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Opportunistic Piggyback Marking for IP Traceback.

, , , and . IEEE Trans. Inf. Forensics Secur., 11 (2): 273-288 (2016)

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SLIC: Self-Learning Intelligent Classifier for network traffic., , , and . Comput. Networks, (2015)Opportunistic Piggyback Marking for IP Traceback., , , and . IEEE Trans. Inf. Forensics Secur., 11 (2): 273-288 (2016)iPET: Privacy Enhancing Traffic Perturbations for Secure IoT Communications., , , , and . Proc. Priv. Enhancing Technol., 2023 (2): 206-220 (April 2023)Accurate in-network file-type classification., , and . SG-CRC, volume 14 of Cryptology and Information Security Series, page 139-146. IOS Press, (2016)Dynamic embedding of virtual networks in hybrid optical-electrical datacenters., , , and . ICCCN, page 1-8. IEEE, (2014)Detection of Syn Flooding Attacks using Linear Prediction Analysis., , and . ICON, page 1-6. IEEE, (2006)ZEST: Attention-based Zero-Shot Learning for Unseen IoT Device Classification., , , and . CoRR, (2023)Size-Based Flow-Scheduling Using Spike-Detection., , and . ASMTA, volume 6751 of Lecture Notes in Computer Science, page 331-345. Springer, (2011)In-network defense against AR-DDoS attacks., , , and . SIGCOMM Posters and Demos, page 18-20. ACM, (2020)Phishpedia: A Hybrid Deep Learning Based Approach to Visually Identify Phishing Webpages., , , , , , , , and . USENIX Security Symposium, page 3793-3810. USENIX Association, (2021)