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Description
Threat detection entails a thorough examination of each individual network packet along with its contained data, featuring elements such as network protocol identification and verification, which allows for the identification of both obscure and concealed protocols. It incorporates machine learning techniques that provide a proactive assessment of traffic risk through scoring systems. Additionally, the detection of network steganography helps uncover hidden traffic within the network, including potential data breaches, espionage activities, and botnet communications. Utilizing proprietary algorithms for steganography detection serves as an efficient means of revealing various information concealment strategies. Furthermore, a unique signature database containing an extensive array of recognized network steganography techniques enhances detection capabilities. Forensic analysis is employed to effectively evaluate the ratio of security incidents relative to the traffic source. Facilitating the extraction of high-risk network traffic aids in concentrating analysis on specific threat levels, while storing processed traffic metadata in an extended format accelerates the trend analysis process. This multifaceted approach ensures a comprehensive understanding of network security challenges and enhances the ability to respond to emerging threats.
Description
HookProbe is an innovative open-source intrusion detection and prevention system (IDS/IPS) designed to operate on Raspberry Pi and edge computing devices. By integrating eBPF/XDP for kernel-level packet filtering with advanced machine learning for threat classification, it provides a self-sufficient network security solution that does not rely on cloud services.
The system architecture features components like NAPSE, which handles AI-driven packet inspection; HYDRA, which manages the threat intelligence pipeline; SENTINEL, serving as the machine learning classification engine; and AEGIS, which orchestrates autonomous defense mechanisms. Remarkably, a single Raspberry Pi 5 can effectively manage over 11 million security events, accurately classify 177,000 machine learning verdicts, and monitor more than 11,800 attacker IP addresses—all without human intervention.
Notable functionalities include:
- Quick installation process taking only five minutes on a Raspberry Pi 5 or any compatible Linux device
- High-speed packet filtering and DDoS protection through eBPF/XDP
- Machine learning-driven threat classification categorizing events as benign, suspicious, or malicious
- Immediate security posture assessment using QSecBit scoring
- User-friendly web dashboard that enables live visualization of threats
- Implementation of post-quantum cryptography standards, specifically Kyber KEM
- A collaborative mesh defense system that enhances security across multiple nodes.
This combination of features ensures that HookProbe delivers a robust, adaptable, and highly autonomous security solution suitable for modern network environments.
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Free Trial
Free Version
Pricing Details
$9/month
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Cryptomage
Founded
2015
Country
Poland
Website
cryptomage.io/cybereye
Vendor Details
Company Name
HookProbe
Founded
2022
Country
Romania
Website
hookprobe.com
Product Features
Cybersecurity
AI / Machine Learning
Behavioral Analytics
Endpoint Management
IOC Verification
Incident Management
Tokenization
Vulnerability Scanning
Whitelisting / Blacklisting
