The third challenge is that while organisations, especially the larger enterprises, have invested in various mechanisms to continuously find out what kind of vulnerabilities exist in a network, they are unable to decide which ones to prioritise and patch. This was part of the problem we saw last year when the Wannacry incident happened. The compromise was well known, but when the incident happened it took everyone by surprise because most organisations took no measures to patch it up.
These are the three practical challenges and they can only be tackled if you use machine learning, deep learning and artificial intelligence, combined with the human brain. That is what Paladion has done.
While our platform drives enhanced security results at every stage of a potential threat’s lifecycle, we specifically designed it to tackle the three modern security challenges I mentioned above.
First, our AI platform detects unknown attacks that follow unknown attack patterns.
We have built algorithms and statistical models that find anomalous, potentially malicious patterns within user and network behaviour. Our AI platform uncovers these behaviours, and then presents them to our experienced analysts and Threat Hunters.
These human experts utilise these AI-generated enriched alerts to determine if they are witnessing a false alarm, or if they’ve found an unknown threat—with no previous record or signature—emerging within the network.
Second, our AI platform can not only identify an organisation’s vulnerabilities, our platform also prioritises those vulnerabilities, and helps organisations focus on real threats.
We designed our AI platform to give special attention to vulnerabilities with existing exploits. If our platform identifies 10,000 vulnerabilities in your network, but sees that only 1,000 of those vulnerabilities have existing exploits, then our AI will tell you to patch those 1,000 exploitable vulnerabilities before you handle the remaining 9,000 lower-priority issues.
Third, we built our AI to help our clients contain and control their uncovered incidents ASAP.
To do this, we used our AI to build “rule books”, also known as “incident response mechanisms”. These help us quickly uncover threats, and then immediately focus on how to effectively respond to them. Our Machine Learning algorithms allow us to rapidly develop very fast, consistent responses to unknown threats. The result: drastically reduced dwell times.
Excellent. Dubai as a city and UAE as a country has embraced most of the latest technologies for the right reasons.
We want to help Dubai on its path to becoming a smarter city and of course, you can only get smart analytics if you embrace AI.
Gone are the days when cybersecurity used to sit in one corner of the IT park. It has become a board level decision. You talk about any strategic initiatives of organisations or for that matter a country and cyber security is in the top two or three. You cannot do that unless you embrace the latest in terms of innovation and AI.
That is where we find our managed detection response service and AI driven MDR service is resonating extremely well especially in this part of the world. It’s not only for enterprise customers, the SME segment can use it. It is cloud ready, easy to deploy and the customer gets seamless and results and outcome based results.
We wanted to invest in the region so that we could be closer to regional customers. From the Command Centre we are providing the detection response mechanism and we are also providing time dissipation services which are more regionally driven. By combining this centre with global command centres, we are able to offer customers the best of both worlds: a regional security outlook with a global perspective.