The Impacts of AI on Cybersecurity

 The Impacts of AI on Cybersecurity

Abraam Ibrahim, 2024 Commonwealth Cyber Initiative Intern

Introduction

In 2024, an estimated 77% of businesses were either using or were exploring the use of Artificial Intelligence (AI) tools in their business processes (National University, 2024). The light-speed pace of AI development and adoption has massive implications across all industries and sectors. Finance experts using AI to assist in trading, doctors using AI for ultrasound measurement, and factory owners employing AI to create smart factories are just a few examples. The ever-advancing field of cybersecurity, already well-known for its rapid acceleration, is among the most impacted by this AI revolution. 

This article explores the anticipated impacts that the rise of AI could have on cybersecurity, and how AI's ability to enhance authentication, automate tasks, and improve threat detection and response is revolutionizing the field while simultaneously introducing new challenges and threats.

The Power of AI in Cybersecurity

AI can streamline and automate a wide variety of security tasks. Authentication, incident response, threat detection, intelligence, and other tasks can be significantly improved or even replaced with AI assistance. By leveraging natural language processing (NLP) and deep learning (DL) capabilities, security experts can make cyber operations more effective and efficient. Similarly, AI integration into security solutions will enhance the overall security posture of organizations by enabling faster and more informed response and defense measures, ultimately reducing the time to detect and mitigate threats.⁤ 

AI in Authentication

Authentication, the process of validating users, has always been an indispensable guard against security breaches. As the thinking goes, if malicious parties can be prevented from ever gaining access to a target (database, account, server, etc), then all damage can be mitigated preemptively. Accordingly, cyber professionals have created increasingly secure login methods to enhance security and user convenience (biometric, MFA), which have now become the industry norm. 

With the advent of AI-enabled machine learning algorithms, security professionals are now employing user behavior analytics (UBA) to detect unusual activity during a sign-in attempt. An algorithm can take various inputs, such as the typing speed, cursor movement, touch input, and biometric data (voice, fingerprints) to determine the validity of an individual request and authenticate legitimate while flagging and reporting suspicious sign-in attempts.

Cybersecurity Automation

AI’s ability to tirelessly sift through massive amounts of data has profound implications for the industry. AI will enable professionals to focus their time on the most important areas while providing cost-saving benefits due to increased efficiency.