Cyber situational awareness: from geographical alerts to high-level management

This paper focuses on cyber situational awareness and describes a visual analytics solution for monitoring and putting in tight relation data from network level with the organization business. The goal of the proposed solution is to make different security profiles (network security officer, network security manager, and financial security manager) aware of the actual network state (e.g., risk and attack progress) and the impact it actually has on the business tasks, making clear the relationships that exist between the network level and the business level. The proposed solution is instantiated on the ACEA infrastructure, the Italian company that provides power and water purification services to cities in central Italy (millions of end users

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

Using visual analytics to develop situation awareness in astrophysics

We present a novel collaborative visual analytics application for cognitively overloaded users in the astrophysics domain. The system was developed for scientists who need to analyze heterogeneous, complex data under time pressure, and make predictions and time-critical decisions rapidly and correctly under a constant influx of changing data. The Sunfall Data Taking system utilizes several novel visualization and analysis techniques to enable a team of geographically distributed domain specialists to effectively and remotely maneuver a custom-built instrument under challenging operational conditions. Sunfall Data Taking has been in production use for 2 years by a major international astrophysics collaboration (the largest data volume supernova search currently in operation), and has substantially improved the operational efficiency of its users. We describe the system design process by an interdisciplinary team, the system architecture and the results of an informal usability evaluation of the production system by domain experts in the context of Endsley's three levels of situation awareness

An Assessment of PIER Electric Grid Research 2003-2014 White Paper

This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014

Sonification of Network Traffic Flow for Monitoring and Situational Awareness

Maintaining situational awareness of what is happening within a network is challenging, not least because the behaviour happens within computers and communications networks, but also because data traffic speeds and volumes are beyond human ability to process. Visualisation is widely used to present information about the dynamics of network traffic dynamics. Although it provides operators with an overall view and specific information about particular traffic or attacks on the network, it often fails to represent the events in an understandable way. Visualisations require visual attention and so are not well suited to continuous monitoring scenarios in which network administrators must carry out other tasks. Situational awareness is critical and essential for decision-making in the domain of computer network monitoring where it is vital to be able to identify and recognize network environment behaviours.Here we present SoNSTAR (Sonification of Networks for SiTuational AwaReness), a real-time sonification system to be used in the monitoring of computer networks to support the situational awareness of network administrators. SoNSTAR provides an auditory representation of all the TCP/IP protocol traffic within a network based on the different traffic flows between between network hosts. SoNSTAR raises situational awareness levels for computer network defence by allowing operators to achieve better understanding and performance while imposing less workload compared to visual techniques. SoNSTAR identifies the features of network traffic flows by inspecting the status flags of TCP/IP packet headers and mapping traffic events to recorded sounds to generate a soundscape representing the real-time status of the network traffic environment. Listening to the soundscape allows the administrator to recognise anomalous behaviour quickly and without having to continuously watch a computer screen.Comment: 17 pages, 7 figures plus supplemental material in Github repositor

The Impact of Automated Cognitive Assistants on Situational Awareness in the Brigade Combat Team

This research investigated the impact of automated cognitive assistants, specifically, the Personalized Assistant that Learns (PAL), on situational awareness, efficiency and effectiveness of decision making in the brigade combat team. PAL was recently commissioned by Defense Advanced Research Projects Agency (DARPA) to enhance decision making with the Command Post of the Future (CPOF). This is the first study to investigate PAL's effectiveness. Previous literature has indicated that automated cognitive assistants can reduce cognitive load and improve the efficiency and effectiveness of decision-making. This is consistent with constructivist theories that assume that relegating repetitive tasks to an assistant allows decision makers to focus on the most critical issues. This is particularly true in those conditions where the environment is in continuous flux and the decision makers must remain cognizant of changing situations. To investigate PAL'S influence on situational awareness, two groups of military officers comprising a convenience sample were placed into two groups representing brigade combat teams. Before tests were administered, each team was trained on the cognitive assistants and given a hands-on examination to measure competency in PAL and CPOF. All subjects participated in one trial with PAL-enhanced CPOF and one trial with CPOF alone. Self-assessments of situational awareness were administered which included sub-scales on: task management, information management, decision support, and appreciation of the environment, visualization and trust. Speed and quality of decision-making were also measured. Repeated measures analysis of variance was used to compare PAL and CPOF only on situational awareness. In the repeated measures ANOVA, the overall difference on self-report of situational awareness approachedthe .05 level with PAL (M = 1.85, SD = 0.46) and CPOF (M = 2.06, SD = 0.57; F(1,10) = 4.61, p = .057), with the lower score indicating higher approval. There was a significant difference on the decision support category of situational awareness in the second trial using both PAL and CPOF (M = 2.21, SD = 0.59; rated higher than the first trial (M = 2.53, SD = 0.49; F(1,10) = 5.06, p = .048). The following differences were not significant but the means all favored PAL over CPOF: quality of decision making products PAL (M = 2.89, SD = 0.75); CPOF (M = 2.53, SD = 0.83), speed of submission in minutes PAL (M = 9:13, SD = 3:15); CPOF (M = 10:00, SD = 5:53), and Situational Awareness quizzes PAL (M = 67.03, SD = 7.15); CPOF (M = 59.24, SD = 8.23). While comparisons of PAL and CPOF were not significant, results indicate that the PAL automated cognitive assistant has promise in improving the situational awareness and efficiency of military leaders in complex decision making. The findings demonstrate that as military officers grow more accustomed to using these analytical systems, both PAL and CPOF, they rate their support in decision making higher. This initial study of PAL was conducted with a convenience sample of 12 military officers. Further studies are warranted to investigate the benefits of automated cognitive assistant on an array of factors that influence decision-making across conditions and audiences

Improving Antibiotic Resistant Infection Transmission Situational Awareness in Enclosed Facilities with a Novel Graphical User Interface for Tactical Biosurveillance

Serious challenges associated with antibiotic resistant infections (ABRIs) force healthcare practitioners (HCP) to seek innovative approaches that will slow the emergence of new ABRIs and prevent their spread. It was realized that traditional approaches to infection prevention based on education, retrospective reports, and biosurveillance often fail to ensure reliable compliance with infection prevention guidelines and real-time problem solving. The objective of this original research was to develop and test the conceptual design of a situational awareness (SA)-oriented information system for coping with healthcare-associated infection transmission. Constantly changing patterns in spatial distribution of patients, prevalence of infectious cases, clustering of contacts, and frequency of contacts may compromise the effectiveness of infection prevention and control in hospitals. It was hypothesized that providing HCPs with a graphical user interface (GUI) to visualize spatial information on the risks of exposure to ABRIs would effectively increase HCPs’ SA. Increased SA may enhance biosurveillance and result in tactical decisions leading to better patient outcomes. The study employed a mixed qualitative-quantitative research method encompassing conceptualization of GUI content, transcription of electronic health record and biosurveillance data into GUI visual artifacts, and evaluation of the GUI’s impact on HCPs’ perception and comprehension of the conditions that increase the risk of ABRI transmission. The study provided pilot evidence that visualization of spatial disease distribution and spatially-linked exposures and interventions significantly increases HCPs’ SA when compared to current practice. The research demonstrates that the SA-oriented GUI enables the HCPs to promptly answer the question, “At a given location, what are the risks of infection transmission there?” This research provides a new form of medical knowledge representation for spatial population-based decision-making within enclosed environments. The next steps include rapid application development and further hypothesis testing concerning the impact of this GUI on decsion-making

Tests of the elaborated intrusion theory of craving and desire: Features of alcohol craving during treatment for an alcohol disorder

PubMed ID: 1936444

Application of Advanced Early Warning Systems with Adaptive Protection

This project developed and field-tested two methods of Adaptive Protection systems utilizing synchrophasor data. One method detects conditions of system stress that can lead to unintended relay operation, and initiates a supervisory signal to modify relay response in real time to avoid false trips. The second method detects the possibility of false trips of impedance relays as stable system swings “encroach” on the relays’ impedance zones, and produces an early warning so that relay engineers can re-evaluate relay settings. In addition, real-time synchrophasor data produced by this project was used to develop advanced visualization techniques for display of synchrophasor data to utility operators and engineers