The Source Address Validation Improvement (SAVI) effort aims to complement ingress filtering with finer-grained, standardized IP source address validation. This document describes threats enabled by IP source address spoofing both in the global and finer-grained context, describes currently available solutions and challenges, and provides a starting point analysis for finer-grained (host granul...

The Source Address Validation Improvement (SAVI) effort aims to complement ingress filtering with finer-grained, standardized IP source address validation. This document describes threats enabled by IP source address spoofing both in the global and finer-grained context, describes currently available solutions and challenges, and provides a starting point analysis for finer-grained (host granul...

Introduction/purpose: The paper provides a review of recent research in the field GPS and ADS-B spoofing. Systems that rely on satellite positioning technology can be targeted by spoofing order to generate incorrect positioning/timing, which is accomplished inserting false signals into "victim's" receiver. Attackers try insert information systems that, for example, provide navigation airplanes ...

Any biometric recognizer is vulnerable to spoofing attacks and hence voice biometric, also called automatic speaker verification (ASV), is no exception; replay, synthesis and conversion attacks all provoke false acceptances unless countermeasures are used. We focus on voice conversion (VC) attacks considered as one of the most challenging for modern recognition systems. To detect spoofing, most...

A speaker verification system should include effective precautions against malicious spoofing attacks, and although some initial countermeasures have been recently proposed, this remains a challenging research problem. This paper investigates discrimination between spoofed and genuine speech, as a function of frequency bands, across the speech bandwidth. Findings from our investigation inform s...

Face anti-spoofing (FAS) approaches based on unsupervised domain adaption (UDA) have drawn growing attention due to promising performances for target scenarios. Most existing UDA FAS methods typically fit the trained models via aligning distribution of semantic high-level features. However, insufficient supervision unlabeled domains and neglect low-level feature alignment degrade methods. To ad...