Critical Infrastructure Protection: Generative AI, Challenges, and Opportunities

• URL: http://arxiv.org/abs/2405.04874v1
• Date: Wed, 8 May 2024 08:08:50 GMT
• Title: Critical Infrastructure Protection: Generative AI, Challenges, and Opportunities
• Authors: Yagmur Yigit, Mohamed Amine Ferrag, Iqbal H. Sarker, Leandros A. Maglaras, Christos Chrysoulas, Naghmeh Moradpoor, Helge Janicke,
• Abstract summary: Critical National Infrastructure (CNI) encompasses a nation's essential assets that are fundamental to the operation of society and the economy. Growing cybersecurity threats targeting these infrastructures can potentially interfere with operations and seriously risk national security and public safety. We examine the intricate issues raised by cybersecurity risks to vital infrastructure, highlighting these systems' vulnerability to different types of cyberattacks.
• Score: 3.447031974719732
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Critical National Infrastructure (CNI) encompasses a nation's essential assets that are fundamental to the operation of society and the economy, ensuring the provision of vital utilities such as energy, water, transportation, and communication. Nevertheless, growing cybersecurity threats targeting these infrastructures can potentially interfere with operations and seriously risk national security and public safety. In this paper, we examine the intricate issues raised by cybersecurity risks to vital infrastructure, highlighting these systems' vulnerability to different types of cyberattacks. We analyse the significance of trust, privacy, and resilience for Critical Infrastructure Protection (CIP), examining the diverse standards and regulations to manage these domains. We also scrutinise the co-analysis of safety and security, offering innovative approaches for their integration and emphasising the interdependence between these fields. Furthermore, we introduce a comprehensive method for CIP leveraging Generative AI and Large Language Models (LLMs), giving a tailored lifecycle and discussing specific applications across different critical infrastructure sectors. Lastly, we discuss potential future directions that promise to enhance the security and resilience of critical infrastructures. This paper proposes innovative strategies for CIP from evolving attacks and enhances comprehension of cybersecurity concerns related to critical infrastructure.

Related papers

• Critical Infrastructure Security: Penetration Testing and Exploit Development Perspectives [0.0]
  This paper reviews literature on critical infrastructure security, focusing on penetration testing and exploit development. Findings of this paper reveal inherent vulnerabilities in critical infrastructure and sophisticated threats posed by cyber adversaries. The review underscores the necessity of continuous and proactive security assessments.
  arXiv  Detail & Related papers  (2024-07-24T13:17:07Z)
• Confronting the Reproducibility Crisis: A Case Study of Challenges in Cybersecurity AI [0.0]
  A key area in AI-based cybersecurity focuses on defending deep neural networks against malicious perturbations. We attempt to validate results from prior work on certified robustness using the VeriGauge toolkit. Our findings underscore the urgent need for standardized methodologies, containerization, and comprehensive documentation.
  arXiv  Detail & Related papers  (2024-05-29T04:37:19Z)
• A Value Driven Framework for Cybersecurity Innovation in Transportation & Infrastructure [0.0]
  This paper introduces a value-driven cybersecurity innovation framework for the transportation and infrastructure sectors. We aim to foster a culture of self-innovation within organizations, enabling a strategic focus on cybersecurity measures.
  arXiv  Detail & Related papers  (2024-05-12T18:45:11Z)
• Securing the Open RAN Infrastructure: Exploring Vulnerabilities in Kubernetes Deployments [60.51751612363882]
  We investigate the security implications of and software-based Open Radio Access Network (RAN) systems. We highlight the presence of potential vulnerabilities and misconfigurations in the infrastructure supporting the Near Real-Time RAN Controller (RIC) cluster.
  arXiv  Detail & Related papers  (2024-05-03T07:18:45Z)
• Cybersecurity in the Quantum Era: Assessing the Impact of Quantum Computing on Infrastructure [0.04096453902709291]
  This analysis explores the impact of quantum computing on critical infrastructure and cloud services. We advocate for proactive security strategies and collaboration between sectors to develop and implement quantum-resistant cryptography. This blueprint strengthens each area's defenses against potential quantum-induced cyber threats.
  arXiv  Detail & Related papers  (2024-04-16T15:36:23Z)
• Performance Analysis of Decentralized Physical Infrastructure Networks and Centralized Clouds [42.37170902465878]
  Decentralized Physical Infrastructure Networks (DePINs) aim to enhance data sovereignty and confidentiality and increase resilience against a single point of failure. This work focuses on the potential of DePINs to disrupt traditional centralized architectures by taking advantage of the Internet of Things (IoT) devices and crypto-economic design in combination with blockchains.
  arXiv  Detail & Related papers  (2024-04-12T08:00:38Z)
• Generative AI for Secure Physical Layer Communications: A Survey [80.0638227807621]
  Generative Artificial Intelligence (GAI) stands at the forefront of AI innovation, demonstrating rapid advancement and unparalleled proficiency in generating diverse content. In this paper, we offer an extensive survey on the various applications of GAI in enhancing security within the physical layer of communication networks. We delve into the roles of GAI in addressing challenges of physical layer security, focusing on communication confidentiality, authentication, availability, resilience, and integrity.
  arXiv  Detail & Related papers  (2024-02-21T06:22:41Z)
• The Security and Privacy of Mobile Edge Computing: An Artificial Intelligence Perspective [64.36680481458868]
  Mobile Edge Computing (MEC) is a new computing paradigm that enables cloud computing and information technology (IT) services to be delivered at the network's edge. This paper provides a survey of security and privacy in MEC from the perspective of Artificial Intelligence (AI) We focus on new security and privacy issues, as well as potential solutions from the viewpoints of AI.
  arXiv  Detail & Related papers  (2024-01-03T07:47:22Z)
• ThreatKG: An AI-Powered System for Automated Open-Source Cyber Threat Intelligence Gathering and Management [65.0114141380651]
  ThreatKG is an automated system for OSCTI gathering and management. It efficiently collects a large number of OSCTI reports from multiple sources. It uses specialized AI-based techniques to extract high-quality knowledge about various threat entities.
  arXiv  Detail & Related papers  (2022-12-20T16:13:59Z)
• The Opportunity to Regulate Cybersecurity in the EU (and the World): Recommendations for the Cybersecurity Resilience Act [1.2691047660244335]
  Safety is becoming cybersecurity under most circumstances. This should be reflected in the Cybersecurity Resilience Act when it is proposed and agreed upon in the European Union. It is based on what the cybersecurity research community for long have asked for, and on what constitutes clear hard legal rules instead of soft.
  arXiv  Detail & Related papers  (2022-05-26T07:20:44Z)
• Dos and Don'ts of Machine Learning in Computer Security [74.1816306998445]
  Despite great potential, machine learning in security is prone to subtle pitfalls that undermine its performance. We identify common pitfalls in the design, implementation, and evaluation of learning-based security systems. We propose actionable recommendations to support researchers in avoiding or mitigating the pitfalls where possible.
  arXiv  Detail & Related papers  (2020-10-19T13:09:31Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.