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Ensign InfoSecurity bags Technology Excellence Award for Cybersecurity – Artificial Intelligence

Conquering advanced and emerging cyber threats with Ensign’s patented AI-Powered Cyber Analytics Solutions.

As more firms increase their digital presence, notably during a global pandemic that accelerated the adoption of technologies, various threat actors have deployed advanced techniques to evade traditional, rules-based threat monitoring systems. Unequipped to detect these emerging or unknown threats, many organisations have become more vulnerable.

To address this, Ensign responds with its AI-Power Cyber Analytics. Built by an experienced team of threat researchers and data scientists, the technology is powered by patented algorithms and novel approaches. Its self-learning threat detection models leverage deep neural networks, proprietary self-learning training techniques, and customised behavioural analytics to provide customers with a technological edge in detecting threats. Beyond relying on known threat types, the technology analyses the organisation’s network traffic to identify anomalous patterns that may indicate an attack.

With its AI-Powered Cyber Analytics solution, Ensign is able to have improved visibility of the threat landscape and enable its clients to detect and stop threats which would otherwise not be detected by traditional cyber security tools. 

“Customers who opt for our AI-Powered Cyber Analytics solution benefit from powerful algorithms that enable the detection of advanced and emerging threats. It allows organisations to gain better visibility into impending attacks quicker and more accurately,” Mr Tan Ah Tuan, Executive Vice President, Ensign Labs said. 

For its efforts to enable organisations to conquer unknown cyber threats, Ensign InfoSecurity bagged the Cybersecurity - AI Award at the recently concluded Technology Excellence Awards, presented by Singapore Business Review. In its fourth year, the awards event lauds companies in Singapore that have pioneered ground-breaking IT products, solutions or initiatives that are leading the technological revolution and digital journeys of their respective industries. 

Ensign has deployed its AI-Powered Cyber Analytics solutions into clients’ security operations centres (SOCs) to enhance their capabilities to detect threats that traditional cyber security tools would not be able to detect and deter. The technology has also been deployed into Ensign’s SOC where it provides Managed Security Services (MSS). MSS customers benefit from advanced threat detection when they opt for Ensign’s data models as part of their MSS package. This solution gives Ensign a unique edge as one of the only MSS providers in APAC that enhances its threat detection capability with proprietary AI-powered models. 

Ensign’s technology has yielded major successes and is backed by novel approaches and patents:

  • Patented self-learning technique 
    Ensign’s patented Self-Learning Threat Detection can leverage partially labelled and unlabelled data to train deep learning models, facilitating automatic detection of new, unknown threats.
  • Patented technology to detect communications to malicious domains via DGA 
    Ensign’s AI-Powered DGA detection model can reduce malicious domain communications alerts by more than 99.99%, minimising alert fatigue, improving accuracy, and accelerating response time. 
  • Patent-pending Phishing Detection 
    Ensign’s Phishing Detection Approach yields more than 95% accuracy rate when detecting phishing attacks and can detect advanced attacks using Homoglyph and Typosquatting/Typoswyping techniques.

“Our AI-Powered Cyber Analytics technology is also a force multiplier that supports cyber teams by improving accuracy of detection, reducing alert fatigue, and improving focus via triage of prioritised correlated incidents,” Mr Tan Ah Tuan, Executive Vice President, Ensign Labs explained. 

Headquartered in Singapore, Ensign has built a library of data models designed to detect a variety of threats and is constantly adding to its repertoire with new threat models to stay ahead of the changing threat landscape.

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