An IoT-Based Intrusion Detection System Approach for TCP SYN Attacks
Source abstract
Abstract
The success of Internet of Things (IoT) deployment has emerged important smart applications. These applications are running independently on different platforms, almost everywhere in the world. Internet of Medical Things (IoMT), also referred as the healthcare Internet of Things, is the most widely deployed application against COVID-19 and offering extensive healthcare services that are connected to the healthcare information technologies systems. Indeed, with the impact of the COVID-19 pandemic, a large number of interconnected devices designed to create smart networks. These networks monitor patients from remote locations as well as tracking medication orders. However, IoT may be jeopardized by attacks such as TCP SYN flooding and sinkhole attacks. In this paper, we address the issue of detecting Denial of Service attacks performed by TCP SYN flooding attacker nodes. For this purpose, we develop a new algorithm for Intrusion Detection System (IDS) to detect malicious activities in the Internet of Medical Things. The proposed scheme minimizes as possible the number of attacks to ensure data security, and preserve confidentiality of gathered data. In order to check the viability of our approach, we evaluate analytically and via simulations the performance of our proposed solution under different probability of attacks.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Network Security and Intrusion Detection · IoT and Edge/Fog Computing · Advanced Malware Detection Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (24)
Show source-provided references
1. Internet of medical things (IOMT)-An overview
2. Internet of things (iot) applications to fight against covid-19 pandemic10.1016/j.dsx.2020.04.041 ↗
3. Towards an effective and efficient deep learning model for covid-19 patterns detection in x-ray images
4. Ilog: An intelligent device for automatic food intake monitoring and stress detection in the iomt10.1109/TCE.2020.2976006 ↗
5. Chinese experts consensus on the internet of things-aided diagnosis and treatment of coronavirus disease 2019 (covid-19)10.1016/j.ceh.2020.03.001 ↗
6. A joint deep learning and internet of medical things driven framework for elderly patients10.1109/ACCESS.2020.2989143 ↗
7. Security attacks and secure routing protocols in rpl-based internet of things: Survey
8. R. Alexander, A. Brandt, J. Vasseur, J. Hui, K. Pister et al. “RPL: IPv6 routing protocol for Low-power and lossy networks,” RFC 6550, Mar. 2012.
9. A comparative study of rpl objective functions
10. Using of multiple rpl instances for enhancing the performance of iot-based systems
11. Routing protocol of low-power and lossy network: Survey and open issues
12. An intrusion detection system on ping of death attacks in iot networks
13. A survey: Attacks on rpl and 6lowpan in iot
14. Design of complex event-processing ids in internet of things
15. A malicious pattern detection engine for embedded security systems in the internet of things10.3390/s141224188 ↗
16. Research on immunity-based intrusion detection technology for the internet of things
17. Svelte: Real-time intrusion detection in the internet of things10.1016/j.adhoc.2013.04.014 ↗
18. 6lowpan: A study on qos security threats and countermeasures using intrusion detection system approach10.1002/dac.2356 ↗
19. Le · IFIP Wireless Days (WD) · 2011 · 1
20. Energy efficient hybrid intrusion detection system for wireless sensor networks
21. An experimental study of hierarchical intrusion detection for wireless industrial sensor networks10.1109/TII.2010.2051556 ↗
22. A signature-based intrusion detection system for the internet of things
23. Kalis—A system for knowledge-driven adaptable intrusion detection for the internet of things
24. Role of iot to avoid spreading of covid-1910.1016/j.ijin.2020.05.002 ↗