Toward the Integration of Cyber and Physical Security Monitoring Systems for Critical Infrastructures

Fausto, Alessandro; Gaggero, Giovanni Battista; Patrone, Fabio; Girdinio, P.; Marchese, Mario

doi:10.3390/s21216970

Cited by 21 publications

(10 citation statements)

References 26 publications

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“…They combined this with a random forest classifier to detect attacks from the new representation. Fausto et al [33] proposed an anomaly detection method based on machine learning. This method is different from those that only use information from the physical or cyber domains; it detects potential anomaly events by integrating data related to both the physical and cyber domains, making the method more universally valuable.…”

Section: Related Workmentioning

confidence: 99%

Intrusion Detection Based on Adaptive Sample Distribution Dual-Experience Replay Reinforcement Learning

Tan,

Wang,

Zhu

et al. 2024

Mathematics

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In order to cope with ever-evolving and increasing cyber threats, intrusion detection systems have become a crucial component of cyber security. Compared with signature-based intrusion detection methods, anomaly-based methods typically employ machine learning techniques to train detection models and possess the capability to discover unknown attacks. However, intrusion detection methods face the challenge of low detection rates for minority class attacks due to imbalanced data distributions. Traditional intrusion detection algorithms address this issue by resampling or generating synthetic data. Additionally, reinforcement learning, as a machine learning method that interacts with the environment to obtain feedback and improve performance, is gradually being considered for application in the field of intrusion detection. This paper proposes a reinforcement-learning-based intrusion detection method that innovatively uses adaptive sample distribution dual-experience replay to enhance a reinforcement learning algorithm, aiming to effectively address the issue of imbalanced sample distribution. We have also developed a reinforcement learning environment specifically designed for intrusion detection tasks. Experimental results demonstrate that the proposed model achieves favorable performance on the NSL-KDD, AWID, and CICIoT2023 datasets, effectively dealing with imbalanced data and showing better classification performance in detecting minority attacks.

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Section: Related Workmentioning

confidence: 99%

Intrusion Detection Based on Adaptive Sample Distribution Dual-Experience Replay Reinforcement Learning

Tan,

Wang,

Zhu

et al. 2024

Mathematics

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“…Their research focused on the ability of deep learning anomaly detection systems to increase security across several different kinds of CPS. Fausto et al (2021) explored the integration of CPS logs into processes that review other typical information logs to detect cyber threats and physical anomalies. Frattini et al (2019) also researched a merging of log information by proposing a combination of security incident and event management and physical security incident management systems, finding that merging plant condition management software and IBM's QRadar in test scenarios benefits security analysis in detecting attacks that target both physical and digital vulnerabilities.…”

Section: Cyber/corporate Security Mergermentioning

confidence: 99%

Organizational perspectives on converged security operations

Mattord,

Kotwica,

Whitman

et al. 2023

ICS

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Purpose The purpose of this paper is to explore the current practices in security convergence among and between corporate security and cybersecurity processes in commercial enterprises. Design/methodology/approach This paper is the first phase in a planned multiphase project to better understand current practices in security optimization efforts being implemented by commercial organizations exploring means and methods to operate securely while reducing operating costs. The research questions being examined are: What are the general levels of interest in cybersecurity and corporate security convergence? How well do the perspectives on convergence align between organizations? To what extent are organizations pursuing convergence? and How are organizations achieving the anticipated outcomes from convergence? Findings In organizations, the evolution to a more optimized security structure, either merged or partnered, was traditionally due to unplanned or unforeseen events; e.g. a spin-off/acquisition, new security leadership or a negative security incident was the initiator. This is in contrast to a proactive management decision or formal plan to change or enhance the security structure for reasons that include reducing costs of operations and/or improving outcomes to reduce operational risks. The dominant exception was in response to regulatory requirements. Preliminary findings suggest that outcomes from converged organizations are not necessarily more optimized in situations that are organizationally merged under a single leader. Optimization may ultimately depend on the strength of relationships and openness to collaboration between management, cybersecurity and corporate security personnel. Research limitations/implications This report and the number of respondents to its survey do not support generalizable findings. There are too few in each category to make reliable predictions and in analysis, there was an insufficient quantity of responses in most categories to allow supportable conclusions to be drawn. Practical implications Practitioners may find useful contextual clues to their needs for convergence or in response to directives for convergence from this report on what is found in some other organizations. Social implications Improved effectiveness and/or reduced costs for organizational cybersecurity would be a useful social outcome as organizations become more efficient in the face of increasing levels of cyber security threats. Originality/value Convergence as a concept has been around for some time now in both the practice and research communities. It was initially promoted formally by ASIS International and ISACA in 2005. Yet there is no universally agreed-upon definition for the term or the practices undertaken to achieve it. In addition, the business drivers and practices undertaken to achieve it are still not fully understood. If convergence or optimization of converged operations offers a superior operational construct compared to other structures, it is incumbent to discover if there are measurable benefits. This research hopes to define the concept of security collaboration optimization more fully. The eventual goal is to develop and promote a tool useful for organizations to measure where they are on such a continuum.

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“…The notion of the critical infrastructure is well-documented (with a full classification provided by the United States Department of Homeland Security in [1]). Society relies on the critical infrastructure service provision, and their interconnectivity is immensely complex providing an ever-growing research trend within domains such as cyber [2], resilience [3,4], physical protection [5] and cascading failure modelling [6]. Alongside these mainstay research areas, as this article demonstrates, critical infrastructure strain is receiving growing attention.…”

Section: Introductionmentioning

confidence: 97%

Critical Infrastructures: Reliability, Resilience and Wastage

et al. 2022

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By 2050, according to the UN medium forecast, 68.6% of the world’s population will live in cities. This growth will place a strain on critical infrastructure distribution networks, which already operate in a state that is complex and intertwined within society. In order to create a sustainable society, there needs to be a change in both societal behaviours (for example, reducing water, energy or food waste activities) and future use of smart technologies. The main challenges are that there is a limited aggregated understanding of current waste behaviours within critical infrastructure ecosystems, and a lack of technological solutions to address this. Therefore, this article reflects on theoretical and applied works concerning waste behaviours, the reliability/availability and resilience of critical infrastructures, and the use of advanced technologies for reducing waste. Articles in the Scopus digital library are considered in the investigation, with 51 papers selected by means of a systematic literature review, from which 38 strains, 86 barriers and 87 needs are identified, along with 60 methods of analysis. The focus of the work is primarily on behaviours, barriers and needs that create an excess or wastage.

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Toward the Integration of Cyber and Physical Security Monitoring Systems for Critical Infrastructures

Cited by 21 publications

References 26 publications

Intrusion Detection Based on Adaptive Sample Distribution Dual-Experience Replay Reinforcement Learning

Intrusion Detection Based on Adaptive Sample Distribution Dual-Experience Replay Reinforcement Learning

Organizational perspectives on converged security operations

Critical Infrastructures: Reliability, Resilience and Wastage

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