Adaptive Cyber Deception: Cognitively Informed Signaling for Cyber Defense

This paper improves upon recent game-theoretic deceptive signaling schemes for cyber defense using the insights emerging from a cognitive model of human cognition. One particular defense allocation algorithm that uses a deceptive signaling scheme is the peSSE (Xu et al., 2015). However, this static signaling scheme optimizes the rate of deception for perfectly rational adversaries and is not personalized to individuals. Here we advance this research by developing a dynamic and personalized signaling scheme using cognitive modeling. A cognitive model based on a theory of experiential-choice (Instance-Based Learning Theory; IBLT), implemented in a cognitive architecture (Adaptive Control of Thought – Rational; ACT-R), and validated using human experimentation with deceptive signals informs the development of a cognitive signaling scheme. The predictions of the cognitive model show that the proposed solution increases the compliance to deceptive signals beyond the peSSE. These predictions were verified in human experiments, and the results shed additional light on human reactions towards adaptive deceptive signals

Cognitive Disability Aesthetics

Cognitive Disability Aesthetics explores the invisibility of cognitive disability in theoretical, historical, social, and cultural contexts. Fraser’s cutting edge research and analysis signals a second-wave in disability studies that prioritizes cognition. He expands upon previous research into physical disability representations and focuses on those disabilities that tend to be least visible in society (autism, Down syndrome, Alzheimer's disease, schizophrenia). Moving beyond established literary approaches analyzing prose representations of disability, the book explores how iconic and indexical modes of signification operate in visual texts. Cognitive Disability Aesthetics successfully reconfigures disability studies in the humanities and exposes the chasm that exists between Anglophone disability studies and disability studies in the Hispanic world

Blind Symbol Rate Estimation of Faster-than-Nyquist Signals Based on Higher-Order Statistics

Both faster-than-Nyquist (FTN) and cognitive radio go towards an efficient use of spectrum in radio communications systems at the cost of an added computational complexity at the receiver side. To gain the maximum potential from these techniques, non-data-aided receivers are of interest. In this paper, we use fourth-order statistics to perform blind symbol rate estimation of FTN signals. The estimator shows good performance results for moderate system's densities beyond the Nyquist rate and for a reasonable number of received samples

Reaching with the sixth sense: Vestibular contributions to voluntary motor control in the human right parietal cortex

The vestibular system constitutes the silent sixth sense: It automatically triggers a variety of vital reflexes to maintain postural and visual stability. Beyond their role in reflexive behavior, vestibular afferents contribute to several perceptual and cognitive functions and also support voluntary control of movements by complementing the other senses to accomplish the movement goal. Investigations into the neural correlates of vestibular contribution to voluntary action in humans are challenging and have progressed far less than research on corresponding visual and proprioceptive involvement. Here, we demonstrate for the first time with event-related TMS that the posterior part of the right medial intraparietal sulcus processes vestibular signals during a goal-directed reaching task with the dominant right hand. This finding suggests a qualitative difference between the processing of vestibular vs. visual and proprioceptive signals for controlling voluntary movements, which are pre-dominantly processed in the left posterior parietal cortex. Furthermore, this study reveals a neural pathway for vestibular input that might be distinct from the processing for reflexive or cognitive functions, and opens a window into their investigation in humans

A hybrid systems model for supervisory cognitive state identification and estimation in neural prosthetics

This paper presents a method to identify a class of hybrid system models that arise in cognitive neural prosthetic medical devices that aim to help the severely handicapped. In such systems a “supervisory decoder” is required to classify the activity of multi-unit extracellular neural recordings into a discrete set of modes that model the evolution of the brain’s planning process. We introduce a Gibbs sampling method to identify the key parameters of a GLHMM, a hybrid dynamical system that combines a set of generalized linear models (GLM) for dynamics of neuronal signals with a hidden Markov model (HMM) that describes the discrete transitions between the brain’s cognitive or planning states. Multiple neural signals of mixed type, including local field potentials and spike arrival times, are integrated into the model using the GLM framework. The identified model can then be used as the basis for the supervisory decoding (or estimation) of the current cognitive or planning state. The identification algorithm is applied to extracellular neural recordings obtained from set of electrodes acutely implanted in the posterior parietal cortex of a rhesus monkey. The results demonstrate the ability to accurately decode changes in behavioral or cognitive state during reaching tasks, even when the model parameters are identified from small data sets. The GLHMM models and the associated identification methods are generally applicable beyond the neural application domain

Outage Analysis for SWIPT-Enabled Two-Way Cognitive Cooperative Communications

In this paper, we study a cooperative cognitive radio network (CCRN) where the secondary user-transmitter (SU-Tx) assists bi-directional communication between a pair of primary users (PUs) following the principle of two-way relaying. In return, it gets access to the spectrum of the PUs to enable its own transmission to SU-receiver (SU-Rx). Further, in order to support sustainable operation of the network, SU-Tx is assumed to harvest energy from the RF signals received from the PUs, using the technique of simultaneous wireless information and power transfer (SWIPT). Assuming a decode-and-forward behaviour and power-splitting based relaying protocol at SU-Tx, closed form expressions for outage probability of PU and SU are obtained. Simulation results validate our analytical results and illustrate spectrum-efficiency and energy-efficiency advantages of the proposed system over one-way relaying.Comment: 15 pages, 5 figures, Submitted to IEEE Transactions on Vehicular Technolog

Outage Analysis for SWIPT-Enabled Two-Way Cognitive Cooperative Communications

In this paper, we study a cooperative cognitive radio network (CCRN) where the secondary user-transmitter (SU-Tx) assists bi-directional communication between a pair of primary users (PUs) following the principle of two-way relaying. In return, it gets access to the spectrum of the PUs to enable its own transmission to SU-receiver (SU-Rx). Further, in order to support sustainable operation of the network, SU-Tx is assumed to harvest energy from the RF signals received from the PUs, using the technique of simultaneous wireless information and power transfer (SWIPT). Assuming a decode-and-forward behaviour and power-splitting based relaying protocol at SU-Tx, closed form expressions for outage probability of PU and SU are obtained. Simulation results validate our analytical results and illustrate spectrum-efficiency and energy-efficiency advantages of the proposed system over one-way relaying.Comment: 15 pages, 5 figures, Submitted to IEEE Transactions on Vehicular Technolog

A Model of Emotion as Patterned Metacontrol

Adaptive systems use feedback as a key strategy to cope with uncertainty and change in their environments. The information fed back from the sensorimotor loop into the control architecture can be used to change different elements of the controller at four different levels: parameters of the control model, the control model itself, the functional organization of the agent and the functional components of the agent. The complexity of such a space of potential configurations is daunting. The only viable alternative for the agent ?in practical, economical, evolutionary terms? is the reduction of the dimensionality of the configuration space. This reduction is achieved both by functionalisation —or, to be more precise, by interface minimization— and by patterning, i.e. the selection among a predefined set of organisational configurations. This last analysis let us state the central problem of how autonomy emerges from the integration of the cognitive, emotional and autonomic systems in strict functional terms: autonomy is achieved by the closure of functional dependency. In this paper we will show a general model of how the emotional biological systems operate following this theoretical analysis and how this model is also of applicability to a wide spectrum of artificial systems