Data loss prevention is a leading area of concern for many organizations, particularly in the health and life science industry. These organizations generate and collect the most sensitive types of information, including valuable proprietary research and deeply personal customer health information. The first and primary objective is to keep malicious third parties from gaining access to this information. However, they are not the only threat, insiders who have legitimate access to this information occasionally mishandle or misuse information they have been entrusted with. This type of incidental and malicious insider threat can be much more difficult to identify. DLP programs within Information Security programs have been tried for years with results charitably described as ‘varied.’
What makes DLP hard? One word, “intent”. A DLP analyst needs to validate what information is being acted on, by who (the easier part), and why they are doing what they are doing. The last part speaks to intent, which most often can’t be represented in a log you can easily search. Figuring out intent is not an impractical problem until you realize the overwhelming scale of DLP alerts that could/should be adjudicated.
At Salem, we think deeply about how to solve for the scale of DLP and other alerts by leveraging AI technology that works fast to contextualize alerts in the way an analyst works, reduce the false positive, and escalate the few likely threats to someone who can act.
Salem automates cyber and DLP alert triage to cut through the noise and identify threats like data exfiltration within minutes, saving precious time and resources.
By leveraging Salem, you can:
- Achieve real-time detection: Validate threats as they happen, minimizing potential damage.
- Empower your security team: Free up your team to focus on high-level investigations and incident response.
- Gain broader visibility: Have Salem investigate your noisiest alerts, including DLP
