When evaluating Intrusion Detection and Prevention Software (IDPS) solutions, essential features to consider include:
Real-time monitoring and alerting
Scalability
Integration capabilities
Data encryption
Machine learning and AI
Real-time monitoring and alerting allow immediate detection and response to threats, ensuring swift action to mitigate risks. Scalability ensures that the solution can grow with the network, handling increasing traffic and data without compromising performance. Integration capabilities allow the IDPS to work seamlessly with existing security infrastructure, providing a unified security posture.
Data encryption safeguards sensitive information both at rest and in transit, reducing the risk of data breaches. The incorporation of machine learning and AI enables the system to identify and adapt to new and evolving threats, enhancing the overall effectiveness of threat detection and prevention. These features foster a proactive security environment, providing robust protection against cyber threats.
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From a pure cyber security and technical point of view the most important aspects are: (1) The detection rate and (2) The width of coverage (how much attack surface is protected).
For the first one, it is unfortunately very difficult to assess the detection rate of a solution unless you are an expert with a large dataset of threats (known and unknown) at your disposal to benchmark the solution against. In any case, you should make sure the solution is capable of detecting unknown and novel threats - this is, the solution must go beyond heuristics and possess a profound understanding of cyber threats.
Second, the width of coverage means that the solution covers a large number of threat verticals but more importantly is deployed at anywhere where a threat may appear. In several cases, customers do not cover all the areas of their network.
So.. the technical aspects of your ID should be based on your environment.
So not trying to oversimplify or downplay the need for the IDS to meet your technical thresholds, but those get discussed a lot. Operational impacts/criteria are often overlooked, in my opinion. I think the key factors are usability (how easy it is to train my folks to use it? how easy is it to integrate it into my operational processes, etc.) and interoperability with my current security ecosystem.
If I have to do a lot of tweaking to get it to work or I need a workaround to get feed accuracy then I'm probably not inclined to pursue a product.
Tuning is one thing. I expect that, but I don't expect the coding equivalent to duct tape and bubblegum to get it to talk and interact with my SIEM, SOAR, etc.
- Capabilities, if we don't understand what these are it is unlikely we will have a success story.
- The expertise to operate
- Product documentation
- Training provided by a supplier
- Best practices
- Successful use case scenario (ideally from the same industry),
- Pricing (matters for local gov), etc.
Documentation. Algorithmic transparency. Ability to get someone smart on the phone FAST at the vendor, without going through gatekeepers. Confidence levels (statistical validity).
Find out what your peers are saying about Darktrace, Vectra AI, Check Point Software Technologies and others in Intrusion Detection and Prevention Software (IDPS). Updated: October 2024.
Intrusion Detection and Prevention Software (IDPS) helps organizations identify potential security threats and respond to them effectively to protect sensitive data and maintain network integrity.
IDPS provides real-time monitoring and analysis of network traffic to detect malicious activities. By leveraging advanced algorithms and machine learning, IDPS solutions can identify unusual patterns and potential threats that traditional firewalls might miss. This proactive approach helps in...
When evaluating Intrusion Detection and Prevention Software (IDPS) solutions, essential features to consider include:
Real-time monitoring and alerting allow immediate detection and response to threats, ensuring swift action to mitigate risks. Scalability ensures that the solution can grow with the network, handling increasing traffic and data without compromising performance. Integration capabilities allow the IDPS to work seamlessly with existing security infrastructure, providing a unified security posture.
Data encryption safeguards sensitive information both at rest and in transit, reducing the risk of data breaches. The incorporation of machine learning and AI enables the system to identify and adapt to new and evolving threats, enhancing the overall effectiveness of threat detection and prevention. These features foster a proactive security environment, providing robust protection against cyber threats.
From a pure cyber security and technical point of view the most important aspects are: (1) The detection rate and (2) The width of coverage (how much attack surface is protected).
For the first one, it is unfortunately very difficult to assess the detection rate of a solution unless you are an expert with a large dataset of threats (known and unknown) at your disposal to benchmark the solution against. In any case, you should make sure the solution is capable of detecting unknown and novel threats - this is, the solution must go beyond heuristics and possess a profound understanding of cyber threats.
Second, the width of coverage means that the solution covers a large number of threat verticals but more importantly is deployed at anywhere where a threat may appear. In several cases, customers do not cover all the areas of their network.
So.. the technical aspects of your ID should be based on your environment.
So not trying to oversimplify or downplay the need for the IDS to meet your technical thresholds, but those get discussed a lot. Operational impacts/criteria are often overlooked, in my opinion. I think the key factors are usability (how easy it is to train my folks to use it? how easy is it to integrate it into my operational processes, etc.) and interoperability with my current security ecosystem.
If I have to do a lot of tweaking to get it to work or I need a workaround to get feed accuracy then I'm probably not inclined to pursue a product.
Tuning is one thing. I expect that, but I don't expect the coding equivalent to duct tape and bubblegum to get it to talk and interact with my SIEM, SOAR, etc.
- Capabilities, if we don't understand what these are it is unlikely we will have a success story.
- The expertise to operate
- Product documentation
- Training provided by a supplier
- Best practices
- Successful use case scenario (ideally from the same industry),
- Pricing (matters for local gov), etc.
Education, documentation, use cases and best practices.
Documentation. Algorithmic transparency. Ability to get someone smart on the phone FAST at the vendor, without going through gatekeepers. Confidence levels (statistical validity).