97 research outputs found
Uncovering the Deceptions: An Analysis on Audio Spoofing Detection and Future Prospects
Audio has become an increasingly crucial biometric modality due to its
ability to provide an intuitive way for humans to interact with machines. It is
currently being used for a range of applications, including person
authentication to banking to virtual assistants. Research has shown that these
systems are also susceptible to spoofing and attacks. Therefore, protecting
audio processing systems against fraudulent activities, such as identity theft,
financial fraud, and spreading misinformation, is of paramount importance. This
paper reviews the current state-of-the-art techniques for detecting audio
spoofing and discusses the current challenges along with open research
problems. The paper further highlights the importance of considering the
ethical and privacy implications of audio spoofing detection systems. Lastly,
the work aims to accentuate the need for building more robust and generalizable
methods, the integration of automatic speaker verification and countermeasure
systems, and better evaluation protocols.Comment: Accepted in IJCAI 202
Security and Privacy Problems in Voice Assistant Applications: A Survey
Voice assistant applications have become omniscient nowadays. Two models that
provide the two most important functions for real-life applications (i.e.,
Google Home, Amazon Alexa, Siri, etc.) are Automatic Speech Recognition (ASR)
models and Speaker Identification (SI) models. According to recent studies,
security and privacy threats have also emerged with the rapid development of
the Internet of Things (IoT). The security issues researched include attack
techniques toward machine learning models and other hardware components widely
used in voice assistant applications. The privacy issues include technical-wise
information stealing and policy-wise privacy breaches. The voice assistant
application takes a steadily growing market share every year, but their privacy
and security issues never stopped causing huge economic losses and endangering
users' personal sensitive information. Thus, it is important to have a
comprehensive survey to outline the categorization of the current research
regarding the security and privacy problems of voice assistant applications.
This paper concludes and assesses five kinds of security attacks and three
types of privacy threats in the papers published in the top-tier conferences of
cyber security and voice domain.Comment: 5 figure
Biometric antispoofing methods: A survey in face recognition
Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. J. Galbally, S. Marcel and J. Fierrez, "Biometric Antispoofing Methods", IEEE Access, vol.2, pp. 1530-1552, Dec. 2014In recent decades, we have witnessed the evolution of biometric technology from the rst
pioneering works in face and voice recognition to the current state of development wherein a wide spectrum
of highly accurate systems may be found, ranging from largely deployed modalities, such as ngerprint,
face, or iris, to more marginal ones, such as signature or hand. This path of technological evolution has
naturally led to a critical issue that has only started to be addressed recently: the resistance of this rapidly
emerging technology to external attacks and, in particular, to spoo ng. Spoo ng, referred to by the term
presentation attack in current standards, is a purely biometric vulnerability that is not shared with other
IT security solutions. It refers to the ability to fool a biometric system into recognizing an illegitimate user
as a genuine one by means of presenting a synthetic forged version of the original biometric trait to the sensor.
The entire biometric community, including researchers, developers, standardizing bodies, and vendors, has
thrown itself into the challenging task of proposing and developing ef cient protection methods against this
threat. The goal of this paper is to provide a comprehensive overview on the work that has been carried out
over the last decade in the emerging eld of antispoo ng, with special attention to the mature and largely
deployed face modality. The work covers theories, methodologies, state-of-the-art techniques, and evaluation
databases and also aims at providing an outlook into the future of this very active eld of research.This work was supported in part by the CAM under Project S2009/TIC-1485, in part by the Ministry of Economy and Competitiveness through the Bio-Shield Project under Grant TEC2012-34881, in part by the TABULA RASA Project under Grant FP7-ICT-257289, in part by the BEAT Project under Grant FP7-SEC-284989 through the European Union, and in part by the Cátedra Universidad Autónoma de Madrid-Telefónica
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