Enhancing Cybersecurity with Artificial Intelligence: Predictive Techniques and Challenges in the Age of IoT

Abstract

As the Internet of Things expands, the surge in connected devices presents significant cybersecurity challenges. The rapid digitization of governments, corporations, and personal life has escalated cyberattacks into a menace for individuals, organizations, and even entire nations. Predictive techniques are becoming increasingly necessary to counteract these ever-evolving cyber threats before they can cause significant harm, as traditional cybersecurity measures are shown to be ineffective against them. This article examines the world of cyber threats, looking into ransomware, phishing, malware, and denial of service (DoS) assaults. It highlights how significant artificial intelligence (AI) is to supporting cybersecurity defense, such as intrusion detection systems, network security, and the use of intelligent agents. The essay also covers the significance of machine learning techniques and predictive modeling in anticipating and averting cyberattacks. Despite the potential benefits of AI-driven cybersecurity, the gravity of problems with data privacy, scalability, and human-machine cooperation cannot be overstated. In today's increasingly digital environment, enterprises may strengthen their defenses against cyber-attacks and protect valuable assets by implementing AI-powered cybersecurity solutions.

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