An approach for detecting LDoS attack based on cloud model
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Computer Science,Theoretical Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s11704-022-0486-1.pdf
Reference35 articles.
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2. Wu Z, Li W, Liu L, Yue M. Low-rate DoS attacks, detection, defense, and challenges: a survey. IEEE Access, 2020, 8: 43920–43943
3. Liu Q, Peng Y, Wu J, Wang T, Wang G. Secure multi-keyword fuzzy searches with enhanced service quality in cloud computing. IEEE Transactions on Network and Service Management, 2021, 18(2): 2046–2062
4. Li X, Liu S, Wu F, Kumari S, Rodrigues J J P C. Privacy preserving data aggregation scheme for mobile edge computing assisted IoT applications. IEEE Internet of Things Journal, 2019, 6(3): 4755–4763
5. Liang W, Xiao L, Zhang K, Tang M, He D, Li K C. Data fusion approach for collaborative anomaly intrusion detection in blockchain-based systems. IEEE Internet of Things Journal, 2021
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1. The use of statistical features for low-rate denial-of-service attack detection;Annals of Telecommunications;2024-04-05
2. The Use of Statistical Features for Low-Rate Denial of Service Attack Detection;2023 2nd International Conference on 6G Networking (6GNet);2023-10-18
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