Adaptive Visualization of Complex Networks with FocalPoint

2016 ◽  
Vol 60 (1) ◽  
pp. 233-237 ◽  
Author(s):  
Catherine Inibhunu ◽  
Scott Langevin
Keyword(s):  
Complex Networks ◽  
Cognitive Load ◽  
Situation Awareness ◽  
Operations Management ◽  
Computational Models ◽  
Situational Awareness ◽  
Computer Network ◽  
Global Network ◽  
Optimum Level ◽  
Information Structures

Maintaining situational awareness of a dynamic global computer network that consists of ten to hundreds of thousands of computers is a complex task for cyber administrators and operators looking to understand, plan and conduct operations in real time. Currently, cyber specialists must manually navigate complex networks by continuous cycles of overviews, drilldowns and manually mapping network incidents to mission impact. This is inefficient as manually maneuvering of network data is laborious, induces cognitive overload, and is prone to errors caused by distractive information resulting in important information and impacts not being seen. We are investigating “FocalPoint” an adaptive level of detail (LOD) recommender system tailored for hierarchical network information structures. FocalPoint reasons about contextual information associated with the network, user task, and user cognitive load to tune the presentation of network visualization displays to improve user performance in perception, comprehension and projection of current situational awareness. Our system is applied to two complex information constructs important to dynamic cyber network operations: network maps and attack graphs. The key innovations include: (a) context-aware automatic tailoring of complex network views, (b) multi-resolution hierarchical graph aggregation, (c) incorporation of new computational models for adaptive-decision making on user tasks, cost/benefit utility and human situation awareness, and (d) user interaction techniques to integrate recommendations into the network viewing system. Our aim is to have a direct impact on planning and operations management for complex networks by; overcoming information overload, preventing tunnel vision, reducing cognitive load, and increasing time available to focus on optimum level of details of the global network space and missions.

Modelling Situation Awareness Information and System Requirements for the Mission using Goal-Oriented Task Analysis Approach

2014 ◽  
pp. 460-478
Author(s):  
Cyril Onwubiko
Keyword(s):  
Situation Awareness ◽  
Task Analysis ◽  
Situational Awareness ◽  
Computer Network ◽  
Valuable Insight ◽  
Test Scenario ◽  
Agent Oriented Software Engineering ◽  
Awareness Information ◽  
System Requirements ◽  
Security Test

This chapter describes work on modelling situational awareness information and system requirements for the mission. Developing this model based on Goal-Oriented Task Analysis representation of the mission using an Agent Oriented Software Engineering methodology advances current information requirement models because it provides valuable insight on how to effectively achieve the mission’s requirements (information, systems, networks, and IT infrastructure), and offers enhanced situational awareness within the Computer Network Defence environment. Further, the modelling approach using Secure Tropos is described, and model validation using a security test scenario is discussed.

Designing Information Systems and Network Components for Situational Awareness

2012 ◽  
pp. 104-123
Author(s):  
Cyril Onwubiko
Keyword(s):  
Information Systems ◽  
Complex Networks ◽  
Computer Networks ◽  
Situational Awareness ◽  
Computer Network ◽  
Distributed Services ◽  
Network Applications ◽  
Systems Software ◽  
Design Requirements

Operators need situational awareness (SA) of their organisation’s computer networks and Information Systems in order to identify threats, estimate impact of attacks, evaluate risks, understand situations, and make sound decisions swiftly and accurately on what to protect against, and how to address incidents that may impact valued assets. Enterprise computer networks are often huge and complex, spanning across several WANs and supporting a number of distributed services. Understanding situations in such dynamic and complex networks is time-consuming and challenging. Operators SA are enhanced through a number of ways, one of which is through the use of situation-aware systems and technology. Designing situation-aware systems for computer network defence (CND) is difficult without understanding basic situational awareness design requirements of network applications and systems. Thus, this chapter investigates pertinent features that are foundation, essential, and beneficial for designing situation-aware systems, software, and network applications for CND.

An Alternative Framework for Research on Situational Awareness in Computer Network Defense

2012 ◽  
pp. 71-85 ◽  
Author(s):  
Eric McMillan ◽  
Michael Tyworth
Keyword(s):  
Situation Awareness ◽  
Situational Awareness ◽  
Computer Network ◽  
Levels Of Analysis ◽  
Network Defense ◽  
Human In The Loop ◽  
Research Account ◽  
Computer Network Defense ◽  
Level Of Analysis ◽  
New Framework

In this chapter the authors present a new framework for the study of situation awareness in computer network defense (cyber-SA). While immensely valuable, the research to date on cyber-SA has overemphasized an algorithmic level of analysis to the exclusion of the human actor. Since situation awareness, and therefore cyber-SA, is a human cognitive process and state, it is essential that future cyber-SA research account for the human-in-the-loop. To that end, the framework in this chapter presents a basis for examining cyber-SA at the cognitive, system, work, and enterprise levels of analysis. In describing the framework, the authors present examples of research that are emblematic of each type of analysis.

An Alternative Framework for Research on Situational Awareness in Computer Network Defense

2014 ◽  
pp. 322-336
Author(s):  
Eric McMillan ◽  
Michael Tyworth
Keyword(s):  
Situation Awareness ◽  
Situational Awareness ◽  
Computer Network ◽  
Levels Of Analysis ◽  
Network Defense ◽  
Human In The Loop ◽  
Research Account ◽  
Computer Network Defense ◽  
Level Of Analysis ◽  
New Framework

In this chapter the authors present a new framework for the study of situation awareness in computer network defense (cyber-SA). While immensely valuable, the research to date on cyber-SA has overemphasized an algorithmic level of analysis to the exclusion of the human actor. Since situation awareness, and therefore cyber-SA, is a human cognitive process and state, it is essential that future cyber-SA research account for the human-in-the-loop. To that end, the framework in this chapter presents a basis for examining cyber-SA at the cognitive, system, work, and enterprise levels of analysis. In describing the framework, the authors present examples of research that are emblematic of each type of analysis.

Modelling Situation Awareness Information and System Requirements for the Mission using Goal-Oriented Task Analysis Approach

2012 ◽  
pp. 245-262
Author(s):  
Cyril Onwubiko
Keyword(s):  
Situation Awareness ◽  
Task Analysis ◽  
Situational Awareness ◽  
Computer Network ◽  
Valuable Insight ◽  
Test Scenario ◽  
Agent Oriented Software Engineering ◽  
Awareness Information ◽  
System Requirements ◽  
Security Test

This chapter describes work on modelling situational awareness information and system requirements for the mission. Developing this model based on Goal-Oriented Task Analysis representation of the mission using an Agent Oriented Software Engineering methodology advances current information requirement models because it provides valuable insight on how to effectively achieve the mission’s requirements (information, systems, networks, and IT infrastructure), and offers enhanced situational awareness within the Computer Network Defence environment. Further, the modelling approach using Secure Tropos is described, and model validation using a security test scenario is discussed.

scholarly journals Effects of User Interfaces on Take-Over Performance: A Review of the Empirical Evidence

Information ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 162
Author(s):  
Soyeon Kim ◽  
René van Egmond ◽  
Riender Happee
Keyword(s):  
User Interface ◽  
Situation Awareness ◽  
User Interfaces ◽  
Situational Awareness ◽  
Selection Criterion ◽  
Auditory Modality ◽  
Automated Driving ◽  
Automated Vehicle ◽  
Positive Effects ◽  
High Urgency

In automated driving, the user interface plays an essential role in guiding transitions between automated and manual driving. This literature review identified 25 studies that explicitly studied the effectiveness of user interfaces in automated driving. Our main selection criterion was how the user interface (UI) affected take-over performance in higher automation levels allowing drivers to take their eyes off the road (SAE3 and SAE4). We categorized user interface (UI) factors from an automated vehicle-related information perspective. Short take-over times are consistently associated with take-over requests (TORs) initiated by the auditory modality with high urgency levels. On the other hand, take-over requests directly displayed on non-driving-related task devices and augmented reality do not affect take-over time. Additional explanations of take-over situation, surrounding and vehicle information while driving, and take-over guiding information were found to improve situational awareness. Hence, we conclude that advanced user interfaces can enhance the safety and acceptance of automated driving. Most studies showed positive effects of advanced UI, but a number of studies showed no significant benefits, and a few studies showed negative effects of advanced UI, which may be associated with information overload. The occurrence of positive and negative results of similar UI concepts in different studies highlights the need for systematic UI testing across driving conditions and driver characteristics. Our findings propose future UI studies of automated vehicle focusing on trust calibration and enhancing situation awareness in various scenarios.

scholarly journals Differences in subcortico-cortical interactions identified from connectome and microcircuit models in autism

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Bo-yong Park ◽  
Seok-Jun Hong ◽  
Sofie L. Valk ◽  
Casey Paquola ◽  
Oualid Benkarim ◽  
...  
Keyword(s):  
Data Exchange ◽  
Computational Models ◽  
Simulation Models ◽  
Autism Diagnostic Observation Schedule ◽  
Supervised Machine Learning ◽  
Global Network ◽  
Imaging Data ◽  
Phenotypic Data ◽  
Severity Scores ◽  
High Level

AbstractThe pathophysiology of autism has been suggested to involve a combination of both macroscale connectome miswiring and microcircuit anomalies. Here, we combine connectome-wide manifold learning with biophysical simulation models to understand associations between global network perturbations and microcircuit dysfunctions in autism. We studied neuroimaging and phenotypic data in 47 individuals with autism and 37 typically developing controls obtained from the Autism Brain Imaging Data Exchange initiative. Our analysis establishes significant differences in structural connectome organization in individuals with autism relative to controls, with strong between-group effects in low-level somatosensory regions and moderate effects in high-level association cortices. Computational models reveal that the degree of macroscale anomalies is related to atypical increases of recurrent excitation/inhibition, as well as subcortical inputs into cortical microcircuits, especially in sensory and motor areas. Transcriptomic association analysis based on postmortem datasets identifies genes expressed in cortical and thalamic areas from childhood to young adulthood. Finally, supervised machine learning finds that the macroscale perturbations are associated with symptom severity scores on the Autism Diagnostic Observation Schedule. Together, our analyses suggest that atypical subcortico-cortical interactions are associated with both microcircuit and macroscale connectome differences in autism.

Network Situational Awareness

2015 ◽  
pp. 334-349 ◽  
Author(s):  
Tom Fairfax ◽  
Christopher Laing ◽  
Paul Vickers
Keyword(s):  
Real Time ◽  
Network Traffic ◽  
Affective Computing ◽  
Situational Awareness ◽  
Computer Network ◽  
Emergent Properties ◽  
Self Organized ◽  
Traffic Volumes ◽  
Self Organized Criticality ◽  
Intelligent Information

This chapter treats computer networks as a cyber warfighting domain in which the maintenance of situational awareness is impaired by increasing traffic volumes and the lack of immediate sensory perception. Sonification (the use of non-speech audio for communicating information) is proposed as a viable means of monitoring a network in real time and a research agenda employing the sonification of a network's self-organized criticality within a context-aware affective computing scenario is given. The chapter views a computer network as a cyber battlespace with a particular operations spectrum and dynamics. Increasing network traffic volumes are interfering with the ability to present real-time intelligence about a network and so suggestions are made for how the context of a network might be used to help construct intelligent information infrastructures. Such a system would use affective computing principles to sonify emergent properties (such as self-organized criticality) of network traffic and behaviour to provide effective real-time situational awareness.

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