DAG-Based Attack and Defense Modeling: Don't Miss the Forest for the Attack Trees

This paper presents the current state of the art on attack and defense modeling approaches that are based on directed acyclic graphs (DAGs). DAGs allow for a hierarchical decomposition of complex scenarios into simple, easily understandable and quantifiable actions. Methods based on threat trees and Bayesian networks are two well-known approaches to security modeling. However there exist more than 30 DAG-based methodologies, each having different features and goals. The objective of this survey is to present a complete overview of graphical attack and defense modeling techniques based on DAGs. This consists of summarizing the existing methodologies, comparing their features and proposing a taxonomy of the described formalisms. This article also supports the selection of an adequate modeling technique depending on user requirements

The reporting behaviours of student nurses who have experienced verbal abuse

Background: There is evidence that student nurses are vulnerable to experiencing verbal abuse from a variety of sources and under-reporting of verbal abuse is prevalent throughout the nursing profession. The objective of the study is to explore the reporting behaviours of student nurses who have experienced verbal abuse. Method: For this study a definition of verbal abuse was adopted from current Department of Health (England) guidelines. Questionnaires were distributed in 2005 to a convenience sample of 156 third year nursing students from one pre-registration nursing programme in England. A total of 114 questionnaires were returned, giving an overall response rate of 73.0%. Results: Fifty one students (44.7% of responses) reported verbal abuse; all of these completed the section exploring reporting behaviours. The incidents involved patients in thirty three cases (64.7%); eight cases (15.7%) involved visitors or relatives and ten cases (19.6%) involved other healthcare workers. Thirty two students (62.7%) stated that they did report the incident of verbal abuse they experienced and nineteen (37.3%) of respondents reported that they did not. Only four incidents developed from an oral report to being formally documented. There was a statistically significant association (P = 0.003) between the focus of verbal abuse (patient/visitor or colleague) and the respondents reporting practices with respondents experiencing verbal abuse from colleagues less likely to report incidents. Most frequent feelings following experiences of verbal abuse from colleagues were feelings of embarrassment and hurt/shock. Most frequent consequences of experiencing verbal abuse from patients or relatives were feeling embarrassed and feeling sorry for the abuser. When comparing non reporters with reporters, the most frequent feelings of non reporters were embarrassment and hurt and reporters, embarrassment and feeling sorry for the abuser. When considering levels of support after the incident the mean rating score of respondents who reported the incident was 5.40 (standard deviation 2.89) and of those that did not, 4.36 (standard deviation 2.87) which was not statistically significant (p = 0.220). Conclusions: 1. Not documenting experiences of verbal abuse formally in writing is a prevalent phenomenon within the sample studied and reporting practices are inconsistent. 2. Both Higher Education Institutions and health care providers should consider emphasising formal reporting and documenting of incidents of verbal abuse during student nurse training and access to formal supportive services should be promoted. 3. Effective incident reporting processes and analysis of these reports can lead to an increased awareness of how to avoid negative interactions in the workplace and how to deal with incidents effectively

An aspect-oriented framework for systematic security hardening of software

In this thesis, we address the problems related to the security hardening of open source software. Accordingly, we first propose an aspect-oriented and pattern-based approach for systematic security hardening. It is based on the full separation between the roles and duties of the security experts and the developers performing the hardening. Such proposition constitutes a bridge that allows the security experts to provide the best solutions to particular security problems with the details on why, how and where to apply them. Moreover, it allows the developers to use these solutions to harden open source software without the need to have high security expertise. We realize the proposed approach by elaborating a programming independent and aspect-oriented based language for security hardening called SHL, developing its corresponding parser, compiler and facilities and integrating all of them into a framework for software security hardening. We also illustrate the feasibility of the elaborated framework by developing several security hardening case studies that deal with known security requirements and vulnerabilities and applying them on large scale software. Second, we enrich SHL and the aspect-oriented languages with new pointcut and primitive constructs ( GAFlow, GDFlow, ExportParameter and ImportParameter ) that provide features missing in the current AOP proposals and needed for systematic security hardening concerns. We also explore the viability of the proposed pointcuts and primitives by elaborating and implementing their algorithms and presenting the result of explanatory case studies. Finally, we improve the proposed framework by proposing a new approach for applying security hardening on the Gimple representation of software and elaborating formal syntax for SHL and Gimple together with an operational semantics for SHL weaving based on Gimple. We realize our proposition by integrating into the GCC compiler few features described in the SHL weaving semantics and developing a demonstrative case stud

Älykäs tunnistauminen ja käyttöoikeuksien hallinta monimuotoisessa verkotetussa maailmassa

Our living environments are full of various connected computing devices. These environments in homes, offices, public spaces, transportation etc. are gaining abilities to acquire and apply knowledge about the environment and its users in order to improve users' experience in that environment. However, before smart adaptive solutions can be deployed in critical applications, authentication and authorization mechanisms are needed to provide protection against various security threats. These mechanisms must be able to interoperate and share information with different devices. The thesis focuses to questions on how to facilitate the interoperability of authentication and authorization solutions and how to enable adaptability and smartness of these solutions. To address questions, this thesis explores existing authentication and authorizations solutions. Then the thesis builds new reusable, interoperable, and adaptive security solutions. The smart space concept, based on semantic web technologies and publish-and-subscribe architecture, is recognized as a prominent approach for interoperability. We contribute by proposing solutions, which facilitate implementation of smart access control applications. An essential enabler for smart spaces is a secure platform for information sharing. This platform can be based on various security protocols and frameworks, providing diverse security levels. We survey security-levels and feasibility of some key establishment protocols and solutions for authentication and authorization. We also study ecosystem and adaptation issues as well as design and implement a fine-grained and context-based reusable security model, which enables development of self-configuring and adaptive authorization solutions.Ympäristöt, joissa elämme, ovat täynnä erilaisia verkkolaitteita. Nämä koteihin, toimistoihin, julkisiin tiloihin ja ajoneuvoihin muodostuvat ympäristöt ovat oppimassa hyödyntämään ympäriltä saatavilla olevaa tietoa ja sopeuttamaan toimintaansa parantaakseen käyttäjän kokemusta näistä ympäristössä. Älykkäiden ja sopeutuvien tilojen käyttöönotto kriittisissä sovelluksissa vaatii kuitenkin tunnistautumis- ja käyttöoikeuksien hallintamenetelmiä tietoturvauhkien torjumiseksi. Näiden menetelmien pitää pystyä yhteistoimintaan ja mahdollistaa tiedonvaihto erilaisten laitteiden kanssa. Tämä lisensiaatin tutkimus keskittyy kysymyksiin, kuinka helpottaa tunnistautumis- ja käyttöoikeusratkaisujen yhteensopivuutta ja kuinka mahdollistaa näiden ratkaisujen sopeutumiskyky ja älykäs toiminta. Tutkimuksessa tarkastellaan olemassa olevia menetelmiä. Tämän jälkeen kuvataan toteutuksia uusista tietoturvaratkaisuista, jotka ovat uudelleenkäytettäviä, eri laitteiden kanssa yhteensopivia ja eri vaatimuksiin mukautuvia. Älytilat, jotka perustuvat semanttisten web teknologioiden ja julkaise-ja-tilaa arkkitehtuurin hyödyntämiseen, tunnistetaan työssä lupaavaksi yhteensopivuuden tuovaksi ratkaisuksi. Tutkimus esittää ratkaisuja, jotka helpottavat älykkäiden tunnistautumis- ja käyttöoikeuksien hallintaratkaisujen kehitystä. Oleellinen yhteensopivuuden mahdollistaja on tietoturvallinen yhteensopivuusalusta. Tämä alusta voi perustua erilaisiin avaintenhallinta ja tunnistautumisprotokolliin sekä käyttöoikeuksien hallintakehyksiin. Tutkimuksessa arvioidaan joidenkin olemassa olevien ratkaisujen käytettävyyttä ja tietoturvatasoa. Tutkimuksessa myös tutkitaan ekosysteemi- ja sopeutumiskysymyksiä sekä toteutetaan hienojakoinen ja kontekstiin perustuva uudelleen käytettävä tietoturvamalli, joka mahdollistaa itsesääntyvien ja mukautuvien käyttöoikeuksien hallinta sovellusten toteuttamisen

Fellow Travellers: What do users trust on recommender websites? A case study of TripAdvisor.com

Ph.DDOCTOR OF PHILOSOPH

Improving data preparation for the application of process mining

Immersed in what is already known as the fourth industrial revolution, automation and data exchange are taking on a particularly relevant role in complex environments, such as industrial manufacturing environments or logistics. This digitisation and transition to the Industry 4.0 paradigm is causing experts to start analysing business processes from other perspectives. Consequently, where management and business intelligence used to dominate, process mining appears as a link, trying to build a bridge between both disciplines to unite and improve them. This new perspective on process analysis helps to improve strategic decision making and competitive capabilities. Process mining brings together data and process perspectives in a single discipline that covers the entire spectrum of process management. Through process mining, and based on observations of their actual operations, organisations can understand the state of their operations, detect deviations, and improve their performance based on what they observe. In this way, process mining is an ally, occupying a large part of current academic and industrial research. However, although this discipline is receiving more and more attention, it presents severe application problems when it is implemented in real environments. The variety of input data in terms of form, content, semantics, and levels of abstraction makes the execution of process mining tasks in industry an iterative, tedious, and manual process, requiring multidisciplinary experts with extensive knowledge of the domain, process management, and data processing. Currently, although there are numerous academic proposals, there are no industrial solutions capable of automating these tasks. For this reason, in this thesis by compendium we address the problem of improving business processes in complex environments thanks to the study of the state-of-the-art and a set of proposals that improve relevant aspects in the life cycle of processes, from the creation of logs, log preparation, process quality assessment, and improvement of business processes. Firstly, for this thesis, a systematic study of the literature was carried out in order to gain an in-depth knowledge of the state-of-the-art in this field, as well as the different challenges faced by this discipline. This in-depth analysis has allowed us to detect a number of challenges that have not been addressed or received insufficient attention, of which three have been selected and presented as the objectives of this thesis. The first challenge is related to the assessment of the quality of input data, known as event logs, since the requeriment of the application of techniques for improving the event log must be based on the level of quality of the initial data, which is why this thesis presents a methodology and a set of metrics that support the expert in selecting which technique to apply to the data according to the quality estimation at each moment, another challenge obtained as a result of our analysis of the literature. Likewise, the use of a set of metrics to evaluate the quality of the resulting process models is also proposed, with the aim of assessing whether improvement in the quality of the input data has a direct impact on the final results. The second challenge identified is the need to improve the input data used in the analysis of business processes. As in any data-driven discipline, the quality of the results strongly depends on the quality of the input data, so the second challenge to be addressed is the improvement of the preparation of event logs. The contribution in this area is the application of natural language processing techniques to relabel activities from textual descriptions of process activities, as well as the application of clustering techniques to help simplify the results, generating more understandable models from a human point of view. Finally, the third challenge detected is related to the process optimisation, so we contribute with an approach for the optimisation of resources associated with business processes, which, through the inclusion of decision-making in the creation of flexible processes, enables significant cost reductions. Furthermore, all the proposals made in this thesis are validated and designed in collaboration with experts from different fields of industry and have been evaluated through real case studies in public and private projects in collaboration with the aeronautical industry and the logistics sector

Aquaculture Law and Policy

The aquaculture industry is fast expanding around the globe and causing major environmental and social disruptions. The volume is about getting a 'good governance' grip on this important industry. The book highlights the numerous law and policy issues that must be addressed in the search for effective regulation of aquaculture. Those issues include among others: the equitable and fair assignment of property rights; the design of effective dispute resolution mechanisms; clarification of what maritime laws apply to aquaculture; adoption of a proper taxation system for aquaculture; resolution of aboriginal offshore title and rights claims; recognition of international trade law restrictions such as labeling limitations and food safety requirements; and determination of whether genetically modified fish should be allowed and if so under what controls. This book will appeal to a broad range of audiences: undergraduate and postgraduate students, academic researchers, policy makers, NGOs, practicing lawyers and industry representatives

Automatic detection of safety and security vulnerabilities in open source software

Growing software quality requirements have raised the stakes on software safety and security. Building secure software focuses on techniques and methodologies of design and implementation in order to avoid exploitable vulnerabilities. Unfortunately, coding errors have become common with the inexorable growth tendency of software size and complexity. According to the US National Institute of Standards and Technology (NIST), these coding errors lead to vulnerabilities that cost the US economy $60 billion each year. Therefore, tracking security and safety errors is considered as a fundamental cornerstone to deliver software that are free from severe vulnerabilities. The main objective of this thesis is the elaboration of efficient, rigorous, and practical techniques for the safety and security evaluation of source code. To tackle safety errors related to the misuse of type and memory operations, we present a novel type and effect discipline that extends the standard C type system with safety annotations and static safety checks. We define an inter-procedural, flow-sensitive, and alias-sensitive inference algorithm that automatically propagates type annotations and applies safety checks to programs without programmers' interaction. Moreover, we present a dynamic semantics of our C core language that is compliant with the ANSI C standard. We prove the consistency of the static semantics with respect to the dynamic semantics. We show the soundness of our static analysis in detecting our targeted set of safety errors. To tackle system-specific security properties, we present a security verification framework that combines static analysis and model-checking. We base our approach on the GCC compiler and its GIMPLE representation of source code to extract model-checkable abstractions of programs. For the verification process, we use an off-the-shelf pushdown system model-checker, and turn it into a fully-fledged security verification framework. We also allow programmers to define a wide range of security properties using an automata-based specification approach. To demonstrate the efficiency and the scalability of our approach, we conduct extensive experiments and case studies on large scale open-source software to verify their compliance with a representative set of the CERT standard secure coding rules

Customer behaviour towards internet banking: a study of the dormant users of Saudi Arabia

Technology acceptance, especially internet banking acceptance has become a vital issue in the business world today. A number of studies agree on the importance of customer adoption and full utilization of internet banking services as the key factors for banks to achieve the benefits from launching this channel (eg. Guriting & Ndubisi, 2006; Nor, 2005; Yousafzai, 2005; Mols et al., 1999). They also highlight the crucial role of the comprehensive understanding of the factors and their interactions with each other that influence customers in accepting and using internet banking services. A review of literature related to internet banking indicates that while there are numerous studies that have tried to identify the factors affecting non-adopters and/or users of internet banking there is no single study, specifically in Saudi Arabia, that sheds light on the factors affecting dormant users of internet banking. Hence, the present study provides additional insights into this issue. The study adds to the body of knowledge in the technology acceptance field by developing a comprehensive model for internet banking acceptance. The model extended the Technology Acceptance Model (TAM) to include additional components, namely task-technology fit (TTF), perceived trust and perceived risk. The subjects for this study were Saudi bank customers who are dormant users of internet banking services. One thousand copies of the questionnaire were distributed in five Saudi cities: Riyadh, Jeddah, Dammam, Abhah and Buraydah. A total of 430 completed questionnaires were received, giving a response rate of 43% of the original sample. Structural equation modelling (SEM) was the statistical technique employed in this study. The main results of this study suggest that two factors, namely perceived usefulness and service visibility directly influence Saudi customers’ intention to use internet banking. Perceived ease of use is indirectly significant on the behavioral intentions through perceived usefulness. Moreover, perceived trust, system reliability and accessibility significantly influence perceived ease of use of internet banking. The results also reveal that customer trust in internet banking can be developed by focusing on only one theoretical construct of trust, perceived bank trustworthiness of the internet banking provider. Based on the findings, implications for internet banking practice and related future research have been identified