Cognitive checkpoint: Emerging technologies for biometric-enabled watchlist screening

Abstract

The version in the Kent Academic Repository may differ from the final published version. Users are advised to check http://kar.kent.ac.uk for the status of the paper. Users should always cite the published version of record.

Cognitive Identity Management: Risks, Trust and Decisions using Heterogeneous Sources

“…A cognitive checkpoint is a complex dynamic system with the following elements of a cognitive system [25]: 1) perception-cycle (information gain about the state of identified person), 2) memory distributed across the entire system, 3) attention driven by memory to prioritize the allocation of available resources, and 4) intelligence driven by perception, memory, and attention; its function is to enable the control and decision-making mechanism to identify intelligent choices. These cognitive elements are distributed in the form of a multi-state multi-perception-cycle semi-automated model [62]. In addition, a cognitive checkpoint is a privacy-sensitive model [11], [14].…”

“…Four information sources for machine reasoning at the security checkpoint: biometrics in infrared (3−12µm), audio (70-600 Hz), and visual (400 − 700µm) spectral bands, and UWB radar illumination (3)(4)(5)(6)(7)(8)(9)(10). for children; the pitch, loudness and timbre of a human voice are the main parameters used by an e-interviewer for emotions and deception detection [1], [41], [55] [62]; -Source B: Infrared domain; the human body radiates nonvisible infrared light (3 − 12µm waves) in proportion to its temperature; this band is used for assessment of both cognitive and physical state [43]; -Source C: Visual domain, 400 − 700µm, for authentication and emotional state assessment using face and face expression recognition [31], [32]; -Source D: Radar illumination, 3-10 GHz; certain concealed items can be detected using the Ultra Wide Band (UWB) radar [24], [38].…”

“…3) Machine reasoning is the key operation in these technologies [62]. For example, an insobriety pattern can be reasoned upon analysis of thermal (infrared) measurements of face temperature, as well as body gesture and speech abnormalities.…”

“…We revisit the risk and trust evaluation in complex systems, and define the cognitive security platform for identity management. We deploy a multi-state model of the identity management [62]. The core of the proposed cognitive platform is the novel inference engine.…”

Cognitive Identity Management: Synthetic Data, Risk and Trust

“…A cognitive security checkpoint for identity management is a complex dynamic system [23], [52], [53]. Various performance projections of cognitive checkpoint include security measures, resistance to cyber attacks, public acceptability, depth of embedding in social infrastructure, type of biometric traits, links to forensics [29], intelligent models [25], [26], [28], as well as privacy, risk and trust (R&T) assessments [53], identity disclosure risks [2].…”