arXiv AI July 14, 2026 By Muhammet Emir Korkmaz, Kemal Bicakci, Yusuf Uzunay

Closing the Loop: An Access-Control Architecture for Automated, Anomaly-Driven Network Revocation in IoT Deployments

arXiv:2607. 11649v1 Announce Type: cross Abstract: Network-based anomaly detection for IoT devices has matured to the point of reporting strong detection accuracy, yet most published systems stop at raising an alert and leave the question of automated enforcement to future work or to a programmable data plane that few real networks operate.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv AI

6d ago

Towards Model-based Run-time Cybersecurity: On Control-Flow Anomaly Detection, Attack Identification, and Hardware Monitoring

arXiv:2608. 11802v1 Announce Type: cross Abstract: Methods to increase the resilience of systems to cyber-attacks become increasingly important.

By Martin Sachenbacher, Martin Leucker, Alexander Weiss, Aliyu Tanko Ali

arXiv Machine Learning

Aug 7

Behavioral Residualization for Unsupervised Intrusion Detection in Automotive CAN Networks

arXiv:2608. 05548v1 Announce Type: cross Abstract: Modern vehicles rely on the Controller Area Network (CAN) bus, whose design prioritizes low cost and real-time performance but provides no message authentication or encryption.

By Chandan Hegde, Mukundh R Reddy

robotics

arXiv Machine Learning

Jun 16

Continual Backdoor Training in IoT/CPS

arXiv:2606. 14987v1 Announce Type: cross Abstract: Internet of Things (IoT) and Cyber-physical systems (CPS) increasingly rely on continual learning (CL) to adapt to evolving environments, device heterogeneity, and concept drift, thereby improving overall utility.

By Oxana Salish, Kuniyilh S

arXiv AI

Jun 18

MIDS: Detecting Stealthy Masquerade and Tampering Attacks on CAN Bus via Bidirectional Mamba

arXiv:2606. 18599v1 Announce Type: cross Abstract: The Controller Area Network (CAN) protocol is the primary communication standard for Electronic Control Units (ECUs) in modern vehicles, but its lack of encryption and authentication exposes it to a range of security threats.

By Qiqi Liu, Runhan Song, Lei Cui, Heng Zhang, Yuyan Sun, Limin Sun

efficiency benchmarks

arXiv Machine Learning

Jul 27

Security Without Detection: Economic Denial as a Primitive for Edge and IoT Defense

arXiv:2512. 23849v2 Announce Type: replace-cross Abstract: Sophisticated attackers can evade detection-based security by using encryption, stealth tactics, and low-rate attack patterns.

By Samaresh Kumar Singh, Joyjit Roy, Sriharsha Anand Pushkala

safety

arXiv AI

Jun 6

DAST: A VLM-LLM Framework for Cross-Interface Anomaly Detection in O-RAN

arXiv:2606. 06261v1 Announce Type: cross Abstract: O-RAN enables a disaggregated baseband stack with programmable functions that communicate over standardized open interfaces.

By Francesco Spinelli, Esteban Municio, Pau Baguer, Gines Garcia-Aviles, Xavier Costa-Perez

llms agents multimodal benchmarks

Related stories

Towards Model-based Run-time Cybersecurity: On Control-Flow Anomaly Detection, Attack Identification, and Hardware Monitoring

Behavioral Residualization for Unsupervised Intrusion Detection in Automotive CAN Networks

Continual Backdoor Training in IoT/CPS

MIDS: Detecting Stealthy Masquerade and Tampering Attacks on CAN Bus via Bidirectional Mamba

Security Without Detection: Economic Denial as a Primitive for Edge and IoT Defense

DAST: A VLM-LLM Framework for Cross-Interface Anomaly Detection in O-RAN