INTEL_REPORT
arXiv — Cryptography & Security (cs.CR) · published 6/17/2026, 4:00:00 AM · TLP amber
Summary
Ingested excerpt (first ~500 chars of normalized text).
Timestamp-Aware Spatio-Temporal Graph Contrastive Learning for Network Intrusion Detection arXiv:2606.17109v1 Announce Type: new Abstract: Given their effectiveness in modeling the relational structure among network traffic flows, graph neural networks (GNNs) have been widely adopted in network intrusion detection systems (NIDSs). However, most existing GNN-based NIDS approaches focus on the relational structure of traffic flows, and treat them as temporally independent, whi…
https://arxiv.org/abs/2606.17109
sha256:32135ec44e57696bf5044e3ff3a49c8f3159e2c048c9613101d722470e156d78
What we pulled out
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Indicators
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Malware families
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Threat actors mentioned
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ATT&CK techniques
MITRE IDs referenced in text and present in local technique table.
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