Abstract - The objective of this paper is to motivate human computation research, leveraged with the advantages of fuzzy-based systems, within the military situational awareness domain. The goal is to stimulate the use of fuzzy logic's ability for providing more intuitive ways to model complex systems as the basis for research aimed toward facilitating human computation in the context of improving military situational awareness.
Abstract - Current military decision making requires the ability to amalgamate a volume, velocity, variety and veracity of information not seen in most other domains. Confounding the calculation for the value of this information is the realization that seldom does the information agree. Appreciative of these challenges, strides have been made to successfully capture and codify how analysts perceive the value of information (VoI) given its source, content, and latency. Capitalizing on this past success, this paper broadens the scope of VoI research and examines two important and interrelated efforts. Presented first is a novel approach that extends the original VoI calculation from a single element of information to an amalgamation of multiple elements of information that either complement or contradict the original premise. Presented second is a 'human-inside-the-loop' concept designed to assist in scaling future autonomous VoI methodologies - effectively interleaving human and machine computation.
Abstract - With the increasing development of social media, we now face large amounts of up-to- date data, new information resources, and fast and transparent information propagating methods. They have changed the way we understand the world, which means we can have a different perspective when computing situation awareness. In this paper, we give a detailed explanation on how social media data affect situation awareness and our focus is set on the military environment. We discuss why subject matter expert based human computation is necessary and essential for this procedure and how to involve it in the situation awareness architecture. The goal of our paper is to give readers some suggestions on how to use social media and human processing power within the military situational awareness domain.
Abstract - Human computation (HC) is an active research field in which people play a notable role as computational elements in an automated system with the aim of arriving at a truly symbiotic human-computer interaction. Situational awareness (SA) and decision support systems (DSSs) are two domains where human computation is rapidly advancing, with the latter arising as an invaluable vehicle to achieve the former. Fuzzy systems and fuzzy logic are two commonly employed tools in these domains due to their inherent capabilities of representing and processing vague and imprecise information while conveying the analysis results in an interpretable fashion. In this paper, we elaborate on the human computation aspects of risk analysis within SA and DSS conducted with the aid of fuzzy sets. The study makes the following contributions: (1) we argue that risk analysis must be a highly automated yet still human-centric endeavour and highlight four manners in which the human component provides value to the underlying data/information fusion processes; (2) we illustrate this fuzzy/human risk analysis methodology through a multimodular Risk Management Framework (RMF) architecture and its application to the maritime domain, particularly in hard-soft data fusion, automated response generation to maritime incidents, port anomaly filtering and dynamic risk management triggered by contextual knowledge and (3) the framework under discussion can be extrapolated to other domains with negligible effort.
Abstract - Biometric is a reliable and convenient way for person authentication. Template security is a major concern in practical implementation of biometric system. This work proposes cryptosystem for face verification with fuzzy vault. Here, a secrete value k locked using fuzzy vault with a set of points. Fuzzy vault scheme is order invariant and applied for coordinate points, hence SIFT is suitable feature extraction method. SIFT is distinctive invariant feature extraction method. As there is a trade-off between accuracy and security, this is challenge to implement biometric template protection scheme which will not degrade the recognition performance of the biometric system.
Abstract - The majority of computer systems use security software/hardware to protect against cyber attacks. A firewall is one the most popular security systems to protect against unauthorized access to or from its hosted network/system. The Microsoft Windows Operating System (OS) is equipped with an intrinsic firewall utility, which has been enhanced over the years to offer advanced security features including IPSec-based virtual private network functionality. This intrinsic Windows Firewall is still not capable of detecting and preventing Denial of Service (DoS) attacks. Nevertheless as an established end user security tool which is supplied with Windows OS, Windows Firewall with some additional intelligence may be an extremely valuable security utility for millions of Windows users. An intelligent Windows fuzzy firewall named FR- WinFirewall has been developed to improve its functionalities and aid prevention of DoS attacks. This paper presents the further extended and generalised version of the FR- WinFirewall to cover IPv6 traffic and for the inclusion of some extra DoS attack types related to ICMPv4, ICMPv6 and TCP. This augmented FR-WinFirewall can monitor, alert and prevent the three types of DoS attacks, ICMP (ICMPv4 and ICMPv6) DoS, UDP DoS and TCP DoS, as these protocols cover the majority of the TCP/IP traffic within any network. In this firewall, three separate fuzzy reasoning components related to three DoS attack types are designed, implemented and tested successfully. The addition of fuzzy intelligence to an intrinsic Windows Firewall makes it comparatively better than many well known firewalls, which are not yet capable of controlling DoS attacks.