NTT Com Security adds machine learning detection capabilities

NTT Com Security, in collaboration with NTT Communications, has added machine learning capabilities to its Managed Security Services (MSS) solution under the WideAngle brand. The new move forms part of the global information security and risk management company’s strategy to develop and deliver the smartest threat detection intelligence for organisations around the world.

8 years ago Posted in

The machine learning enhancements, which are part of NTT Com Security’s innovative analysis engine, are able to detect infections of unknown malware in real time. These detection logic enhancements are equipped to ‘know’ when an unknown pattern is associated with malware communication and then alert on suspicious patterns 24/7.

“Evasion now becomes much harder for cyber criminals,” said Tore Terjesen, Director of Security Labs at NTT Com Security. “Our machine learning method addresses techniques commonly used by intruders to bypass blacklist detection, techniques that until now have proven to be both successful and essential for the continuous survival of the malware infection. Machine learning detection methods previously proposed in the industry typically suffer from a high false positive rate or low hit rate. We have invested in machine learning to improve and optimize our analysis with respect to this. When complemented with our existing threat detection methods, these will provide our customers with meaningful information for active advanced security and risk management.”

Machine learning is defined as a subset of artificial intelligence that gives computers the ability to learn without being explicitly programmed. In order to build models that detect malware designed to bypass state of the art intrusion detection systems, access to both malicious and benign activity patterns are required. To achieve this, NTT Com Security takes advantage of its large network of honeypots and the data shared by means of the NTT Global Threat Intelligence Platform when building machine learning models. The analysis engine also has the ability to combine scattered activity fragments and suppress or support the composite pattern depending on the overall level of confidence. In the context of security, highly advanced malware detection intelligence can make it extremely difficult for cyber criminals to evade an analysis engine. In effect, customers can proactively mitigate risks from complex and emerging security threats.

NTT Com Security is the first MSS partner to deliver fully-operational real time detection capabilities of this kind. With its machine learning post infection detection methods now implemented by market-leading organizations and government agencies worldwide, the company is looking to apply similar techniques to enhance its pre infection detection capabilities. NTT Com Security’s Research and Development teams are now developing additional machine learning functions and world-class analytics that leverage the Global Threat Intelligence Platform to collate and analyse high quality data across its comprehensive global network.

Tore added: “More and more organisations are collaborating with MSS providers for collective knowledge and advanced research. The fact that NTT Com Security is part of NTT Group means our WideAngle MSS solution can benefit from the $3.5 billion invested annually in global Research and Development activities to respond to the changing threat environment. Machine learning is our latest investment in detection intelligence for our MSS solution and we are proud to be the first in operation.”

NTT Com Security adds machine learning detection capabilities

89% of security leaders think traditional security approaches are failing in the face of modern threats

Lack of automated patch management a remote security risk

Clearlake Capital to acquire Quest Software

Dell Technologies and AWS collaborate

Aqua Security acquires Argon

79% of European businesses already seeing savings from shift to cloud security

Costs, cyberattacks and compliance - cause for concern

Renewable energy powers Zscaler