Search: “tf-idf”

On Identifying Adversarial Intent Injection in AI-Native 6G Networks

Dual-path CNN and AutoEncoder framework detects adversarial intent injection in AI-native 6G networks, reaching 0.97 accuracy and 0.98 F1.

The paper defines a fine-grained threat model for adversarial intent injection in AI-native 6G intent-based networking, where malicious policies are disguised within benign intent flows. It evaluates four injection strategies: stealth-mode, random distribution, increasing frequency, and decreasing frequency. A dual-path detection framework combines a CNN using TF-IDF features for supervised detection with an AutoEncoder trained only on benign data for one-class detection, reaching 0.97 accuracy and 0.98 F1-score, roughly 9% and 36% gains over the state-of-the-art baseline.

arXiv cs.CR·Sep 10, 19:23 UTC · 5d agoResearch

MemSentry: A Framework for Detecting Persistent Memory Poisoning in Agentic AI

MemSentry intercepts persistent-memory writes in agentic AI to catch memory poisoning, reaching 91.7% accuracy with SBERT+LR classification.

Memory poisoning lets adversaries plant crafted content in an agent's long-term memory to suppress security alerts, enable privilege escalation, or override policies without modifying model weights or system prompts. The paper presents MemSentry, a configuration-driven framework that evaluates proposed persistent-memory writes on source trust, semantic risk, attack radius over a dependency DAG, access risk, and a signed security-state delta to issue deterministic Accept, Review, or Quarantine decisions. Across 1,000 GPT-4-generated scenarios on a 20-asset dependency DAG, SBERT+LR achieved 91.7% accuracy and 0.908 macro-F1, all four classifiers detected 100% of external quarantine-class threats, and verified-insider writes are escalated for human review rather than auto-quarantined.

arXiv cs.CR·Sep 8, 13:40 UTC · 7d agoAI safety & security

Talos Targets Disinformation with Fake News Challenge Victory

Cisco Talos·Jun 20, 17:22 UTC · Jun 20, 2017Threat actor