AI is a rapidly growing technology that has many benefits for society. However, as with all new technologies, misuse is a potential risk. One of the most troubling potential misuses of AI can be found in the form of adversarial AI attacks.
In an adversarial AI attack, AI is used to manipulate or deceive another AI system maliciously. Most AI programs learn, adapt and evolve through behavioral learning. This leaves them vulnerable to exploitation because it creates space for anyone to teach an AI algorithm malicious actions, ultimately leading to adversarial results. Cybercriminals and threat actors can exploit this vulnerability for malicious purposes and intent.
Although most adversarial attacks have so far been performed by researchers and within labs, they are a growing matter of concern. The occurrence of an adversarial attack on AI or a machine learning algorithm highlights a deep crack in the AI mechanism. The presence of such vulnerabilities within AI systems can stunt AI growth and development and become a significant security risk for people using AI-integrated systems. Therefore, to fully utilize the potential of AI systems and algorithms, it is crucial to understand and mitigate adversarial AI attacks.
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