Threats identification for the smart Internet of Things in eHealth and adaptive security countermeasures

Habib, Kashif; Leister, Wolfgang

doi:10.1109/ntms.2015.7266525

Cited by 19 publications

(15 citation statements)

References 20 publications

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“…The authors identify two types of attackers in IoT health systems: a) Internal Attackers (that exist within the healthcare system and execute malicious operations secretly), and b) External Attackers (that reside outside the healthcare system and and perform malicious activities. An adversarial model is also presented in [57], combined with an asset-based approach. The authors identify key assets (personal, physical, information, and intangible assets) and they further classify the vulnerabilities that can be exploited by a threat agent to harm a system.…”

Section: A: Threat Modeling For Iomtmentioning

confidence: 99%

“…Additionally, some exploitation methods could also include direct attack, social engineering, malware and various combinations [8]. In [57] the authors present an asset-based vulnerability framework for IoMT. Once the key system assets are identified, the next step entails the identifications of the various vulnerabilities that might be exploited by a threat agent to harm a healthcare system.…”

Section: A: Iomt-specific Vulnerability Assessmentmentioning

confidence: 99%

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Risk Assessment Methodologies for the Internet of Medical Things: A Survey and Comparative Appraisal

et al. 2021

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The Internet of Medical Things (IoMT) has revolutionized health care services by providing significant benefits in terms of patient well being and relevant costs. Traditional risk assessment methodologies, however, cannot be effectively applied in the IoMT context since IoMT devices form part of a distributed and trustless environment and naturally support functionalities that favor reliability and usability instead of security. In this work we present a survey of risk assessment and mitigation methodologies for IoMT. For conducting the survey, we assess two streams of literature. First, we systematically review and classify the current scientific research in IoMT risk assessment methodologies. Second, we review existing standards/best practices for IoMT security assessment and mitigation in order to i) provide a comparative assessment of these standards/best practices on the basis of predefined criteria (scope and/or coverage, maturity level, and relevant risk methodology applied) and ii) identify common themes for IoMT security controls. Based on the analysis, we provide various IoMT research and implementation gaps along with a road map of fruitful areas for future research. The paper could be of significant value to security assessment researchers and policymakers/stakeholders in the health care industry.

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Section: A: Threat Modeling For Iomtmentioning

confidence: 99%

Section: A: Iomt-specific Vulnerability Assessmentmentioning

confidence: 99%

Risk Assessment Methodologies for the Internet of Medical Things: A Survey and Comparative Appraisal

et al. 2021

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“…The authors discussed [46] the importance of using a dynamic security mechanism in the field of eHealth systems in order to identify attacks, such as privacy violation, denial-of-service, data manipulation, man-in-the-middle, etc. The authors suggested using environmental sensors and system monitoring components in the devices, in order to explore security events in the internal and external environment.…”

Section: C: Threats Identification and Adaptive Security Countermeasumentioning

confidence: 99%

SEC-C-U: The Security of Intensive Care Unit Medical Devices and Their Ecosystems

2020

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An intensive care unit (ICU) is dedicated to caring for patients whose medical condition places them at high risk of mortality or serious morbidity. ICU medical devices (ICUMDs) are used to closely monitor, stabilize, and treat ICU patients who are often unconscious and rely almost solely on ICUMDs. ICUMDs have become more autonomous, with a range of components, connectivity to external devices, and functionalities, opening the door to cyber-attacks. We present a taxonomy based on the functionality of 19 widely used ICUMDs, providing an explanation of each device's medical role, properties, interactions, and how they impact each other's security. We provide an extensive survey of 16 possible attacks aimed at ICUMDs and assess each device's vulnerability. We also create an ecosystem graph describing the roles and interactions of the players of each ICU sub-department. For each device type we produce a unique attack flow diagram that presents the most vulnerable vectors and components within the ecosystem. Finally, we survey relevant security mechanisms and map their coverage for the attacks, identifying existing gaps. We show that current security mechanisms generally fail to provide protection, covering just 12.5-56.3% of the attacks against ICUMDs, leaving the devices and the patients vulnerable.

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“…The number of DoS attacks are in majority that may be hurled in contradiction of the IoT, example channels jamming process, high computational consumption possessions like recollection process, bandwidth, disk storage or processing time, and disruption of node information behavior. [23][24] [25] 3) Physical attacks: These attacks interfere with hardware mechanisms. As the unattended and dispersed environment of IoT, most of the devices characteristically work in outdoor surroundings, which are extremely vulnerable to physical bouts.…”

Section: Security Threats In Internet Of Thingsmentioning

confidence: 99%

An Efficient Approach for the Security Threats on Data Centers in IOT Environment

Alshammari¹

2017

ijacsa

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Abstract-Internet of Things has progressed from the conjunction of wireless knowledge, MEMS which is termed as micro electromechanical systems, micro facilities and the Internet. The conjunction has helped scratch down the storage walls concerning operating technology (OT) and information technology (IT), and allowing amorphous machine created data to be examined for understandings that will drive enhancements. The Things known as IOT is an arrangement of interconnected computing procedures, mechanical and digital machineries, substances or matters that are delivered with inimitable identifiers, and the ability to handover data over a system without necessitating human to humanoid, or human to computer collaboration. However, the security is one of the main concerns in Internet of things, which should be minimized. There are unnecessary requests from the attacker to overload the data center, which results in the hanging of the servers, decreasing the throughput, and requesting a transmission to the Data centers. This paper deals with an efficient approach to decrease the unwanted request at the Data Centers, so that the sessions will be reduced, and the unnecessary load will be reduced on the data centers, in order to mitigate the effect of attack as much as possible.

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Threats identification for the smart Internet of Things in eHealth and adaptive security countermeasures

Cited by 19 publications

References 20 publications

Risk Assessment Methodologies for the Internet of Medical Things: A Survey and Comparative Appraisal

Risk Assessment Methodologies for the Internet of Medical Things: A Survey and Comparative Appraisal

SEC-C-U: The Security of Intensive Care Unit Medical Devices and Their Ecosystems

An Efficient Approach for the Security Threats on Data Centers in IOT Environment

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