Kemp Flowmon ADS vs. Kaspersky Anti Targeted Attack Platform

Flowmon ADS is a customizable anomaly detection solution with excellent scalability capabilities and quick integration into the organization environment. Flowmon ADS provides a large set of essential detections out of the box, which allows to quickly acquire an awareness of potential problems in the monitored network. Custom configuration, filters, and false-positive flagging make the system highly customizable for diverse environments. Powerful dashboards make summaries and reporting a breeze. We use the Flowmon Anomaly Detection System daily for event detection and incident handling. It provides high-quality detection methods with low false-positive rates.

I would say it is less appropriate for an organization which is looking to implement a tool within a short period of time. However, we found support on the web forum as well as from support team and were given solutions always. It was somewhat a relief for the users. We were not in a position to provide further IT security resources. And Anti Targeted Attack Platform did not require such. The tool was able to identify and eliminate a critical threat right after the implementation.

• Kemp Flowmon ADS provides a large set of essential detections out of the box, which allows us to quickly acquire an awareness of potential problems in the monitored network.
• Custom configuration, filters, and false-positive flagging make the system highly customizable for diverse environments.
• Powerful dashboards make summaries and reporting a breeze.

• Complex attacks are identified frequently.
• Advanced thread intelligence.
• Privacy of all data is very well maintained.

• Multi-license policy
• Outdated GUI
• Limited use of AI methods

• False positives were identified frequently.
• Implementing rules are a very complex process.
• UI crashes were spotted randomly.
• Deployment needs to be much smoother.

• Early detection of cyber security events and incidents.
• Processing a large number of network flows on input (which means more than 60K flows per second)
• Parameterization of detection methods.
• The possibility to decide on the false-positive rate within the output of each method.

• Implementation did not go as planned. Therefore, time consumption was increased.
• Since we moved out of the tool, we had to consider another which costed time.