Detecting denial of sleep attacks by analysis of wireless sensor networks and the Internet of Things
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2023.14.4.52Keywords:
Denial of service, Denial of sleep, Internet of Things, Wake-up radio, Network security, Wireless sensor networks, AODV protocol.Dimensions Badge
Issue
Section
License
Copyright (c) 2023 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The Internet of Things (IoT) amalgamates a large number of physical objects that are distinctively identified, ubiquitously interconnected and accessible through the Internet. IoT endeavors to renovate any object in the real world into a computing device that has sensing, communicating, computing and control capabilities. There are a budding number of IoT devices and applications and this escort to an increase in the number and complexity of malicious attacks. It is important to defend IoT systems against malicious attacks, especially to prevent attackers from acquiring control over the devices. Energy utilization is significant for battery-enabled devices in the IoT and wireless sensor networks which are operated long time period. The Denial-of-Sleep attack is an explicit type of denial-of-service attack that beleaguered a battery-powered device’s power supply that results in the exhaustion of this critical resource. This paper focuses on the survey on Denial of sleep attacks in Wireless Sensor networks and the IoT.Abstract
How to Cite
Downloads
Similar Articles
- Bratati Dey, Poonam Sharma, A comprehensive review of urban growth studies and predictions using the Sleuth model , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Krishna P. Kalyanathaya, Krishna Prasad K, A framework for generating explanations of machine learning models in Fintech industry , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Kakali Ghosh, Rajeshwar Mukherjee, Avasthātraya: Deeper insights , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Tara K. Sharma, Problems and prospects of tourism financing in Sikkim , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- Aditi Sharma, Atal Bihari Bajpai, Naina Srivastava, Yunus Ali, Anjali Thapa, Naveen Gaurav, Arun Kumar, Effect of Growth Regulators and in vitro Clonal Propagation of Adhatoda vasica , The Scientific Temper: Vol. 13 No. 01 (2022): The Scientific Temper
- Jasleen Kaur, Sultan Singh, Assessing the Impact of Stress on the Health and Job Performance of Employees in Indian Banks , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- S. Vanaja, Hari Ganesh S, Application of data mining and machine learning approaches in the prediction of heart disease – A literature survey , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Engida Admassu, Classifying enset based on their disease tolerance using deep learning , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- D. Jayadurga, A. Chandrabose, Expanding the quantity of virtual machines utilized within an open-source cloud infrastructure , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Sheena Edavalath, Manikandasaran S. Sundaram, MARCR: Method of allocating resources based on cost of the resources in a heterogeneous cloud environment , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
<< < 18 19 20 21 22 23 24 25 26 > >>
You may also start an advanced similarity search for this article.

