Evidential Reasoning Approach to Behavioural Analysis of ICT Users’ Security Awareness

The role of ICT system’s user should be taken into consideration when developing different information security solutions because user, as its constitutive element, can significantly affect overall system security with his/her potentially risky behaviour depending on the level of user’s security awareness. In this paper authors propose risk assessment approach of ICT users’ behaviour based on the evidential reasoning technique. Performance testing was compared using combination of cluster analysis and discriminant analysis while empirical analysis was conducted on the total of 627 e-mail users grouped regarding gender, age, technical background knowledge and level of experience. Assessment methodology used in this paper has proven to be well suited for evaluation of users’ awareness and identification of their potentially risky behaviour. Results of empirical analysis showed that all groups of users got overall utility grade higher than the simulated "minimally enough aware" user, but less than “average awareness” grade. As users of all groups are highly critical towards collocutor, it can mean that users are quite aware about the importance of information security foundation, but also about lack of knowledge regarding different security issues. Another possible reason may be the users’ negligence toward security guidelines and protocols

An approach to the assessment of potentially risky behaviour of ICT systems’ users

Korisnika informacijsko komunikacijskog sustava treba promatrati njegovim sastavnim dijelom, jer korisnik svojim rizičnim ponašanjem može značajno utjecati na ukupnu razinu sigurnosti sustava. Cilj rada je razviti postupak modeliranja sustava za procjenu rizičnog ponašanja korisnika. Ontologija i OWL simbolički jezik su odabrani za izradu strukture semantičkog modela odnosno formalizaciju prikupljenog znanja iz domene "ponašanja korisnika sustava sa stajališta sigurnosti". Za procjenu ponašanja odabran je algoritam za evidencijsko zaključivanje koji se koristi za pocjenu stanja te omogućuje usporedbu zatečenog stanja više sustava. Dobiveni normirani rezultati obrade su dali ocjenu ponašanja korisnika u rasponu od 0,066 za naivno do 1,000 za "paranoidno" ponašanje. U radu je prikazan način upotrebe algoritma za evidencijsko zaključivanje prilikom procjene ljudskog dijela tehničkog sustava, način procjene cijele grupe umjesto pojedinačnog procjenjivanja te su definirani uvjeti mapiranja algoritma i ontološke strukture.Information and Communication Technology system’s user should be considered as system’s component, because user’s behaviour can significantly affect the system’s security level. The aim of this paper is to develop an assessment method for user’s potentially risky behaviour. Ontology and OWL symbolic language have been chosen in order to define the semantic model and to formalize the knowledge of the domain on "user’s potentially risky behaviour". The Evidential Reasoning algorithm has been chosen for assessment of user’s behaviour. The normalized results for assessment on user’s behaviour give an interval ranging from 0,066 for the "naïve" user to 1,000 for the "paranoid" system’s user which can be used for reference in future work. This paper shows how to use the Evidential Reasoning algorithm to evaluate the human part of a technical system, how to evaluate a group of users instead of an individual evaluation. Furthermore, conditions required to map the algorithm to the ontological structure are defined

Development of an Efficient Planned Maintenance Framework for Marine and Offshore Machinery Operating under Highly Uncertain Environment

The constantly increasing complexity of marine and offshore machinery is a consequence of a constant improvement in ship powering, automation, specialisation in cargo transport, new ship types, as well as an effort to make the sea transport more economic. Therefore, the criteria of reliability, availability and maintainability have become very important factors in the process of marine machinery design, operation and maintenance. An important finding from the literature exposed that failure to marine machinery can cause both direct and indirect economic damage with a long-term financial consequence. Notably, many cases of machinery failures reported in databases were as a result of near misses and incidents which are potential accident indicators. Moreover, experience has shown that modelling of past accident events and scenarios can provide insights into how a machinery failure can be subsisted even if it is not avoidable, also a basis for risk analysis of the machinery in order to reveal its vulnerabilities. This research investigates the following modelling approach in order to improve the efficiency of marine and offshore machinery operating under highly uncertain environment. Firstly, this study makes full use of evidential reasoning’s advantage to propose a novel fuzzy evidential reasoning sensitivity analysis method (FER-SAM) to facilitate the assessment of operational uncertainties (trend analysis, family analysis, environmental analysis, design analysis, and human reliability analysis) in ship cranes. Secondly, a fuzzy rule based sensitivity analysis methodology is proposed as a maintenance prediction model for oil-wetted gearbox and bearing with emphasis on ship cranes by formulating a fuzzy logic box (diagnostic table), which provides the ship crane operators with a means to predict possible impending failure without having to dismantle the crane. Thirdly, experience has shown that it is not financially possible to employ all the suggested maintenance strategies in the literature. Thus, this study proposed a fuzzy TOPSIS approach that can help the maintenance engineers to select appropriate strategies aimed at enhancing the performance of the marine and offshore machinery. Finally, the developed models are integrated in order to facilitate a generic planned maintenance framework for robust improvement and management, especially in situations where conventional planned maintenance techniques cannot be implemented with confidence due to data deficiency

The level of adoption of analytical tools

This PhD thesis is focused on disclosing features that might cause the increase in the use of analytical tools for better decision making. The theoretical part of this research is developed in two phases. At first, an exhaustive literature review was conducted with the purpose of identifying the main features in companies that impact positively the adoption of new analytical tools. This review brought our attention in four key drivers which were the foundation of the theoretical model: management support on data analysis, data-based competitive advantage, systemic thinking and communication outside the company. Secondly, a scale was proposed for classifying companies according with how its analytical capabilities are developed. The theoretical model and scale required to be validated with data from the real world. Four constructs derived from the model were operationalized in 17 items. An extensive statistical research related with the agreement, convergence, test-retest reliability and factor structure of the dimensions was conducted. Results allowed us to ascertain that our instrument is reliable and valid. Then, the questionnaire was sent to companies located in Barcelona area. The central part of the research analyzes data obtained from the companies. At first, the statistical engineering, which is interpreted as the link between the statistical thinking (the strategic management) and methods (the day-to-day operations), was adapted as guideline. A set of seven statistical tools were wisely assembled in a sequential order and relevant conclusions were obtained. Later, it was necessary to validate our preliminary conclusions with additional research and make them more robust. A second approach was utilized with this purpose. The evidential reasoning, which is a type of multi criteria decision analysis method, was implemented. Two different approaches lead us to similar results. At this phase of the thesis unstructured and soft features about the analytical practices were still missing. A complementary approach was needed to include aspects as personal values, beliefs and motivations and identify how they influence on analytical practices of the companies. The laddering methodology was utilized for these purposes. It is defined as a type of in-depth interview that is applied to understand how individuals transform attributes of any given concept into meaningful associations with respect to themselves. Consider this analogy; the data from questionnaires gave us "the picture of forest", then in-depth interviews yielded "the picture of the three". The last part of the thesis is reserved to provide guidelines to companies interested on increasing their analytical capabilities. Here it is offered a road map composed of five stages. The proposed order is: A company receive its diagnostic and is given a stage in the road map, later guidelines are provided to move the company upwards into the scale. The sequence of diagnostic-guidelines-diagnostic should be repeated until the company reach the highest level in the scale: analytics as competitive advantage. At the end of the thesis are presented two sets of values and attributes which were found decisive for increasing the adoption of analytical tools. In the first set, three values: honesty, serving the society and leadership impact the statistical thinking (the strategic level) in the company, whereas three attributes: the goal setting, creativity and information from outside are acting on the statistical methods (the operational level). The statistical engineering (the tactical level) establish a link between strategic and operational levels. All the tools and methods developed in this thesis, including the questionnaire, the scale for ranking the companies, the script for in-depth interviews, the road map for moving upward to higher levels in the scale and its related guidelines, represent an original and helpful toolkit for improving the analytical capabilities in companies

Advanced uncertainty modelling for container port risk analysis.

Globalization has led to a rapid increase of container movements in seaports. Risks in seaports need to be appropriately addressed to ensure economic wealth, operational efficiency, and personnel safety. As a result, the safety performance of a Container Terminal Operational System (CTOS) plays a growing role in improving the efficiency of international trade. This paper proposes a novel method to facilitate the application of Failure Mode and Effects Analysis (FMEA) in assessing the safety performance of CTOS. The new approach is developed through incorporating a Fuzzy Rule-Based Bayesian Network (FRBN) with Evidential Reasoning (ER) in a complementary manner. The former provides a realistic and flexible method to describe input failure information for risk estimates of individual hazardous events (HEs) at the bottom level of a risk analysis hierarchy. The latter is used to aggregate HEs safety estimates collectively, allowing dynamic risk-based decision support in CTOS from a systematic perspective. The novel feature of the proposed method, compared to those in traditional port risk analysis lies in a dynamic model capable of dealing with continually changing operational conditions in ports. More importantly, a new sensitivity analysis method is developed and carried out to rank the HEs by taking into account their specific risk estimations (locally) and their Risk Influence (RI) to a port's safety system (globally). Due to its generality, the new approach can be tailored for a wide range of applications in different safety and reliability engineering and management systems, particularly when real time risk ranking is required to measure, predict, and improve the associated system safety performance

A comprehensive review of hybrid game theory techniques and multi-criteria decision-making methods

More studies trend to hybrid the game theory technique with the multi-criteria decision-making (MCDM) method to aid real-life problems. This paper provides a comprehensive review of the hybrid game theory technique and MCDM method. The fundamentals of game theory concepts and models are explained to make game theory principles clear to the readers. Moreover, the definitions and models are elaborated and classified to the static game, dynamic game, cooperative game and evolutionary game. Therefore, the hybrid game theory technique and MCDM method are reviewed and numerous applications studied from the past works of literature are highlighted. The result of the previous studies shows that the fundamental elements for both frameworks were studied in various ways with most of the past studies tend to integrate the static game with AHP and TOPSIS methods. Also, the integration of game theory techniques and MCDM methods was studied in various applications such as politics, economy, supply chain, engineering, water management problem, allocation problem and telecommunication network selection. The main contribution of the recent studies of employment between game theory technique and MCDM method are analyzed and discussed in detail which includes static and dynamic games in the non-cooperative game, cooperative game, both non-cooperative and cooperative games and evolutionary gam

Freight transport modal choice in North West England's Atlantic Gateway

Overuse of the road network has led to greater levels of congestion, elevated levels of road surface wear and tear and an increase in transport related air pollution. When taken in combination with the failure of attempts to balance modal split the road network’s continuing slide towards breaking point seems to be beyond question. However, circumstances have conspired to present one particular region of England with a tabula rasa for the development of new policies to influence the modal split of freight transportation. England’s economy is currently based around a London-centric model. The current move towards developing what has become known as a Northern Powerhouse is aimed at rebalancing the economy of the nation for the betterment of all of its citizens. The Atlantic Gateway is an integral part of these efforts. The devolution of powers and responsibilities from national government to regional authorities may provide an opportunity for positive change the likes of which has not be seen in the North of England since the beginning of the industrial revolution. Different regions are influenced by their own geographical and infrastructure constraints. Devolution ensures that decisions are made locally and are therefore more able to meet local needs. A greater understanding of what influences modal choice within the Atlantic Gateway allows local policy makers to make better informed decisions on how to accommodate the increasing levels of freight transportation on the existing local transport infrastructure. Two different multi-criteria decision making analysis tools are utilised in this study. The first model uses the Analytic Hierarchy Process (AHP) to determine the weights of a range of criteria identified as influencing modal choice. The second model combines AHP with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to allow the modes of transport under consideration to be ranked. This AHP-TOPSIS approach was adopted to address the limited data made available by the freight transportation industry in support of this research and the inadequacy of the data which is publicly available from mainstream sources. With billions of Pounds having been spent over many years to balance modal split it was disappointing to find that today, in the North West of England, road is still, by far, the preferred mode for transporting freight. The margin by which road leads the other modes within this geographical region shows the degree to which modal shift policy has so far failed. It also shows the amount of work needed to be done if modal shift is to be delivered in the future

Condition monitoring of marine and offshore machinery using evidential reasoning techniques

This paper first assesses the operational uncertainties of a particular piece of equipment in a marine and offshore system based on an oil analysis technique. Trend analysis, family analysis, environmental analysis, human reliability analysis and design analysis for each criterion are aggregated using evidential reasoning (ER) and analytical hierarchy process (AHP) algorithms. Data is collected from available statistics and supplemented by expert judgement from the related industry. The results provided in this study will be beneficial to the marine and offshore industries as indicators for monitoring and diagnosis of faults in machinery and thus assist practitioners in making better decisions in their maintenance management process. Furthermore, by changing the conditions that affect the operation of machinery, and through calculating a value for this operation, a benchmark for condition monitoring is constructed. The operational condition of machinery depends on many variables and their dependencies; thus, alteration of a criterion value will ultimately alter the operational conditions of the machinery. For any deviation to be corrected in a timely manner, the operational condition of the machinery has to be monitored properly and frequently

Smart Sustainable Manufacturing Systems

With the advent of disruptive digital technologies, companies are facing unprecedented challenges and opportunities. Advanced manufacturing systems are of paramount importance in making key enabling technologies and new products more competitive, affordable, and accessible, as well as for fostering their economic and social impact. The manufacturing industry also serves as an innovator for sustainability since automation coupled with advanced manufacturing technologies have helped manufacturing practices transition into the circular economy. To that end, this Special Issue of the journal Applied Sciences, devoted to the broad field of Smart Sustainable Manufacturing Systems, explores recent research into the concepts, methods, tools, and applications for smart sustainable manufacturing, in order to advance and promote the development of modern and intelligent manufacturing systems. In light of the above, this Special Issue is a collection of the latest research on relevant topics and addresses the current challenging issues associated with the introduction of smart sustainable manufacturing systems. Various topics have been addressed in this Special Issue, which focuses on the design of sustainable production systems and factories; industrial big data analytics and cyberphysical systems; intelligent maintenance approaches and technologies for increased operating life of production systems; zero-defect manufacturing strategies, tools and methods towards online production management; and connected smart factories