The Chronicles of Radio Frequency Fingerprinting

Radio Frequency Fingerprinting RFF has evolved from an early idea for radar emitter identification into a broad research field for wireless device identification and spectrum monitoring for security. Rather than presenting a conventional literature survey, this work provides a critical historical...

A Novel Contrastive Loss for Zero-Day Network Intrusion Detection

Machine learning has achieved state-of-the-art results in network intrusion detection; however, its performance significantly degrades when confronted by a new attack class -- a zero-day attack. In simple terms, classical machine learning-based approaches are adept at identifying attack classes o...

MalRAG: A Retrieval-Augmented LLM Framework for Open-Set Malicious Traffic Identification

Fine-grained identification of IDS-flagged suspicious traffic is crucial in cybersecurity. In practice, cyber threats evolve continuously, making the discovery of novel malicious traffic a critical necessity as well as the identification of known classes. Recent studies have advanced this goal wi...

HyDRA: a Hybrid Dual-Mode Network for Closed- and Open-Set RFFI with Optimized VMD

Device recognition is vital for security in wireless communication systems, particularly for applications like access control. Radio Frequency Fingerprint Identification RFFI offers a non-cryptographic solution by exploiting hardware-induced signal distortions. This paper proposes HyDRA, a Hybrid...

Malware Families Discovery Via Open-Set Recognition on Android Manifest Permissions

Malware are malicious programs that are grouped into families based on their penetration technique, source code, and other characteristics. Classifying malware programs into their respective families is essential for building effective defenses against cyber threats. Machine learning models have ...

ECG Identity Authentication in Open-Set with Multi-Model Pretraining and Self-Constraint Center and Irrelevant Sample Repulsion Learning

Electrocardiogram ECG signal exhibits inherent uniqueness, making it a promising biometric modality for identity authentication. As a result, ECG authentication has gained increasing attention in recent years. However, most existing methods focus primarily on improving authentication accuracy...

aglvq (=1.0.0), beacon-trellis (=0.1.0) +64 more potentially affected by CVE-2020-15205 via tensorflow (=2.1.0)

tensorflow PYPI version =2.1.0 is affected by a known vulnerability. The following packages have a transitive dependency on tensorflow and may be impacted: - aglvq =1.0.0 - beacon-trellis =0.1.0 - biobb-ml =3.0.0, =0.0.1, =0.2.0, =0.0.2, =0.1.0, =1.1.0, =0.2.0rc1, =0.2.0rc3 and more Source cves:...

aglvq (=1.0.0), beacon-trellis (=0.1.0) +64 more potentially affected by CVE-2020-15211 via tensorflow (=2.1.0)

tensorflow PYPI version =2.1.0 is affected by a known vulnerability. The following packages have a transitive dependency on tensorflow and may be impacted: - aglvq =1.0.0 - beacon-trellis =0.1.0 - biobb-ml =3.0.0, =0.0.1, =0.2.0, =0.0.2, =0.1.0, =1.1.0, =0.2.0rc1, =0.2.0rc3 and more Source cves:...

aglvq (=1.0.0), beacon-trellis (=0.1.0) +64 more potentially affected by CVE-2020-15207 via tensorflow (=2.1.0)

tensorflow PYPI version =2.1.0 is affected by a known vulnerability. The following packages have a transitive dependency on tensorflow and may be impacted: - aglvq =1.0.0 - beacon-trellis =0.1.0 - biobb-ml =3.0.0, =0.0.1, =0.2.0, =0.0.2, =0.1.0, =1.1.0, =0.2.0rc1, =0.2.0rc3 and more Source cves:...