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PacketWorker – A savior for Network Security & Risk Practitioners in these times of working remotely

Ritu Chaudhary
March 31, 2020

COVID-19 has wrecked small and large scale industries, and disrupted economies globally. Security and risk practitioners always require an upper hand while dealing with adverse network security situations. But what happens when they are forced to work remotely? How will they continue to cater to the network monitoring requirements during this pandemic?

It is obvious that remote work bring newer cyber security challenges for security teams that have majorly focused on risk management within the peripheries of an organization environment. Hackers are now targeting people’s increased dependency on digital platforms. In the quest for more information on the coronavirus, people are more likely to click on malicious links. In a “perimeter-less” work environment, traditional rule-based security methods are not even remotely designed to protect data or users. This is where we can rely on the Vehere PacketWorker, which is versatile enough to adapt to the new perimeter-less environment, provide richer and in-depth network analysis, enabling organizations to function with zero compromises. 

Here’s how:

  • Cloud and Shadow-IT monitoring- Deployed in an hour, the PacketWorker facilitates comprehensive monitoring of networks for cloud and shadow-IT, to pin-point even the slightest anomaly, which may indicate a massive cyber threat.
  • Security analytics for remote workers- A network situational awareness platform, PacketWorker integrates deep packet and payload inspection, machine learning, comprehensive rules-engine to detect network anomalies. This enables security teams to establish standards for remote workers for a deeper understanding of how remote users interact with data and identify anomalous behaviour outside the work margins.
  • Machine Learning in the remote working situation- By leveraging Machine Learning, PacketWorker records the attributes of a session, for example, the applications used by the remote user, or even an unknown coronavirus malware. It then builds on these attributes and correlates to future activities, whereby even the slightest anomaly is alerted. This narrows down the number of false positives, while concurrently delivering transparent insight into the chronology of events. The PacketWorker alerts in the early stages of a malicious incident, significantly reducing the damage of a breach.

Given the outbreak of the COVID-19 and its related malware, there is a higher probability that employees, out of curiosity and confusion about the virus, may accidentally click on malicious links and lose confidential passwords. PacketWorker’s behaviour analysis and machine learning capability, thus, enables the security practitioners and risk management teams to proactively monitor and supervise target-based risks.

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