Context-Aware Automation Based Energy Conservation Techniques for IoT Ecosystem

Mangla, Monika; Akhare, Rakhi; Ambarkar, Smita Sanjay

doi:10.1007/978-981-13-7399-2_6

Cited by 8 publications

(2 citation statements)

References 34 publications

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“…However, the digitization of healthcare comes with the cost of security [5]. In literature, various authors demonstrated the various aspects of the IoT system [6] presented the energyefficient IoT system but lack to provide the security aspect whereas the authors also put forth the theoretical aspects of various RPL attacks [7]. The practical way of attacking is still unrevealed.…”

Section: Related Workmentioning

confidence: 99%

Critical and Comparative Analysis of DoS and Version Number Attack in Healthcare IoT System

Ambarkar

Shekokar

2021

Lecture Notes in Networks and Systems

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Recently the entire world is witnessing the pandemic outbreak of COVID 19, which creates havoc in the healthcare industry. Error tolerance may lead to death threats for the patient in the healthcare system. However, practically the healthcare industry faces many manual error incidences, inadequate staffing, aging population, etc. These challenges will increase the stress level and disturbs the psychological as well as physical health of the healthcare practitioner. Internet of things (IoT) technique is adept to tackle such outbreaks by providing complete digitization of healthcare systems. However, IoT application deployment comes with many security threats and attacks challenges. Here it is worth mentioning that to implement a robust security solution, the comprehensive analysis of attack must carry out. This paper contributes by analyzing two preeminent attacks, the Denial of service (DoS) and version Number attack on the healthcare system. DoS rapidly destroy the network whereas version number haltingly takes control of the network. The paper further critically analyzes the performance and severity of these two attacks based on discrete parameters like routing metric, power consumption, number of packets received, number of expected transmissions, beacon interval, and proposes the robust solution.

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Section: Related Workmentioning

confidence: 99%

Critical and Comparative Analysis of DoS and Version Number Attack in Healthcare IoT System

Ambarkar

Shekokar

2021

Lecture Notes in Networks and Systems

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“…Building automation system (BAS) plays an important role and gains more attention in industrial and personal uses [1][2][3]. Optimal and safe benefits of these systems require a high level of awareness of its integrated resources (i.e., sensors, actuators, or any computing resource) that gain an artificial sensory perception of these buildings and their occupants' behavior s that convert the building into an intelligent ecosystem [4].…”

Section: Introductionmentioning

confidence: 99%

Conflict Detection and Resolution Model for Multi-users IoT Automation Systems

2022

IJIES

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Building automation (BA) strives to control interconnected physical devices by using software management systems on which end-users can personalize their environmental preferences. In large buildings, among the leading causes of IoT apps conflict are the shareable locations/devices amongst residents and the diversity of their preferences. Addressing such conflicts and ensuring the safety of residents are vital requirements in building automation systems. Consequently, the potential of IoT safety and correctness frameworks relies on supporting conflict detection. This paper provides a model for detecting and resolving IoT automation conflicts. These conflicts can result from shareable locations or devices. The proposed model is evaluated using a benchmark dataset and refined scenarios collected from competitor-related works (80+ IoT apps with 117+ rules). The proposed model surpasses state-of-the-art models by covering more conflicts (joint behavior conflict); moreover, it does not require events' chain between IoT apps like other models, one more advantage is that the proposed model uses a filtering process in conflict detection which leads to small detection run-time. Thereby, our proposed model can maximize the correctness and safety of building automation systems.

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Study on Green Cloud Computing—A Review

Meenal

Ankita

2021

Machine Learning Approach for Cloud Data Analytics in IoT

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Context-Aware Automation Based Energy Conservation Techniques for IoT Ecosystem

Cited by 8 publications

References 34 publications

Critical and Comparative Analysis of DoS and Version Number Attack in Healthcare IoT System

Critical and Comparative Analysis of DoS and Version Number Attack in Healthcare IoT System

Conflict Detection and Resolution Model for Multi-users IoT Automation Systems

Study on Green Cloud Computing—A Review

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