Forensic Analysis for Signature-Based Detection to Secure Data

Signature-based detection remains one of the cornerstone methods in cybersecurity for identifying known threats. However, its effectiveness is challenged by the rapid evolution of malware, including zero-day attacks and polymorphic viruses. This study explores the role of forensic analysis in enhancing the capabilities of signature-based detection. By examining real-world case studies and employing modern forensic techniques, it demonstrate how forensic analysis can detect patterns and anomalies that go beyond traditional signature matching. It analyzes the limitations of signature-based systems, the evasion techniques used by attackers, and the potential of integrating artificial intelligence to bolster forensic methods. The findings underscore the need for continuous advancements in detection techniques, focusing forensic analysis as a crucial tool in modern cybersecurity defense strategies.