ARTINALI#: An Efficient Intrusion Detection Technique for Resource-Constrained Cyber-Physical Systems

Aliabadi, Maryam Raiyat; Seltzer, Margo; Asl, Mojtaba Vahidi; Ghavamizadeh, Ramak

doi:10.1016/j.ijcip.2021.100430

Cited by 9 publications

(2 citation statements)

References 25 publications

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“…However, the heterogeneity of devices currently means that a separate solution is required for each type of device. That is why most researchers propose an HIDS focused on a single or few device types (e.g., a smart artificial pancreas [133], a smart-connected-pacemaker [101], or a diabetes management control system [44]). The transferability of these approaches to the real world and, in particular, scalability are problems that are often not addressed by researchers.…”

Section: Advancing Standardization Projectsmentioning

confidence: 99%

Attack Detection for Medical Cyber-Physical Systems–A Systematic Literature Review

et al. 2023

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The threat situation due to cyber attacks in hospitals is emerging and patient life is at risk. One significant source of potential vulnerabilities is medical cyber-physical systems (MCPS). Detecting intrusions in this environment faces challenges different from other domains, mainly due to the heterogeneity of devices, the diversity of connectivity types, and the variety of terminology. To summarize existing results, we conducted a structured literature review (SLR) following the guidelines of Kitchenham et al. for SLRs in software engineering. We developed six research questions regarding detection approach, detection location, included features, adversarial focus, utilized datasets, and intrusion prevention. We identified that most researchers focused on an anomaly-based detection approach at the network layer. The primary focus was on the detection of malicious insiders. While several researchers used publicly available datasets for training and testing their algorithms, the lack of suitable datasets resulted in the development of testbeds consisting of various medical devices. Based on the results, we formulated five future research topics. First, the special conditions of hospital networks, the MCPS deployed within them, and the contrasts to other IT and OT environments should be examined. Thereupon, MCPS-specific datasets should be created that allow researchers to address the health domain's unique requirements and possibilities. At the same time, endeavors aimed at standardization in this area should be supported and expanded. Moreover, the use of medical context for attack detection should be further explored. Last but not least, efforts for MCPS-tailored intrusion prevention should be intensified. This way, the emerging threat landscape can be addressed, IT security in hospitals can be improved, and patient health can be protected.

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Section: Advancing Standardization Projectsmentioning

confidence: 99%

Attack Detection for Medical Cyber-Physical Systems–A Systematic Literature Review

et al. 2023

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“…Several botnets carry out attacks at the same time with simultaneous characteristics, which are substantially more intense than sporadic and periodic attacks. Most detection systems, especially models that use clustering and deep learning techniques, consume many resources, causing problems when the detection is carried out at the same time in a short time frame [5 , 6] . The proposed dataset has the characteristics of simultaneous attacks in a short period, so the security system must survive resource problems when dealing with botnet attacks.…”

Section: Data Descriptionmentioning

confidence: 99%