The Aho-Corasick Paradigm in Modern Antivirus Engines: A Cornerstone of Signature-Based Malware Detection

The Aho-Corasick (AC) algorithm remains one of the most influential developments in deterministic multi-pattern matching due to its ability to recognize multiple strings in linear time within a single data stream. Originally conceived for bibliographic text retrieval, the structure of the algorithm is based on a trie augmented with failure links and output functions, which has proven to be remarkably adaptable across computational domains. This review presents a comprehensive synthesis of the AC algorithm, with details on its theoretical foundations, formal automaton structure, and operational principles, as well as tracing its historical evolution from text-search systems to large-scale malware detection. This work further explores the integration of Aho-Corasick automata within modern antivirus architectures, describing mechanisms of signature compilation, real-time scanning pipelines, and large-scale deployment in contemporary cybersecurity systems. The deterministic structure of the Aho-Corasick automaton provides linear-time pattern recognition relative to input size, while practical performance characteristics reflect memory and architecture constraints in large signature sets. This linear-time property enables predictable and efficient malware detection, where each byte of input induces a constant computational cost. Such deterministic efficiency makes the algorithm ideally suited for real-time antivirus scanning and signature-based threat identification. Thus, nearly fifty years after its inception, AC continues to bridge formal automata theory and modern cybersecurity practice.