3 papers
cs.CV2024
VidModEx: Interpretable and Efficient Black Box Model Extraction for High-Dimensional Spaces
Somnath Sendhil Kumar, Yuvaraj Govindarajulu, Pavan Kulkarni +1
In the domain of black-box model extraction, conventional methods reliant on soft labels or surrogate datasets struggle with scaling to high-dimensional input spaces and managing t…
cs.CR2024
Enhancing TinyML Security: Study of Adversarial Attack Transferability
Parin Shah, Yuvaraj Govindarajulu, Pavan Kulkarni +1
The recent strides in artificial intelligence (AI) and machine learning (ML) have propelled the rise of TinyML, a paradigm enabling AI computations at the edge without dependence o…
cs.LG2024
MISLEAD: Manipulating Importance of Selected features for Learning Epsilon in Evasion Attack Deception
Vidit Khazanchi, Pavan Kulkarni, Yuvaraj Govindarajulu +1
Emerging vulnerabilities in machine learning (ML) models due to adversarial attacks raise concerns about their reliability. Specifically, evasion attacks manipulate models by intro…