infrared Deep Learning Monitoring Systems,” 2022 International Joint Conference on Neural Networks (IJCNN), Padua, Italy, pp. 1-6 (2022).
[3] C. Junliang, “CNN or RNN: Review and Experimental Comparison on Image Classification,” 2022 IEEE 8th International Conference on Computer and Communications (ICCC), Chengdu, China, pp. 1939-1944 (2022).
[4] D. Edwards and D. B. Rawat, “Study of adversarial machine learning with infrared examples for surveillance applications”, Electronics, vol. 9, no. 8 (2020).
[5] Peiyu Ma, Recognition of Handwritten Digit using Convolutional Neural Network IEEE (2020).
[6] X. Zhu, X. Li, J. Li, Z. Wang and X. Hu, Fooling thermal infrared pedestrian detectors in real world using small bulbs (2021).
[7] S. S. Patil and E. Rosemaro, “Cybersecurity Threat Detection and Prevention using Machine Learning Approaches”, IJRAET, vol. 12, no. 1, pp. 9–15, Jun. (2023).
[8] A. Sikri, A. Mathur and G. Verma, “Secrecy Performance Enhancement of Artificial Noise Injection Scheme-based FSO Systems,” 2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall), Norman, OK, USA, pp. 01-05 (2021).
[9] B. He, X. Zhou, and T. D. Abhayapala, “Artificial noise injection for securing single-antenna systems”, IEEE Trans. Veh. Technol., vol. 66, no. 10, pp. 9577-9581, Oct. (2017).
[10] Y. O. Anisimov and D. A. Katcai, “Deep Reinforcement Learning Approach for Autonomous Driving”, Journal of Physics. Conference Series, vol. 1864, no. 1, pp. 12013 (2021).
[11] A. Sikri, A. Mathur, M. Bhatnagar, G. Kaddoum, P. Saxena and J. Nebhen, “Artificial Noise Injection–Based Secrecy Improvement for FSO Systems,” in IEEE Photonics Journal, vol. 13, no. 2, pp. 1-12 (April 2021) Art no. 7900412, doi: 10.1109/JPHOT.2021.3060974.
[12] A. Selvakkumar, S. Pal and Z. Jadidi, “Addressing adversarial machine learning attacks in smart healthcare perspectives” in Sensing Technology., Springer, pp. 269-282 (2022).
[13] A. Kurakin, I. J. Goodfellow and S. Bengio, “Adversarial examples in the physical world” in Artificial intelligence safety and security., Chapman and Hall/CRC, pp. 99-112 (2018).
[14] S. Saika, S. Shewali, M. J. Borah, and D. J. Mahanta, “Arithmetic mean of interval valued intuitionistic fuzzy soft sets and its application in diagnosing infectious diseases,” J. Interdiscip. Math., vol. 27, no. 5, pp. 1079–1090 (2024), doi: 10.47974/JIM-1934.
