{"data":{"id":"40be6cbb-a7ca-436f-a97b-c8961f16607e","title":"Deep learning-based sequential detection of attacks on low-Latency network services","summary":"This research paper presents a hybrid deep learning method using autoencoders (neural networks that learn to compress and reconstruct data) and transformers (AI models that process sequences of information) to detect a new type of attack called unresponsive ECN attacks on low-latency network services (systems designed to minimize delay in data transmission). The proposed method achieves over 90% accuracy in detecting these attacks while keeping false alarms below 0.01%, outperforming existing detection approaches by more than 10%.","solution":"N/A -- no mitigation discussed in source.","labels":["research","security"],"sourceUrl":"https://www.sciencedirect.com/science/article/pii/S2214212626000888?dgcid=rss_sd_all","publishedAt":"2026-04-08T18:01:15.876Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":["denial_of_service"],"issueType":"research","affectedPackages":null,"affectedVendors":[],"affectedVendorsRaw":[],"classifierModel":"claude-haiku-4-5-20251001","classifierPromptVersion":"v3","cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"patchAvailable":null,"disclosureDate":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["availability"],"aiComponentTargeted":"framework","llmSpecific":false,"classifierConfidence":0.72,"researchCategory":"peer_reviewed","atlasIds":null}}