Design of a Novel Information System for Semi-automated Management of Cybersecurity in Industrial Control Systems

Abstract

There is an urgent need in many critical infrastructure sectors, including the energy sector, for attaining detailed insights into cybersecurity features and compliance with cybersecurity requirements related to their Operational Technology (OT) deployments. Frequent feature changes of OT devices interfere with this need, posing a great risk to customers. One effective way to address this challenge is via a semi-automated cyber-physical security assurance approach, which enables verification and validation of the OT device cybersecurity claims against actual capabilities, both pre- and post-deployment. To realize this approach, this paper presents new methodology and algorithms to automatically identify cybersecurity-related claims expressed in natural language form in ICS device documents. We developed an identification process that employs natural language processing (NLP) techniques with the goal of semi-automated vetting of detected claims against their device implementation. We also present our novel NLP components for verifying feature claims against relevant cybersecurity requirements. The verification pipeline includes components such as automated vendor identification, device document curation, feature claim identification utilizing sentiment analysis for conflict resolution, and reporting of features that are claimed to be supported or indicated as unsupported. Our novel matching engine represents the first automated information system available in the cybersecurity domain that directly aids the generation of ICS compliance reports.

Transforming Cybersecurity into Critical Energy Infrastructure: A Study on the Effectiveness of Artificial Intelligence

“…In the discussion of the security of ICSs, Ameri et al's [9] work provides a valuable analysis of how AI-based defense strategies can mitigate risks in critical infrastructures. It matches our findings, showing a 90% reduction in undetected security incidents at ICSs, underscoring the ability of AI systems to identify and neutralize threats efficiently.…”

“…One of the fundamental aspects of the literature is identifying specific cyber threats facing the energy sector [8]. Studies such as those by Ameri et al demonstrate how vulnerabilities in Industrial Control Systems (ICSs) [9] can be exploited to cause significant disruptions. This work highlights the need for AI solutions that can proactively detect and neutralize threats, serving as a basis for subsequent research that focuses on developing anomaly-detection algorithms specific to these environments.…”

“…Studies such as those by Ameri et al [9] and Siva Kumar et al [12] illustrate the complexities and risks associated with industrial control systems and network infrastructure in the energy sector. AI tools must be integrated precisely to maintain operational stability and security, a critical aspect that Jadidi et al [21] examined by detailing effective cybersecurity management strategies.…”

Cyber Threat Assessment and Management for Securing Healthcare Ecosystems using Natural Language Processing

“…Also in [35], a closed-domain CS BERT model, fine-tuned with a large corpus of textual CS data to recognise CS entities. The CyBERT model focuses on the identification of CS claims in Industrial Control Systems (ICS) NL documents [36,37]. The authors collected a large corpus of labelled sequences from ICS device documentation to pretrain and fine-tune a BERT language model.…”

Design and Implementation of an Information Management System for College Students in Higher Education Institutions Based on Cloud Computing

“…This method also proposes a solution to the problem of network load balancing, but the comprehensive load capacity of the server is not fully considered, resulting in long network response time and easy occurrence of network unresponsiveness. American K et al [5] proposed a semi automated method for ensuring network physical security, which can automatically identify and verify network security related statements in industrial control system equipment documents through the development of new algorithms and tools, thereby assisting in the generation of compliance reports and reducing OT device security risks. However, this method does not take into account the issue of storing a large amount of data in the system, which may lead to server overload.…”