Uncovering Hidden Threats in IoT-Centered Cloud Technology
S. Hariharasitaraman, Nilamadhab Mishra, Ajinkya Bhanpurkar, Saroja Kumar Rout, Arul Kumar Natarajan · Advances in information security, privacy, and ethics book series · 2024
The current study comprehensively investigates Hardware Trojans testing in the cloud using both traditional methods and machine learning models. It highlights the challenge posed by the uniqueness of each Hardware Trojan and emphasizes the need for reliable solutions. The study recommends using machine learning models with feature extraction to detect patterns in different Hardware Trojans. However, the study also identifies limitations in the existing models, including reliance on the XGBoost algorithm. The study explores hybrid mechanisms and newer languages, such as LightBGM, for model development as potential areas for further research. The study also underscores the significance of addressing security concerns in Hidden threats in IoT-based Cloud technology.