DESIGNED FOR VALUE CREATION.

DESIGNED WITH THE USER IN MIND.

Our technology was built from the ground up with a very special purpose in mind: to move you up the value chain by leveraging your data, no matter its volume, variety or velocity, and without ever compromising on your customers' privacy and data protection.

Featured Technology

Deep Packet Inspection


What is Deep Packet Inspection?

Deep packet inspection (DPI) is a type of network packet filtering. It evaluates both data and header of a packet that is going through an inspection point. Simultaneously, it extract data from packets.


How does DPI apply to threat detection?

DPI examines the content of the payload and extracts all the metadata that can be extracted. This information will be used by the threat detection engine to make accurate detection. This contextual information is also presented to the analyst on the dashboard so that the human analyst can have a better understanding of the threats and make informed decisions.

Intelligent Detection

With heuristics and behavioural based rule sets, DPI is able to provide intelligent security threat detection.

Advanced Detection

DPI provides the ability for full parsing of content layers of the packet which allows the detection of most dangerous attacks

Featured Technology

Machine Learning


What is machine learning?

Machine learning uses algorithms to parse data, learn from that data, and make informed decisions based on what it has learned. Deep learning structure algorithms in layers to create an "artificial neural network" that can learn and make intelligent decisions on its own.


How is ML/DL applied to threat detection?

Creating rules for detecting cyberattacks is a traditional method of defense. However, due to the sheer volume of attacks and their complexity, automating detection through ML/DL is necessary for scaling up our defenses. ML/DL algorithms help us learn from data in order to detect similar attacks and respond to behavior changes. They are applied in a series of detections such as traffic classification, malware domain classification (DGA), abnormal behavior detection, tunneling and exfiltration activities' detection.

Product Scalability

Manual rule creation cannot scale for all threats. ML/DL can help close the detection gap by learning from data.

Advanced Detection

Based on semi-supervised and unsupervised methods to detect similar or changing attacks

Featured Technology

Virtual Reality SoC

A futuristic cyber operation platform for conducting cyber security operation and incident response

Key Advantages

Virtual Reality

Multisensory
Experiences

Allows operations personnel to have a new experience to conduct Cyber Operation in the VR space.

Time
Efficiencies

Enhancement and extension of current cyber monitoring system (Contextus) for inter-operational collaboration in the same integrated workspace but different activity, extending the boundary beyond the physical space.

Increased
Flexibility

A futuristic way to conduct operation with the flexibility to setup different operational unit, with flexibility to add features and tools into the environment quickly.

New
Perspective

Enhance Visualisation and Operational experience with 3D visualisation, plus 360° views will improve personal productivity while conducting an operation.