DÏoT

Problem Setting

Massive attacks on vulnerable IoT devices cause data leakage or disruption of devices and systems.
Existing Intrusion Detection Systems (IDS) cannot detect zero-day attacks or introduce a high false alarm rate.
The highly dynamic attack landscape in IoT, the rapid growth and heterogeneity of IoT devices introduce new challenges for detecting attacks

Solution

DÏoT offers a unique network intrusion detection technology utilizing distributed deep learning-based algorithms for enabling IoT users to effortlessly and quickly protect their IoT devices and networks against attacks.

• Autonomous and efficient system based on distributed deep learning algorithms
• Zero-day attack detection, no false alarms
• Superior performance compared to state-of-the-art technologies
• Proven track record in IT and AI security research and successful industry collaborations of the heco-founders

Advanced Technology

• Novel network traffic modelling techniques that can detect the potential malicious traffic at packet-level granularity.
• Advanced AI algorithms boost accuracy and efficiency.
• Optimized distributed deep learning scheme boosts model training process while preserving privacy of IoT user data.

Customer Benefits

• Reliable, autonomous, and cost-effective solution to protect IoT devices and networks
• No tedious and error-prone setup required
• Privacy-preserving: Sensitive data of IoT users not shared with others