Situation awareness

About: Situation awareness is a research topic. Over the lifetime, 7380 publications have been published within this topic receiving 108695 citations. The topic is also known as: SA & situational awareness.

Wide-Area Situational Awareness for Critical Infrastructure Protection

Abstract: Despite successive attempts to protect critical infrastructures against incidents and malicious threats by using traditional situational awareness solutions, the complex and critical nature of these infrastructures makes this adaptation difficult. For this reason, experts are reconsidering the topic of Wide-Area Situational Awareness (WASA) to provide monitoring of performance at all times from anywhere while ensuring dynamic prevention and response services. Given the novelty of this new research field, a WASA methodological framework together with a set of requirements for awareness construction are presented in this paper in order to help in the development and commissioning of future WASA defense solutions.

Displaying Uncertainty in Advanced Navigation Systems

Abstract: Few human factors studies have addressed the issue of displaying the uncertainty of information provided to users; an issue of growing importance given the current proliferation of advanced situation awareness and navigation displays used in the aviation, automotive and maritime environments. This paper first discusses the growing need to develop guidelines concerning when and how to display uncertainty, and then describes the results of two initial studies aimed at both demonstrating the general utility of displaying uncertainty, and determining the optimal ways to visually represent various levels of uncertainty. We conclude that the impact and effectiveness of future multi-sensor situation awareness displays will be dependent on the skillful presentation of data uncertainty.

Situation awareness: operationally necessary and scientifically grounded

Abstract: Dekker (Cogn Tech Work, doi: 10.1007/s10111-015-0320-8 , 2015) provides a stilted account of situation awareness (SA) in which it is only (or primarily) used to explain away human error. He ignores the large body of work over the past 25 years that has clearly defined SA, builds a strong foundation of cognitive theory on how it works in the brain, and provides a substantial base of scientifically grounded principles for how to improve SA through improvements in display design, automation, and training (see Endsley and Jones, Designing for situation awareness: an approach to human-centered design, 2nd edn. Taylor and Francis, London, 2012). He also ignores work on human error that delves in detail into the reasons for losses of SA in accidents and uses that knowledge to provide needed system improvements. SA is widely recognized by operators and practitioners across aviation, power systems, emergency management, military, medical, and many other domains as being critical to effective decision making and performance. It is incumbent on the human factors profession to respond to this need with improved systems and approaches for enhancing SA in the difficult and complex worlds where it is so essential.

Scalable Framework for Cyber Threat Situational Awareness Based on Domain Name Systems Data Analysis

Abstract: There are myriad of security solutions that have been developed to tackle the Cyber Security attacks and malicious activities in digital world. They are firewalls, intrusion detection and prevention systems, anti-virus systems, honeypots etc. Despite employing these detection measures and protection mechanisms, the number of successful attacks and the level of sophistication of these attacks keep increasing day-by-day. Also, with the advent of Internet-of-Things, the number of devices connected to Internet has risen dramatically. The inability to detect attacks on these devices are due to (1) the lack of computational power for detecting attacks, (2) the lack of interfaces that could potentially indicate a compromise on this devices and (3) the lack of the ability to interact with the system to execute diagnostic tools. This warrants newer approaches such as Tier-1 Internet Service Provider level view of attack patterns to provide situational awareness of Cyber Security threats. We investigate and explore the event data generated by the Internet protocol Domain Name Systems (DNS) for the purpose of Cyber threat situational awareness. Traditional methods such as Static and Binary analysis of Malware are sometimes inadequate to address the proliferation of Malware due to the time taken to obtain and process the individual binaries in order to generate signatures. By the time the Anti-Malware signature is available, there is a chance that a significant amount of damage might have happened. The traditional Anti-Malware systems may not identify malicious activities. However, it may be detected faster through DNS protocol by analyzing the generated event data in a timely manner. As DNS was not designed with security in mind (or suffers from vulnerabilities), we explore how the vast amount of event data generated by these systems can be leveraged to create Cyber threat situational awareness. The main contributions of the book chapter are two-fold: (1). A scalable framework that can perform web scale analysis in near real-time that provide situational awareness. (2). Detect early warning signals before large scale attacks or malware propagation occurs. We employ deep learning approach to classify and correlate malicious events that are perceived from the protocol usage. To our knowledge this is the first time, a framework that can analyze and correlate the DNS usage information at continent scale or multiple Tier-1 Internet Service Provider scale has been studied and analyzed in real-time to provide situational awareness. Merely using a commodity hardware server, the developed framework is capable of analyzing more than 2 Million events per second and it could detect the malicious activities within them in near real-time. The developed framework can be scaled out to analyze even larger volumes of network event data by adding additional computing resources. The scalability and real-time detection of malicious activities from early warning signals makes the developed framework stand out from any system of similar kind.

Antecedents of trust in human-robot collaborations

Abstract: Robotic systems are being introduced into military echelons to extend warfighter capabilities in complex, dynamic environments. While these systems are designed to complement human capabilities (e.g., aiding in battlefield situation awareness and decision making, etc), they are often misused or disused because the user does not have an appropriate level of trust in his or her robotic counterpart(s). We describe a continuing body of research that identifies factors impacting a human's level of trust in a robotic teammate. The factors identified to date can be categorized as human influences (e.g., individual differences in terms of personality, experience, culture), machine influences (e.g., robotic platform, robot performance in terms of levels of automation, failure rates, false alarms), and environmental influences (e.g. task type, operational environment, shared mental models). A framework for human-robot team trust was constructed, which is evolving into a working model contingent upon the results of an on-going meta-analysis.