While external cyber threats capture headlines, the rise of insider threats from within an organization is a growing concern. In 2023, the average cost of a data breach caused by an insider reached $4.90 million, 9.6% higher than the global average data breach cost of $4.45 million. To effectively combat this danger, integrating advanced analytics into data security software has become a critical and proactive defense strategy.
Understanding insider threats
Insider threats come from users who abuse authorized access to a company’s assets deliberately or accidentally. There are typically two types of insider threats: intentional (malicious) and unintentional. An unintentional insider threat could be caused by negligence or simply an accident. Intentional threats are actions that harm an organization for personal benefit or grievance.
Regardless of the intent, both types of insider threats can have severe consequences for businesses. Detecting and mitigating these risks quickly is crucial — breaches initiated by malicious insiders took nearly 308 days to resolve.
Need for fast detection
Traditional methods of detecting threats have trouble keeping up with evolving attacker tactics. Advanced threat detection analytics can help to provide a dynamic, proactive way to swiftly identify insider threats by scanning and analyzing data. Rapid detection is crucial due to its role in reducing financial losses, preserving reputation, minimizing data exposure, meeting compliance demands and ensuring operational continuity.
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