Adversarial attacks pose a serious threat to the stability of AI systems. These attacks involve introducing input data in subtle ways to cause inaccurate outputs. Safeguarding against such attacks necessitates a multi-faceted approach that encompasses {robust{design principles, rigorous testing methodologies, and ongoing monitoring strategies. By e

The burgeoning sector of artificial intelligence (AI) presents both unprecedented opportunities and substantial risks. As sophisticated AI systems become increasingly integrated into our lives, it is imperative to establish robust safeguards to mitigate potential harms. One vital aspect of this endeavor involves mitigating the risk of AI maliciousu