400 research outputs found
Security in transnational interoperable PPDR communications: threats and requirements
The relevance of cross border security operations
has been identified as a priority at European level for a long time.
A European network where Public Protection and Disaster Relief
(PPDR) forces share communications processes and a legal
framework would greatly enforce response to disaster recovery
and security against crime. Nevertheless, uncertainty on costs,
timescale and functionalities have slowed down the
interconnection of PPDR networks across countries and limited
the transnational cooperation of their PPDR forces so far. In this
context, the European research project ISITEP is aimed at
developing the legal, operational and technical framework to
achieve a cost effective solution for PPDR interoperability across
European countries. Inter alia, ISITEP project is specifying a
new Inter-System-Interface (ISI) interface for the
interconnection of current TETRA and TETRAPOL networks
that can be deployed over Internet Protocol (IP) connectivity.
This approach turns communications security as a central aspect
to consider when deploying the new IP ISI protocol between
PPDR national networks. Ensuring that threats to the
interconnected communications systems and terminals are
sufficiently and appropriately reduced by technical, procedural
and environmental countermeasures is vital to realise the trusted
and secure communication system needed for the pursued PPDR
transnational cooperation activities. In this context, this paper
describes the framework and methodology defined to carry out
the development of the security requirements and provides a
discussion on the undertaken security risk and vulnerability
analysis.Peer ReviewedPostprint (author's final draft
Protecting Voice Controlled Systems Using Sound Source Identification Based on Acoustic Cues
Over the last few years, a rapidly increasing number of Internet-of-Things
(IoT) systems that adopt voice as the primary user input have emerged. These
systems have been shown to be vulnerable to various types of voice spoofing
attacks. Existing defense techniques can usually only protect from a specific
type of attack or require an additional authentication step that involves
another device. Such defense strategies are either not strong enough or lower
the usability of the system. Based on the fact that legitimate voice commands
should only come from humans rather than a playback device, we propose a novel
defense strategy that is able to detect the sound source of a voice command
based on its acoustic features. The proposed defense strategy does not require
any information other than the voice command itself and can protect a system
from multiple types of spoofing attacks. Our proof-of-concept experiments
verify the feasibility and effectiveness of this defense strategy.Comment: Proceedings of the 27th International Conference on Computer
Communications and Networks (ICCCN), Hangzhou, China, July-August 2018. arXiv
admin note: text overlap with arXiv:1803.0915
High-Performance Fake Voice Detection on Automatic Speaker Verification Systems for the Prevention of Cyber Fraud with Convolutional Neural Networks
This study proposes a highly effective data analytics approach to prevent cyber fraud on automatic speaker verification systems by classifying histograms of genuine and spoofed voice recordings. Our deep learning-based lightweight architecture advances the application of fake voice detection on embedded systems. It sets a new benchmark with a balanced accuracy of 95.64% and an equal error rate of 4.43%, contributing to adopting artificial intelligence technologies in organizational systems and technologies. As fake voice-related fraud causes monetary damage and serious privacy concerns for various applications, our approach improves the security of such services, being of high practical relevance. Furthermore, the post-hoc analysis of our results reveals that our model confirms image texture analysis-related findings of prior studies and discovers further voice signal features (i.e., textural and contextual) that can advance future work in this field
Smart Home Personal Assistants: A Security and Privacy Review
Smart Home Personal Assistants (SPA) are an emerging innovation that is
changing the way in which home users interact with the technology. However,
there are a number of elements that expose these systems to various risks: i)
the open nature of the voice channel they use, ii) the complexity of their
architecture, iii) the AI features they rely on, and iv) their use of a
wide-range of underlying technologies. This paper presents an in-depth review
of the security and privacy issues in SPA, categorizing the most important
attack vectors and their countermeasures. Based on this, we discuss open
research challenges that can help steer the community to tackle and address
current security and privacy issues in SPA. One of our key findings is that
even though the attack surface of SPA is conspicuously broad and there has been
a significant amount of recent research efforts in this area, research has so
far focused on a small part of the attack surface, particularly on issues
related to the interaction between the user and the SPA devices. We also point
out that further research is needed to tackle issues related to authorization,
speech recognition or profiling, to name a few. To the best of our knowledge,
this is the first article to conduct such a comprehensive review and
characterization of the security and privacy issues and countermeasures of SPA.Comment: Accepted for publication in ACM Computing Survey
Smart home personal assistants : a security and privacy review
Smart Home Personal Assistants (SPA) are an emerging innovation that is changing the means by which home users interact with technology. However, several elements expose these systems to various risks: i) the open nature of the voice channel they use, ii) the complexity of their architecture, iii) the AI features they rely on, and iv) their use of a wide range of underlying technologies. This paper presents an in-depth review of SPA’s security and privacy issues, categorizing the most important attack vectors and their countermeasures. Based on this, we discuss open research challenges that can help steer the community to tackle and address current security and privacy issues in SPA. One of our key findings is that even though the attack surface of SPA is conspicuously broad and there has been a significant amount of recent research efforts in this area, research has so far focused on a small part of the attack surface, particularly on issues related to the interaction between the user and the SPA devices. To the best of our knowledge, this is the first article to conduct such a comprehensive review and characterization of the security and privacy issues and countermeasures of SPA
Security Frameworks for Machine-to-Machine Devices and Networks
Attacks against mobile systems have escalated over the past decade. There have been increases of fraud, platform attacks, and malware. The Internet of Things (IoT) offers a new attack vector for Cybercriminals. M2M contributes to the growing number of devices that use wireless systems for Internet connection. As new applications and platforms are created, old vulnerabilities are transferred to next-generation systems. There is a research gap that exists between the current approaches for security framework development and the understanding of how these new technologies are different and how they are similar. This gap exists because system designers, security architects, and users are not fully aware of security risks and how next-generation devices can jeopardize safety and personal privacy. Current techniques, for developing security requirements, do not adequately consider the use of new technologies, and this weakens countermeasure implementations. These techniques rely on security frameworks for requirements development. These frameworks lack a method for identifying next generation security concerns and processes for comparing, contrasting and evaluating non-human device security protections. This research presents a solution for this problem by offering a novel security framework that is focused on the study of the “functions and capabilities” of M2M devices and improves the systems development life cycle for the overall IoT ecosystem
Project BeARCAT : Baselining, Automation and Response for CAV Testbed Cyber Security : Connected Vehicle & Infrastructure Security Assessment
Connected, software-based systems are a driver in advancing the technology of transportation systems. Advanced automated and autonomous vehicles, together with electrification, will help reduce congestion, accidents and emissions. Meanwhile, vehicle manufacturers see advanced technology as enhancing their products in a competitive market. However, as many decades of using home and enterprise computer systems have shown, connectivity allows a system to become a target for criminal intentions. Cyber-based threats to any system are a problem; in transportation, there is the added safety implication of dealing with moving vehicles and the passengers within
- …