A team of researchers from the University of Missouri has introduced a groundbreaking artificial intelligence (AI)-based system designed to strengthen the integrity and security of global semiconductor supply chains. This innovation aims to detect and prevent cyber threats hidden within computer chips, safeguarding industries dependent on advanced electronic components.
Led by doctoral researcher Ripan Kumar Kundu, the team developed an AI-driven method capable of identifying hardware trojans—malicious alterations embedded within chip designs that can compromise data, weaken security systems, and disrupt operations. Unlike traditional detection methods that are often costly and time-consuming, this new system leverages large language models (LLMs) to scan chip blueprints with 97% accuracy, while also providing explanations for potential threats to increase transparency and developer trust.
This technology holds major implications for the semiconductor supply chain, where chips are designed, tested, and assembled across multiple countries. Given the complexity and global nature of this trade network, vulnerabilities can arise at various production stages. By identifying hidden trojans early in the design process, companies can prevent large-scale recalls, financial losses, and disruptions to international supply operations.
Doctoral co-author Khurram Khalil emphasized that the system can be integrated into existing chip design workflows and adapted for multiple sectors — including consumer electronics, healthcare, finance, and defense. The tool can operate locally or through cloud-based systems, enhancing flexibility and accessibility across global production networks.
As industries increasingly depend on semiconductors for digital innovation, the University of Missouri’s AI-powered detection method provides a proactive solution to one of the most pressing challenges in global trade — securing supply chains against invisible cyber threats.
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