A Decision-centric approach for secure and energy-efficient cyber-physical systems

Jithish, J.; Sankaran, Sriram; Achuthan, Krishnashree

doi:10.1007/s12652-020-01995-z

Cited by 10 publications

(5 citation statements)

References 81 publications

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“…When compared to other techniques mutual authentication scheme achieves higher reliability and the elliptical curve cryptographic technique achieves high accuracy in wireless body area networks. 72 DoS Attacks [36] 82 Vulnerable attacks [26] 84 High and low-rate attacks [27] 89…”

Section: Discussionmentioning

confidence: 99%

“…Kong et al [35] suggested smart healthcare systems which promotes communication security in wireless body area networks. Jithish et al [36] discussed the cyber-physical system and used the Markov decision process in wireless body area networks to increase network longevity and energy efficiency, as well as to defend against denial of service and deception attacks.…”

Section: Different Security Aspects Of Secure Wbanmentioning

confidence: 99%

“…• Spoofing attacker [57] • Jamming Attack [21] • DoS Attacks [36] • Vulnerable attacks [26] • High and low-rate attacks [27] Figure 7 shows the comparison of attacker detection techniques. Spoofing attacker detection method [57] obtained the 75% of delivery rate after detecting the attacks, Jamming Attack detection method [21] obtained the 72% of the delivery rate, DoS attack detection method obtained 82% of delivery rate, Vulnerable attack detection methods [26] obtained 84% of delivery rate and High and low-rate attack detection method [27] obtained the 89% of delivery rate.…”

Section: Fig 6 Comparison Of Cryptographic Techniquesmentioning

confidence: 99%

“…After summarizing all the above points, this investigation recommends the implementation of body area networks with unmanned aerial vehicles for secure and faster communication. To overcome the limitation of wireless body area networks, the advantage of flying ad hoc networks and flying Jamming Attack [21] DoS Attacks [36] Vulnerable attacks [26] High and low rate attacks [27] Delivery Rate (%) Fig. 7 Comparison of attacker detection techniques Fig.…”

Section: Recommendationmentioning

confidence: 99%

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A Perspective Review of Security Challenges in Body Area Networks for Healthcare Applications

Ananthi

Jose

2021

Int J Wireless Inf Networks

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Body area network (BAN) connects sensors and actuators to the human body in order to collect patient’s information and transmitting it to doctors in a confined space with limited users. wireless body area network (WBAN) is derived from wireless sensor networks (WSN) and enables to transfer of the patient's information with a wide range of communication due to the limitations of the wired body area network. It plays a vital role in healthcare monitoring, healthcare systems, medical field, sports field, and multimedia communication. Sensors and actuators lead to high energy consumption due to their tiny size. WBAN facilitates in securely storing patient information and transmitting it to the doctor without data loss at a specific time. This review examines and summarizes methodological approaches in WBAN relating to security, safety, reliability, and the fastest transmission. Flying body area networks (FBAN) utilizing unmanned aerial vehicles for data transmission are recommended to promote rapid and secure communication in WBAN. FBAN improve the security, scalability, and speed in order to transmit patient’s information to the doctor due to high mobility.

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Section: Discussionmentioning

confidence: 99%

Section: Different Security Aspects Of Secure Wbanmentioning

confidence: 99%

Section: Fig 6 Comparison Of Cryptographic Techniquesmentioning

confidence: 99%

Section: Recommendationmentioning

confidence: 99%

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A Perspective Review of Security Challenges in Body Area Networks for Healthcare Applications

Ananthi

Jose

2021

Int J Wireless Inf Networks

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“…The GPRS satellite signal is weakened as it traverses through the atmosphere, impacted by the reflections, from objects such as tall buildings or large rock surfaces, along its route to reach a vehicle. Hence, the signal's travel time increases, resulting in inaccurate location information in vehicular ad-hoc networks [3].…”

Section: Introductionmentioning

confidence: 99%

Lane clearance approach for emergency vehicles in highways network

Khatri

Mathi

2022

PLoS ONE

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The steady rise in the number of vehicles in modern urban areas and poor conformance to traffic laws (or rules) lead to avoidable commute delays and traffic jams. Also, there is an increased likelihood of road accidents requiring immediate medical attention. Emergency vehicle (EV) service is adversely affected due to the unavailability of the clear lane that supports EVs to get to their endpoint without being delayed along the national highways. Moreover, the EV’s sirens have a limited range, which may fail to reach and notify other vehicular traffic about its mobility promptly. In addition to this range constraint, EVs in motion often lose their communication links while moving from network to network. This paper delineates an approach using the next generation mobile internet protocol, for automated pathway clearance, for EVs. The prototype model of the proposed approach was experimentally designed and implemented. The proposed design concept is validated by performance characterization via numerical analysis.

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Hybrid deep architecture for intrusion detection in cyber‐physical system: An optimization‐based approach

Arumugam,

Paul,

Issac

et al. 2024

Adaptive Control & Signal

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SummaryIntrustion Detection System (IDS) refers to the gear or software that monitors a network or system for malicious activity or policy violations. Periodically, the system records any intrusion action or breach, which frequently modifies the administrator. Cyber Physical System (CPS) is particularly called as networked connected system, in which the system components are spatially distributed and integrated via the communication network. The control mechanism ensures computation significance; however, the system does affect attacks. Researchers are trying to handle this issue via the existing anomaly datasets. In this way, this paper follows an intrusion detection system under three major stages including extraction of features, selection of feature, and detection. The primary stage is the extraction of Statistical features like standard deviation, mean, mode, variance, and median, as well as higher‐order statistical features like moment, percentile, improved correlation, kurtosis, mutual information, skewness, flow‐based features, and information gain‐based features. The curse of dimensionality becomes a significant problem in this scenario, so it is crucial to choose the right features. Improved Linear Discriminant Analysis (LDA) is utilized to choose the right features. The selected features are subjected to a Hybrid classifier for final detection. Here, models like CNN (Convolutional Neural Network) and Bi‐GRU (Bidirectional Gated Recurrent Unit) are combined. A new Bernoulli Map Estimated Arithmetic Optimization Algorithm (BMEAOA) is added to train the system by adjusting the ideal weights of the two classifiers, leading to improved detection outcomes. Ultimately, the effectiveness is assessed in comparison to the other traditional techniques.

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A Decision-centric approach for secure and energy-efficient cyber-physical systems

Cited by 10 publications

References 81 publications

A Perspective Review of Security Challenges in Body Area Networks for Healthcare Applications

A Perspective Review of Security Challenges in Body Area Networks for Healthcare Applications

Lane clearance approach for emergency vehicles in highways network

Hybrid deep architecture for intrusion detection in cyber‐physical system: An optimization‐based approach

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