Conceivable security risks and authentication techniques for smart devices

With the rapidly escalating use of smart devices and fraudulent transaction of users’ data from their devices, efficient and reliable techniques for authentication of the smart devices have become an obligatory issue. This paper reviews the security risks for mobile devices and studies several authentication techniques available for smart devices. The results from field studies enable a comparative evaluation of user-preferred authentication mechanisms and their opinions about reliability, biometric authentication and visual authentication techniques

Ocular attention-sensing interface system

The purpose of the research was to develop an innovative human-computer interface based on eye movement and voice control. By eliminating a manual interface (keyboard, joystick, etc.), OASIS provides a control mechanism that is natural, efficient, accurate, and low in workload

Practical Hidden Voice Attacks against Speech and Speaker Recognition Systems

Voice Processing Systems (VPSes), now widely deployed, have been made significantly more accurate through the application of recent advances in machine learning. However, adversarial machine learning has similarly advanced and has been used to demonstrate that VPSes are vulnerable to the injection of hidden commands - audio obscured by noise that is correctly recognized by a VPS but not by human beings. Such attacks, though, are often highly dependent on white-box knowledge of a specific machine learning model and limited to specific microphones and speakers, making their use across different acoustic hardware platforms (and thus their practicality) limited. In this paper, we break these dependencies and make hidden command attacks more practical through model-agnostic (blackbox) attacks, which exploit knowledge of the signal processing algorithms commonly used by VPSes to generate the data fed into machine learning systems. Specifically, we exploit the fact that multiple source audio samples have similar feature vectors when transformed by acoustic feature extraction algorithms (e.g., FFTs). We develop four classes of perturbations that create unintelligible audio and test them against 12 machine learning models, including 7 proprietary models (e.g., Google Speech API, Bing Speech API, IBM Speech API, Azure Speaker API, etc), and demonstrate successful attacks against all targets. Moreover, we successfully use our maliciously generated audio samples in multiple hardware configurations, demonstrating effectiveness across both models and real systems. In so doing, we demonstrate that domain-specific knowledge of audio signal processing represents a practical means of generating successful hidden voice command attacks

Opportunity Recognition in High Tech and Regulatory Environment: A study of product based Indian Telecom start-ups

Opportunity recognition forms the first step of entrepreneurship. Off late entrepreneurship research has looked at opportunity recognition from varied lenses with entrepreneurial learning forming the core of most scholarly work. However opportunity recognition in high tech sectors is slightly different due to a high component of knowledge intensiveness inherent in such sectors and has been largely ignored in most work. So, we explore a specific high tech sector in the paper to understand and further the existing concepts within opportunity recognition process. We choose the Indian telecom sector as the context of the study and using an inductive case based approach arrive at conceptual combination as the dominant form of idea generation. The regulatory environment was found to acts as an enabler for the new ideas to flourish. We also bring in the idea of dynamic customization as the driving force behind the venture akin to symbiotic relationship present between organisms in the nature.

Emotional Prosody Measurement (EPM): A voice-based evaluation method for psychological therapy effectiveness

The voice embodies three sources of information: speech, the identity, and the emotional state of the speaker (i.e., emotional prosody). The latter feature is resembled by the variability of the F0 (also named fundamental frequency of pitch) (SD F0). To extract this feature, Emotional Prosody Measurement (EPM) was developed, which consists of 1) speech recording, 2) removal of speckle noise, 3) a Fourier Transform to extract the F0-signal, and 4) the determination of SD F0. After a pilot study in which six participants mimicked emotions by their voice, the core experiment was conducted to see whether EPM is successful. Twenty-five patients suffering from a panic disorder with agoraphobia participated. Two methods (storytelling and reliving) were used to trigger anxiety and were compared with comparable but more relaxed conditions. This resulted in a unique database of speech samples that was used to compare the EPM with the Subjective Unit of Distress to validate it as measure for anxiety/stress. The experimental manipulation of anxiety proved to be successful and EPM proved to be a successful evaluation method for psychological therapy effectiveness

Evolution and Competition in the Market for Handheld Computers

Since the early 1990s, electronic organisers or electronic agendas have been evolving towards fully fledged, but miniature, computers. This paper is a case study about this market. Uniquely, and reminiscent of the home computer market in the 1980s, this is a market for personal computers not dominated by Microsoft. Or at least, not yet. In tracking the evolution of this market, the paper points especially to the importance of networking and standardization. The market for handheld computers is a small market, compared to the units shipped in the market for PCs. Nevertheless a surprisingly large number of vendors has been and still is active in this market. During the short history of this market, there have been several periods where technological breakthroughs created expectations of huge growth, with entry by new suppliers as a result. As the dust settled, the losers either changed strategy, or left the market altogether. The paper will argue that standardization and networking are major factors in explaining competitive success and the recent growth of the industry.industrial organization ;

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