Abstract
Indian Journal of Modern Research and Reviews, 2025;3(4):66-72
Adaptive Cybersecurity With AI: Enhancing Threat Detection and Response in Intrusion Detection Systems
Author :
Abstract
Cyberattacks these days are both sneaky and more common, so the old security methods just don’t hit the mark anymore. In this work, we take a look at how AI—short for artificial intelligence—can jump in to spot and even block these ever-changing threats, sometimes before they fully take shape. Digital security has taken an unexpected turn—AI has sped up threat detection, reaction times, and risk handling in ways we hadn’t seen before. Old-school security systems just aren’t agile enough for today’s ever-changing challenges; they often stumble where AI, with its built-in safeguards, steps in. In our discussion we look closely at how AI works in cyber-security—explaining not only how it is wired to spot potential dangers but also noting, in most cases, its noticeable limits. We also bring in a few real-life case studies that show how these developments, with all their ups and downs, are reshaping our digital defenses. Cyberattacks these days are both sneaky and more common, so the old security methods just don’t hit the mark anymore. In this work, we take a look at how AI—short for artificial intelligence—can jump in to spot and even block these ever-changing threats, sometimes before they fully take shape. It wanders through a mix of tools like machine learning, deep learning, and natural language processing, all while tossing in a few real-world examples to show that these methods really do have some bite. And then there’s the whole tricky side of things, like trying to really get what these models are up to and keeping our data safe; in most cases, these challenges hint at just where AI-powered cybersecurity might be headed.
Keywords
Artificial Intelligence, Cybersecurity, Threat Detection, Machine Learning, Intrusion Detection Systems (IDS), Zero-Trust Architecture, AI in Security