1,720,960 research outputs found
CRITICAL INFRASTRUCTURE PROTECTION: THREATS MINING AND ASSESSMENT
No full textWithin Homeland Defense, a crucial aspect is related to
Critical Infrastructure (CI) protection. In fact, CIs
encompass a wide range of strategic sectors for
countries, such as food, water, public health, emergency
services, energy, transportation, information
technology, telecommunication and finance. Therefore,
CIs operation should be granted to ensure national
needs satisfaction. In order to monitor and prevent
dangerous situations and threats that could affect CIs,
Situation Awareness (SAW) theory addresses the goal
of maintaining operator awareness, through rough data
acquired by heterogeneous sensors monitoring CIs. One
of the great problems in SAW is related to the definition
of agile models able to highlight threats and to adapt
themselves to monitoring requirements. This paper
describes how Data Mining (DM) approach can be
applied on data acquired by sensors watching at
infrastructures, in order to build agile Hidden Markov
Models (HMMs), for on-going situation assessment and
consequent threat evaluation
An agile model for situation assessment: How to make Evidence Theory able to change idea about classifications
No full text"A relevant issue felt in the domain of Situation Awareness is related to the definition of models describing situations and threats of interest. Actually, the widely adopted approaches are based on two phases: employ training data as input of learning algorithms, and then validate the built model through other sets of data, gathered from the field. Model construction is therefore considered as an off-line process, and model correction is contemplated in terms of little adjustments in real-time applications. Great advantages could be derived by the employment of agile models, able to revise themselves evaluating model inconsistencies, contraddictions and errors, or taking into account user informations. In this paper, the analysis of model agility is conducted with regard to the Evidence Theory approach. The technique contemplates automated reasoning on time-independent models and it is therefore addressed to static pattern recognition, in the domain of Situation Awareness. The mathematical formalism adopted is the Transferable Belief Model, defined by Smets, able to simply identify modelling disagreements or deviations among several information sources. In this work, we investigate about possible metrics to adopt in the correction process. Firstly, we shown the classical model inability to identify two consequent situations; then we propose an algorithm using contradiction information, to allow the model to be aware of different, consequent situations and to change opinion respect to previous situation classified. Some simulation results related to a simple case study in the Critical Infrastructure domain are then reported.
INFUSION: A system for situation and threat assessment in current and foreseen scenarios
No full textThis paper describes INFUSION, a system for the evaluation of situations and threats in simulated military scenarios and for scenario projection, in order to support the decision making process in strategic and tactical context. The system deals with fuzzy variables that model information acquired from the on-going scenario; it adopts the Evidence Theory approach to fuse information and classify situations; moreover, it evaluates threats measuring the risk of on-going situations on the items of interest. INFUSION is able to foresee possible future scenarios, through the projection of the item of the simulated scenario to a desired time or position. Trajectory projection of items depends on their intent, estimated through the Bayesian approach. INFUSION has been tested on different terrestrial scenarios where the situations of encirclement, collision and engagement have been simulated. Considerations on operative results and future works are also reported
Mixed Holistic Reductionistic Approach for Impact Assessment of Cyber Attacks
No full text"Recently issues about cyber-war have gained relevant attention, especially because of gravity of damages that could be caused by cyber attacks to strategic targets, mining security of citizens. Examples of targets might include national civil and military airports, command and control systems of civil and military transportation means electronic military systems for national defense, national infrastructures for water and electricity distribution, industries and also hospitals or firefighters informatics systems. The risk of cyber attacks for the mentioned systems and infrastructures has grown because of the introduction of general-purpose and open (not proprietary)communication protocols, widely interconnecting systems and services. With this regard, it is of great importance the problem of evaluating the impact that cyber attacks could generate and to select effective countermeasures to protect military and civil heterogeneous and interconnected systems. In this paper the Mixed Holistic Reductionist (MHR) model is proposed as a conceptual methodology to evaluate the impact of a set of cyber attacks to military and civil infrastructures of strategic interest. The reductionist approach allows modeling of heterogeneous systems using the simplest elements and then coming to assess the interaction of basic components. The holistic paradigm instead allows to analyze complex systems by evaluating their behavior in complex and thus as a monolithic unit. This model allows combining the holistic method with the reductionist, trying to maintain the benefits of both paradigms. The two methods are linked together through an additional layer which is an intermediate level of abstraction, usually represented by the services of any infrastructure. Services are defined as logical objects, in order to obtain useful functionality to the customer, or other infrastructure. The validity of MHR model has been already tested within the context of Critical Infrastructure protection. In p- rticular, it has been implemented in CISIA, a system-interdependency simulator, developed by "Roma Tre"University. In this work, the effectiveness of the model is studied with regard to government infrastructure protection from cyber attacks and, with this regard, an explicative case study is presented.
Homeland situation awareness through mining and fusing heterogeneous information from intelligence databases and field sensors
No full textOne of the most felt issues in the defence domain is that of having huge quantities of data stored in databases and acquired from field sensors without being able to infer information from them. Usually, databases are continuously updated with observations, and are related to heterogeneous data. Deep and continuous analysis on the data could mine useful correlations, explain relations existing among data and cue searches for further evidences. The solution to the problem addressed before seems to deal both with the domain of data mining and with the domain of high level data fusion. The focus of this paper is the definition of an architecture for a system adopting data mining techniques to adaptively discover clusters of information and relation among them, to classify observations acquired and to use the model of knowledge and the classification derived in order to assess situations, threats and refine the search for evidences.
Keywords: situation awareness; SAW; data mining; hidden Markov models; HMMs; agile modelling; intelligence databases; field sensors; data fusion; data clusters; information integration; classification; threats; defence industry; homeland securit
Countermeasures Selection via Evidence Theory
No full text"\"In this paper an approach to understand the possible causes of outages in different and interconnected infrastructures, based on the evidences of detected failures is provided. Moreover, causes inferred are used to estimate possible not detected failures that, together with those detected, allow to better understand the infrastructure vulnerability and the impact of outages. Such a kind of analysis is regarded as a useful support to identify effective countermeasures, in order to mitigate risks related to malfunctioning behavior of critical infrastructures.\"
Aware online interdependency modelling via evidence theory
No full text"Critical infrastructure interdependency models are typically used in a simulation-based perspective, in order to perform 'what if?' analyses and identify structural vulnerabilities in a dynamic perspective. While in the literature some attempts have been made to use interdependency models at real time, such approaches are flawed by the inability to properly determine the ongoing situation. Such models, typically, receive data from SCADA systems, which are mostly able to assess the effects of failures rather than the causes, while knowing the typology of failure would increase dramatically the predictive-ability of online interdependency models. In this paper, a situation awareness framework is provided with the aim to complement online interdependency models by providing more specific information on the causes of the outages highlighted by sensor data. In order to determine such causes, in this paper a transferable belief model representation is adopted to increase the awareness of interdependency models on fault causes. Moreover in this paper some of the limitations of evidence theory methods are highlighted and discussed, with particular reference to a real time context, providing some insights on how to overcome them, especially the closed-world assumption.
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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