AI TEF for intelligent cyber threat detection and protection

Service description

The service aims at testing intelligent solutions related to industrial cyber security from different perspectives, ranging from the capability of industrial solutions ( industrial assets, software solutions or dedicated solutions to protect against cyber-attacks) to mitigate cyber risk, leveraging innovative data-driven approaches, to AI-based network anomaly detection.
The testing facility can offer secure industrial networks, industrial connected assets, IoT devices, Cloud and Edge infrastructure and related software stack.
Potential use cases to be developed and validated through service, but not limited to, are the following:

  • Reproducing in-lab a whole attack chain, including the phases of victim identification, vulnerabilities discovery, the implementation of infection tools and finally the trap that initiates the attack. Technically, the service will operate a server specialized in the attack delivery, and in the victim identification, and finally several vulnerable workstations that model the victims’ machines. These targets will be attacked through the victim’s browser with a simple click by exploiting a specific malware.

  • AI-powered threat detection systems and algorithms that allow to evaluate incident response strategies to the ever-evolving cyber threats scenarios. AI-based threat detection is designed to prevent evolving threat tactics that are difficult to detect and mitigate, such as expanding attack vectors, including IoT devices, cloud deployments, and mobile devices. Its objective is to address the increasing volume and velocity of cyberattacks, especially ransomware. The algorithms can detect any anomaly or pattern indicative of security breaches, cyberattacks, or other malicious activities, such as malware or ransomware, based on data sources such as network traffic logs, system event logs, user activity records available at the testing facility;

  • NLP-based solutions for spam/ham detection across different sources (emails, digital massages, calls, etc.);

  • Etc.

Expected results: Expected results: Series of experiments needed to test: – vulnerability assessment of the industrial asset – the risk of the industrial asset to integrate with other actors (edge computing, sensors, IoT solutions) – Procedures to mitigate the identified risk. In particular, this service will highlight the limitations of defense tools which, despite commercial announcements, are still unable to deal with this kind of threat, namely fileless attacks, where everything happens in memory.
Methodology: Needs and requirements – Analysis of concept; – Data preparation pipelines, – On site Test before Invest
Target: Industrial plant or asset provider

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