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Introduction
It is clear by now that the advent of OpenAI’s Chat GPT has elevated the conversation surrounding the integration of AI. Already, diverse tests of the system, from the student needing help with secondary school homework to large scale industrial problems, to developers using AI assistants as a pair programmer, have shown that AI assistance shows great promise as well as cause for concern. Its popularity owes part of its success to the democratisation of the system so that we all become beta testers. From the point of view of cybersecurity, this has raised serious concerns regarding plagiarism, impersonation, database poisoning and, more worryingly, an increase in the capacity of malicious users to accelerate their attacks dramatically. Conversely, while current security software leverages rule-based detection in order to detect sophisticated attacks, AI can analyse vast amounts of data from multiple sources, including network traffic, logs, and user behaviour, to identify potential threats faster. The primary benefit of AI in cybersecurity is its ability to improve threat detection and potentially the response. While AI-powered systems can also continuously monitor the network and detect anomalies that may indicate a potential attack, particularly from AI-driven systems, this paper introduces some of the important themes developing today on cybersecurity within the context of AI.
AI-Powered Attacks
Darktrace found that the average linguistic complexity of phishing emails has risen by 17 percent since ChatGPT's November 2022 launch; indeed, five simple prompts have been demonstrated by an AI model....
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