Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/16234
Title: WebScreen+: Web Traffic Screening Performance Enhancement with eBPF Filtering
Authors: Hubballi, Neminath
Khandait, Pratibha
Keywords: Deep Packet Inspection;Intrusion Detection;Packet Filtering;Regular Expression
Issue Date: 2025
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Hubballi, N., & Khandait, P. (2025). WebScreen+: Web Traffic Screening Performance Enhancement with eBPF Filtering. 2025 International Conference on Computing, Networking and Communications, ICNC 2025. https://doi.org/10.1109/ICNC64010.2025.10993687
Abstract: Web applications attract different cyber attacks as they often deal with sensitive information like banking transactions. Web Application Firewalls are used to screen incoming requests and detect such attacks. A busy web server may receive large number of requests and hence screening can become performance bottleneck. Our contributions in this paper are two-fold. First, we present a novel Deep Packet Inspection (DPI) based method for detecting attacks against a web server. This method employs attack-specific signatures encoded as regular expressions, enabling precise screening of incoming HTTP requests. We describe an approach to semi-automatically generate these signatures using Jaccard index, which measures the similarity between invariant character sets extracted from known malicious HTTP requests. Second, we filter non-essential traffic at the network interface card level to achieve scalability. We evaluate the effectiveness of both the detection method and performance enhancement strategy rigorously through experiments conducted in a live network environment. © 2025 IEEE.
URI: https://dx.doi.org/10.1109/ICNC64010.2025.10993687
https://dspace.iiti.ac.in:8080/jspui/handle/123456789/16234
Type of Material: Conference Paper
Appears in Collections:Department of Computer Science and Engineering

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