Securing Contrastive mmWave-based Human Activity Recognition against Adversarial Label Flipping
2026-08-06T07:23:25Z•8e46956cfb0340389141a532e23b3cc81acacdbbf88b188e9c9c6e9f1b6f8d12
adversarial-machine-learningamd-sev-snpauthenticationbackdoor-detectionconfidential-computingcritical-infrastructuredata-poisoningfederated-learningiot-intrusion-detectionjailbreakslabel-flippingllm-agentsmultimodal-llm-securityprompt-injectionquantum-key-distributionrefresh-tokensv2x-security
What happened
Collection of recent security research covering adversarial machine learning, poisoning and backdoor detection, prompt injection defenses, LLM and V2X security, critical-infrastructure risk, IoT intrusion detection, confidential computing, quantum-key-distribution monitoring, and refresh-token design. The material is primarily research and defensive in nature; no specific software vulnerabilities or CVEs are identified in the supplied records.
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_cr
- Record identifier
- 8e46956cfb0340389141a532e23b3cc81acacdbbf88b188e9c9c6e9f1b6f8d12
- Enrichment time
- 2026-08-06T07:23:25Z
- AI-assisted enrichment
- Yes
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