Revolutionizing Security: The Role of AI and Machine Learning in Threat Anomaly Detection
In an era dominated by digital advancements, the ever-growing complexity of cyber threats demands innovative solutions. Artificial Intelligence (AI) and Machine Learning (ML) have emerged as powerful tools in the realm of threat detection, reshaping the landscape of cybersecurity. In this article, we delve into the transformative role of AI and ML in fortifying digital defenses and explore the cutting-edge technologies that drive these advancements.
Understanding the Threat Landscape
Before delving into the specifics of AI and ML in threat detection, it’s crucial to comprehend the evolving threat landscape. Cyber adversaries employ sophisticated techniques, exploiting vulnerabilities across networks, applications, and various system components. Traditional security measures often struggle to keep pace with these dynamic threats, necessitating a more intelligent and adaptive approach. Therefore it becomes important to understand the overall Threat landscape.
In this article, I am intending to share my fair research on the role of AI and ML algorithms in the space of Anomaly detection. Like always, I am going to take a generic approach to explain concepts that are understandable by all readers who are interested to learn…
