Cybersecurity Threat Landscape: Mitigating Risks through AI-Enabled Solutions

Prof. Kamal Pooj

Abstract


The contemporary cybersecurity landscape is continuously evolving, characterized by increasingly sophisticated threats that pose substantial risks to organizations across various sectors. This paper presents an in-depth exploration of the cybersecurity threat landscape and assesses the efficacy of leveraging Artificial Intelligence (AI) to mitigate these risks.

The abstract delves into the multifaceted nature of cyber threats, including malware, phishing attacks, ransomware, and other malicious activities that exploit vulnerabilities in information systems. It scrutinizes the escalating scale and complexity of these threats, necessitating innovative approaches for timely detection and response.

Furthermore, this paper evaluates the role of AI-enabled solutions in bolstering cybersecurity measures. It elucidates how AI algorithms, powered by machine learning and predictive analytics, offer unparalleled capabilities in threat detection, anomaly identification, and automated response mechanisms. The abstract highlights the advantages of AI in rapidly identifying patterns, analyzing vast datasets, and proactively fortifying defenses against emerging threats.

Additionally, the paper discusses the limitations and challenges associated with AI-based cybersecurity solutions, including potential biases in algorithms, adversarial attacks, and the requirement for continuous learning to adapt to evolving threats.


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