ESPRESSO achieves over 0.99 true positive rate at 10^{-3} false positive rate for stepping-stone intrusion detection on synthetic data for SSH, SOCAT, ICMP, DNS and mixed protocols, outperforming DeepCoFFEA while also enabling chain length prediction.
Finn: Fingerprinting network flows using neural networks
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VFEFL introduces a CC-DVFE scheme and robust aggregation to achieve privacy-preserving federated learning with malicious client detection without dual-server or trusted-party assumptions.
Reddit data analysis shows reply-based mobile scams growing nearly twice as fast as click-based ones while evading commercial and open-source detectors.
citing papers explorer
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Tracing the Chain: Deep Learning for Stepping-Stone Intrusion Detection
ESPRESSO achieves over 0.99 true positive rate at 10^{-3} false positive rate for stepping-stone intrusion detection on synthetic data for SSH, SOCAT, ICMP, DNS and mixed protocols, outperforming DeepCoFFEA while also enabling chain length prediction.
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VFEFL: Privacy-Preserving Federated Learning against Malicious Clients via Verifiable Functional Encryption
VFEFL introduces a CC-DVFE scheme and robust aggregation to achieve privacy-preserving federated learning with malicious client detection without dual-server or trusted-party assumptions.
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Read This Paper to Get $50 Million:* An Analysis of Mobile Messaging Scams Using Reddit Data
Reddit data analysis shows reply-based mobile scams growing nearly twice as fast as click-based ones while evading commercial and open-source detectors.