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Seeing the Forest for the Trees: Understanding Security Hazards in the 3GPP Ecosystem through Intelligent Analysis on Change Requests.

, , , , , , , and . USENIX Security Symposium, page 17-34. USENIX Association, (2022)

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Self-paced and Reweighting PU Learning for Imbalanced Malicious Traffic Detection., , , and . GLOBECOM, page 6018-6023. IEEE, (2023)M3F: A novel multi-session and multi-protocol based malware traffic fingerprinting., , , , , and . Comput. Networks, (May 2023)Analysis of the performance and robustness of methods to detect base locations of individuals with geo-tagged social media data., , , , , and . Int. J. Geogr. Inf. Sci., 35 (3): 609-627 (2021)DeepGFL: Deep Feature Learning via Graph for Attack Detection on Flow-Based Network Traffic., , and . MILCOM, page 579-584. IEEE, (2018)Towards Comprehensive Detection of DNS Tunnels., , , , , and . ISCC, page 1-7. IEEE, (2020)Sherlock on Specs: Building LTE Conformance Tests through Automated Reasoning., , , , , , , and . USENIX Security Symposium, page 3529-3545. USENIX Association, (2023)Understanding the Influence of Graph Kernels on Deep Learning Architecture: A Case Study of Flow-Based Network Attack Detection., , , and . TrustCom/BigDataSE, page 312-318. IEEE, (2019)Marrying Graph Kernel with Deep Neural Network: A Case Study for Network Anomaly Detection., , , , and . ICCS (2), volume 11537 of Lecture Notes in Computer Science, page 102-115. Springer, (2019)Effectiveness Evaluation of Evasion Attack on Encrypted Malicious Traffic Detection., , , , and . WCNC, page 1158-1163. IEEE, (2022)Producing More with Less: A GAN-based Network Attack Detection Approach for Imbalanced Data., , , , , , and . CSCWD, page 384-390. IEEE, (2021)