Intelligent and Dynamic Ransomware Spread Detection and Mitigation in Integrated Clinical Environments

Maimó, Lorenzo Fernández; Celdrán, Alberto Huertas; Gómez, Ángel Luis Perales; Clemente, Félix J. García; Weimer, James; Lee, Insup

doi:10.3390/s19051114

Cited by 72 publications

(44 citation statements)

References 36 publications

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“…In this dramatic scenario, the authors of [10] identified critical shortcomings of ICE in challenging scenarios such as security, quality of service (QoS), and high availability. To improve the previous aspects, the authors of [11] presented an architecture, called ICE++, for the MEC paradigm that combined SDN/NFV. As an extension of ICE++, proposed ML-based solution able to classify several well-known families of ransomware affecting the medical devices of ICE.…”

Section: Cybersecurity In Icementioning

confidence: 99%

Detecting and mitigating cyberattacks using software defined networks for integrated clinical environments

Celdrán

Karmakar

Mármol

et al. 2021

Peer-to-Peer Netw. Appl.

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The evolution of integrated clinical environments (ICE) and the future generations of mobile networks brings to reality the hospitals of the future and their innovative clinical scenarios. The mobile edge computing paradigm together with network function virtualization techniques and the software-defined networking paradigm enable self-management, adaptability, and security of medical devices and data management processes making up clinical environments. However, the logical centralized approach of the SDN control plane and its protocols introduce new vulnerabilities which affect the security of the network infrastructure and the patients’ safety. The paper at hand proposes an SDN/NFV-based architecture for the mobile edge computing infrastructure to detect and mitigate cybersecurity attacks exploiting SDN vulnerabilities of ICE in real time and on-demand. A motivating example and experiments presented in this paper demonstrate the feasibility of of the proposed architecture in a realistic clinical scenario.

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Section: Cybersecurity In Icementioning

confidence: 99%

Detecting and mitigating cyberattacks using software defined networks for integrated clinical environments

Celdrán

Karmakar

Mármol

et al. 2021

Peer-to-Peer Netw. Appl.

Self Cite

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“…Moreover, ML based malware detection methods were discussed. Furthermore, Fernandez Maimo et al (Fernandez Maimo et al 2019) used ML techniques for detecting and classifying ransomware attacks in ICE. The NFV/SDN methods were used to isolate and remove contaminated medical equipment and networks.…”

Section: Tablementioning

confidence: 99%

Peer Review #3 of "A systematic review of security and privacy issues in the internet of medical things; the role of machine learning approaches (v0.1)"

2021

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Background . The Internet of Medical Things (IoMTs) is gradually replacing the traditional healthcare system. However, little attention has been paid to their security requirements in the development of the IoMT devices and systems. One of the main reasons can be the difficulty of tuning conventional security solutions to the IoMT system. Machine Learning (ML) has been successfully employed in the attack detection and mitigation process. Advanced ML technique can also be a promising approach to address the existing and anticipated IoMT security and privacy issues. However, because of the existing challenges of IoMT system, it is imperative to know how these techniques can be effectively utilized to meet the security and privacy requirements without affecting the IoMT systems quality, services, and device's lifespan.Methodology. This paper is devoted to perform a Systematic Literature Review (SLR) on the security and privacy issues of IoMT and their solutions by ML techniques. The recent research papers disseminated between 2010 to 2020 are selected from multiple databases and a standardized SLR method is conducted. A total of 153 papers were reviewed and a critical analysis were conducted on the selected papers. Furthermore, this review study attempts to highlight the limitation of the current methods and aims to find possible solutions to them. Thus, a detailed analysis was carried out on the selected papers through focusing on their methods, advantages, limitations, the utilized tools, and data. Results.It was observed that ML techniques have been significantly deployed for device and network layer security. Most of the current studies improved traditional metrics while ignored performance complexity metrics in their evaluations. Their studies environments and utilized data barely represent IoMT system. Therefore, conventional ML techniques may fail if metrics such as resource complexity and power usage are not considered.

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“…IoT and CC are service computing platforms that allow object interconnection, including personal and sensitive data, over wireless channels [29,30,31]. The collective data of physical objects or sensors is generally stored on a cloud-server [32,33,34,35].…”

Section: System Modelsmentioning

confidence: 99%

A Hash-Based RFID Authentication Mechanism for Context-Aware Management in IoT-Based Multimedia Systems

Deebak

Al‐Turjman

Mostarda

2019

Sensors

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With the technological advances in the areas of Machine-To-Machine (M2M) and Device-To-Device (D2D) communication, various smart computing devices now integrate a set of multimedia sensors such as accelerometers, barometers, cameras, fingerprint sensors, gestures, iris scanners, etc., to infer the environmental status. These devices are generally identified using radio-frequency identification (RFID) to transfer the collected data to other local or remote objects over a geographical location. To enable automatic data collection and transition, a valid RFID embedded object is highly recommended. It is used to authorize the devices at various communication phases. In smart application devices, RFID-based authentication is enabled to provide short-range operation. On the other hand, it does not require the communication device to be in line-of-sight to gain server access like bar-code systems. However, in existing authentication schemes, an adversary may capture private user data to create a forgery problem. Also, another issue is the high computation cost. Thus, several studies have addressed the usage of context-aware authentication schemes for multimedia device management systems. The security objective is to determine the user authenticity in order to withhold the eavesdropping and tracing. Lately, RFID has played a significant for the context-aware sensor management systems (CASMS) as it can reduce the complexity of the sensor systems, it can be available in access control, sensor monitoring, real time inventory and security-aware management systems. Lately, this technology has opened up its wings for CASMS, where the challenging issues are tag-anonymity, mutual authentication and untraceability. Thus, this paper proposes a secure hash-based RFID mechanism for CASMS. This proposed protocol is based on the hash operation with the synchronized secret session-key to withstand any attacks, such as desynchronization, replay and man-in-the-middle. Importantly, the security and performance analysis proves that the proposed hash-based protocol achieves better security and performance efficiencies than other related schemes. From the simulation results, it is observed that the proposed scheme is secure, robust and less expensive while achieving better communication metrics such as packet delivery ratio, end-to-end delay and throughput rate.

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Intelligent and Dynamic Ransomware Spread Detection and Mitigation in Integrated Clinical Environments

Cited by 72 publications

References 36 publications

Detecting and mitigating cyberattacks using software defined networks for integrated clinical environments

Detecting and mitigating cyberattacks using software defined networks for integrated clinical environments

Peer Review #3 of "A systematic review of security and privacy issues in the internet of medical things; the role of machine learning approaches (v0.1)"

A Hash-Based RFID Authentication Mechanism for Context-Aware Management in IoT-Based Multimedia Systems

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