Koosha Sadeghi

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Security systems using brain signals or Electroencephalography (EEG), is an emerging field of research. Brain signal characteristics such as chaotic nature and uniqueness, make it an appropriate information source to be used in security systems. In this paper, E-BIAS, a pervasive EEG-based security system with both identification and authentication(More)
Commercially available wearable brain sensors and devices that convert smartphones into virtual reality systems open up the potential to implement real time collaborative brain-mobile interactive applications. These applications may derive psychological contexts using electroencephalogram (EEG) collected in a wireless setting, and provide individualized(More)
Commercially available wearables and apps that convert mobile devices into data collection hubs can be used to implement smart applications in aware cities. In this paper, we consider wearable devices on various human users as a networked cluster of computing power and information source in an Internet-of-People architecture. Applications can be developed(More)
Pervasive Brain Mobile Interfaces (BMoI) can be made more accurate and time efficient when knowledge from other sensors and computation power from available devices in the Internet of Things (IoT) infrastructure are utilized. This paper takes the example of Neuro-Movie (nMovie), an interactive movie application that blurs movie scenes based on mental state,(More)
Machine learning algorithms are widely used in cyber forensic biometric systems to analyze a subject's truthfulness in an interrogation. An analytical method (rather than experimental) to evaluate the security strength of these systems under potential cyber attacks is essential. In this paper, we formalize a theoretical method for analyzing the immunity of(More)
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