Traditional anti-malware solutions primarily depend on signature-based detection, which has become less effective over the past two decades. This method struggles to keep up with the rapid emergence of new malware, with over 300,000 new samples identified daily. Additionally, polymorphic and metamorphic malware can easily evade detection by altering their signatures, while fileless malware remains undetectable by these approaches.

SentryBay reimagines cybersecurity by focusing on securing sensitive data rather than solely detecting malware. This data-centric approach employs techniques like data masking, encryption, and endpoint isolation, which protect sensitive information even in compromised environments. Unlike traditional methods, SentryBay's solutions do not require constant updates and operate efficiently in the background, minimizing resource consumption.

False positives are a significant drawback of behavioral and heuristic detection methods, as they can mistakenly flag legitimate applications as malware. This not only frustrates users but also burdens IT support teams with unnecessary investigations. Moreover, attackers can exploit these false alarms to disrupt operations, making it crucial for organizations to balance detection accuracy with user experience.