AI-Powered GUI Attack and Its Defensive Methods

TL;DR

This paper explores AI-powered attacks on GUI systems using object recognition and proposes defensive methods like adversarial example generation, demonstrating that such attacks are feasible and defenses are temporarily effective.

Contribution

It introduces a novel AI-based GUI attack method and evaluates its effectiveness, along with proposing initial defensive strategies against such threats.

Findings

AI-based GUI attacks are feasible with current techniques.

Defensive methods like adversarial examples can mitigate attacks temporarily.

The attack and defense approaches are simple and effective.

Abstract

Since the first Graphical User Interface (GUI) prototype was invented in the 1970s, GUI systems have been deployed into various personal computer systems and server platforms. Recently, with the development of artificial intelligence (AI) technology, malicious malware powered by AI is emerging as a potential threat to GUI systems. This type of AI-based cybersecurity attack, targeting at GUI systems, is explored in this paper. It is twofold: (1) A malware is designed to attack the existing GUI system by using AI-based object recognition techniques. (2) Its defensive methods are discovered by generating adversarial examples and other methods to alleviate the threats from the intelligent GUI attack. The results have shown that a generic GUI attack can be implemented and performed in a simple way based on current AI techniques and its countermeasures are temporary but effective to mitigate the threats of GUI attack so far.