Web 3.0 security firm SeQure adds support for Neo N3 to its network monitoring & hack detection software
Web 3.0 security firm SeQure has added support for Neo to its blockchain anomaly detection product, SeQure-AI. The service uses a machine learning model and network monitoring to detect hacks and bugs as they occur in real-time, potentially aiding in asset recovery.
SeQure provides various software services to help protect Web 3.0 infrastructure, bringing with it over 15 years of combined expertise in cryptography and cybersecurity.
The team claims to have analyzed over 100 large-scale hacking events in the blockchain industry and devised solutions for more than 10 different forms of attack. Examples include mitigations for flashloan exploits, denial of service, and compromised private keys.
The company currently offers three main products:
- SeQure-Key: An end-to-end key management system
- SeQure-AI: Anomaly detection for blockchain networks
- SeQure-ET: A technology to detect and automatically upgrade encryption algorithms
Cross-chain bridge hacks are noted as a specialty for SeQure, as these are one of the most common security risks in Web 3.0. SeQure recently partnered with Poly Network, integrating it as a supported chain in the SeQure-AI product.
Alongside the Neo integration, the team recently launched SeQure-Dashboard, a tool that allows users to perform statistical analysis on transaction histories and receive notifications for hack events.
According to SeQure, the most notable feature of its machine learning model is the ability to train it using only normal transaction data. In other words, rather than detecting malicious activity by looking for known attack patterns, the solution detects deviations from regular network activity.
This allows the system to flag suspicious behavior for investigation even in cases where the attack is novel or when a network has little or no prior history of attacks to use for training.
The SeQure team is working on another tool, dubbed Whitehacker, which will use the malicious behaviors learned through SeQure-AI to mimic hacker activity. This can be used to provide security benchmarks for supported blockchains and smart contracts.
The original announcement can be read at the following link:
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