Preventive Determination and Avoidance of DDoS Attack with SDN over the IoT Networks
Abstract
The Internet of Things (IoT) is growing increasingly along with the development of security issues. The IoT system is unable in protecting against ransomware and various forms of malicious threats. The way a vast number of IoT devices are treated is uncomfortable and insecure. Security problems have become increasingly important with the spread of IoT devices. The Software-Defined Networking (SDN) paradigm provides a way to control IoT devices securely. For the IoT paradigm, we have suggested a general system for detecting and mitigating Distributed Denial-of-Service (DDoS) attacks using an SDN. The proposed architecture consists of a pool of controllers comprising SDN controllers, IoT gateway-integrated. Also, we have offered an IoT DDoS attack detection and mitigation algorithm attached to the proposed SDN IoT platform. Finally, the proposed algorithm shows the experimental results that have improved performance and the proposed architecture adapts to heterogeneous and fragile devices to enhance IoT security.
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Attacks such as preference, side-channel attack, data duplication using the tag, physical hampering of sensor devices, or sensor tracking may cause issues in the perception layer of IoT-based healthcare.
“Preference, side-channel attack [198], data duplication using the tag, physical hampering of the sensor devices, or sensor tracking are some of the attacks that may cause issues in the perception layer [199].”
From Federated learning-based AI approaches in smart healthcare: Concepts, taxonomies, challenges and open issues (2023) · cites this paper as [198]
In an IoT-based healthcare system, several attacks can hamper the total loss of the system.
“In the IoT-based healthcare system, several attacks can hamper the total loss of the system.”
From Federated learning-based AI approaches in smart healthcare: Concepts, taxonomies, challenges and open issues (2023) · cites this paper as [198]
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- Authors
- Shayshab Azad, K. M., Hossain, N., Islam, M. J., Rahman, A., & Kabir, S.
- Affiliations
- Green University of Bangladesh (BD)
- Venue
- 2021 International Conference on Automation, Control and Mechatronics for Industry 4.0 (ACMI)
- Publisher
- IEEE
- Published
- 2021-07-08
- Pages
- 1-6
- OpenAlex
- W3200968423
- Cited by
- 25
- References
- 18
- Citations by year
- 2026: 1 · 2024: 11 · 2023: 5 · 2022: 6 · 2021: 2
- FWCI
- 5.55
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- International Conference on Automation, Control and Mechatronics for Industry 4.0 (ACMI) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
- Physical Sciences › Computer Science › Computer Networks and Communications › Software-Defined Networks and 5G
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Keywords
- DDoS attack detection, DDoS mitigation, software-defined networking, Internet of Things security, SDN controller, IoT gateway, attack detection algorithm, heterogeneous IoT devices
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