Hybrid Feature Selection for Efficient Detection of DDoS Attacks in IoT
Author:
Affiliation:
1. Department of Electrical and Computer Engineering, Tenneessee State University, USA
2. Department of Electrical and Computer Engineering, Tennessee State University, United States
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3556677.3556687
Reference19 articles.
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2. Sonar K. and Upadhyay H. 2014. A survey: DDOS attack on Internet of Things. International Journal of Engineering Research and Development 10(11) pp.58-63.Alsboui T. Qin Y. Hill R. and Al-Aqrabi H. 2020. Enabling distributed intelligence for the Internet of Things with IOTA and mobile agents. Computing 102(6) pp.1345-1363. Sonar K. and Upadhyay H. 2014. A survey: DDOS attack on Internet of Things. International Journal of Engineering Research and Development 10(11) pp.58-63.Alsboui T. Qin Y. Hill R. and Al-Aqrabi H. 2020. Enabling distributed intelligence for the Internet of Things with IOTA and mobile agents. Computing 102(6) pp.1345-1363.
3. Alsboui , T. , Qin , Y. , Hill , R. and Al-Aqrabi , H. , 2020. Enabling distributed intelligence for the Internet of Things with IOTA and mobile agents. Computing, 102(6) , pp. 1345 - 1363 . Alsboui, T., Qin, Y., Hill, R. and Al-Aqrabi, H., 2020. Enabling distributed intelligence for the Internet of Things with IOTA and mobile agents. Computing, 102(6), pp.1345-1363.
4. A DDoS Attack Detection and Mitigation With Software-Defined Internet of Things Framework A DDoS Attack Detection and Mitigation With Software-Defined Internet of Things Framework
5. Wehbi K. Hong L. Al-salah T. and Bhutta A.A. 2019 April. A survey on machine learning based detection on DDoS attacks for IoT systems. In 2019 SoutheastCon (pp. 1-6). IEEE. Wehbi K. Hong L. Al-salah T. and Bhutta A.A. 2019 April. A survey on machine learning based detection on DDoS attacks for IoT systems. In 2019 SoutheastCon (pp. 1-6). IEEE.
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