Litcius/Paper detail

DistilXIDS: Efficient, lightweight and explainable transformer-based language model for real-time network intrusion detection

Amal Ajayan, G. Kirubavathi, Iqbal H. Sarker

2025Neurocomputing9 citationsDOI

Topics & Concepts

Computer scienceScalabilityIntrusion detection systemInferenceDenial-of-service attackMachine learningArtificial intelligenceFalse positive paradoxAdaptabilityData miningRobustness (evolution)Benchmark (surveying)AutoencoderNetwork securityEncoderAttack patternsReliability (semiconductor)Latency (audio)Class (philosophy)Offset (computer science)TransformerAttack modelFeature (linguistics)SkewDistributed computingAnomaly detectionLanguage modelLow latency (capital markets)Prior probabilityFault toleranceByzantine fault toleranceNetwork Security and Intrusion DetectionAnomaly Detection Techniques and ApplicationsAdvanced Malware Detection Techniques
DistilXIDS: Efficient, lightweight and explainable transformer-based language model for real-time network intrusion detection | Litcius