AI EdgeLabs
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About
AI EdgeLabs is a powerful and autonomous cybersecurity AI platform designed to protect edge and IoT infrastructures from various threats, including malware, ransomware, DDoS, and botnets. It leverages AI and machine learning to provide network visibility, early threat detection, and automated incident response. Key features include a centralized dashboard for attack surface visibility, robust security reporting, and easy integration into complex infrastructures. The platform consists of three main components: the Sensor (for on-the-spot threat detection and prevention), the Backbone (for communication and data storage), and The Lab (for R&D and model retraining). AI EdgeLabs caters to various industries, including retail, automotive, and telecommunications.
Platform
Task
Features
• automated incident response
• centralized dashboard
• edge and iot security
• ai-powered threat detection and prevention
• incident response & remediation
• threat analytics
• network visibility & anomaly detection
FAQs
What is edge computing?
Edge computing brings data processing closer to the source, reducing latency and bandwidth needs. It's particularly useful for IoT devices where sending all data to a central server is impractical.
What is Edge Security?
Edge security protects corporate resources outside of centralized data centers. It secures users and apps at the network's edge, a more vulnerable area for cyberattacks.
How does edge security help overcome edge computing challenges?
Edge security addresses the increased attack surface created by edge computing. It builds a security stack to defend against zero-day threats, malware, and other attacks.
What does edge security look like?
Edge security includes device security (managing and monitoring endpoints), cloud security (protecting data in the cloud), and network edge security (securing internet connectivity).
What is AI EdgeLabs?
AI EdgeLabs is a cybersecurity AI platform that helps security teams respond to attacks and protect Edge/IoT infrastructures. It offers network visibility, threat detection, and automated response.
What are the AI EdgeLabs components?
AI EdgeLabs has three main components: the Sensor (autonomous threat detection), the Backbone (communication and data storage), and The Lab (R&D and model retraining).
What security risks does AI EdgeLabs help protect against?
AI EdgeLabs protects against data theft, exfiltration, ransomware attacks, and unauthorized access to computing resources.
What are the AI EdgeLabs industry applications?
AI EdgeLabs has industry applications in retail, automotive, railway, manufacturing, telecommunications, oil and gas, transportation and logistics, agriculture, healthcare, smart cities, energy and utilities.
How does the AI EdgeLabs Sensor work?
The EdgeLabs Sensor is a network telemetry agent that scans, reports, and uses AI models to check traffic behavior and prevent threats. It provides real-time visibility and helps locate and resolve application performance issues.
What are the key features of AI EdgeLabs?
AI EdgeLabs key features include network visibility & anomaly detection, threat analytics, and incident response & remediation.
Is there a trial of AI EdgeLabs?
Yes, AI EdgeLabs offers a trial to test basic functionality.
What is a brute force attack?
A brute force attack is a hacking method that tries various usernames and passwords to gain unauthorized access.
What is an Intrusion Detection System (IDS)?
An Intrusion Detection System (IDS) monitors network events for security issues and potential threats, sending alerts to security personnel.
What is an Intrusion Prevention System (IPS)?
An Intrusion Prevention System (IPS) goes beyond detection by automatically taking steps to stop identified threats, such as blocking traffic or resetting connections.
Job Opportunities
Host Cyber Security Researcher Specialist - Linux OS
AI-powered cybersecurity platform for edge and IoT environments, providing threat detection, prevention, and automated response.
Benefits:
Competitive salary
All other perks and benefits
Unique working experience on an Autonomous Cyber AI solution for Edge and IOT environments
Experience Requirements:
3+ years of Cyber Security Research experience with a focus on Linux OS
Other Requirements:
Proficiency with eBPF and framework based on eBPF (Falco, bpftrace, bcc etc.)
Proficiency in malware analysis tools and techniques
Familiarity with malware sandboxing tools and virtual machines
Hands-on experience in pentesting and hacking
Basic knowledge of security issues associated with containers, Kubernetes, Distributed Systems, and Linux of large-scale web applications
Hands-on programming experience in Python, Golang, Bash, or any other programming language
Experience building IoT/OT, Edge, and network security solutions
Responsibilities:
Research and Implement Detection Algorithms
Malware Analysis and Signature Development
Develop Tools and Techniques
Network Traffic and Payload Analysis
Machine Learning and AI Integration
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