839 resultados para 280505 Data Security


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For any discipline to be regarded as a professional undertaking by which its members may be treated as true “professionals” in a specific area, practitioners must clearly understand that discipline’s history as well as the place and significance of that history in current practice as well as its relevance to available technologies and artefacts at the time. This is common for many professional disciplines such as medicine, pharmacy, engineering, law and so on but not yet, this paper submits, in information technology. Based on twenty five elapsed years of experience in developing and delivering Cybersecurity courses at undergraduate and postgraduate levels, this paper proposes a rationale and set of differing perspectives for the planning and development of curricula relevant to the delivery of appropriate courses in the history of cybersecurity or information assurance to information and communications technology (ICT) students and thus to potential information technology professionals.

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The decisions people make about medical treatments have a great impact on their lives. Health care practitioners, providers and patients often make decisions about medical treatments without complete understanding of the circumstances. The main reason for this is that medical data are available in fragmented, disparate and heterogeneous data silos. Without a centralised data warehouse structure to integrate these data silos, it is highly unlikely and impractical for the users to get all the information required on time to make a correct decision. In this research paper, a clinical data integration approach using SAS Clinical Data Integration Server tools is presented.

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Iris based identity verification is highly reliable but it can also be subject to attacks. Pupil dilation or constriction stimulated by the application of drugs are examples of sample presentation security attacks which can lead to higher false rejection rates. Suspects on a watch list can potentially circumvent the iris based system using such methods. This paper investigates a new approach using multiple parts of the iris (instances) and multiple iris samples in a sequential decision fusion framework that can yield robust performance. Results are presented and compared with the standard full iris based approach for a number of iris degradations. An advantage of the proposed fusion scheme is that the trade-off between detection errors can be controlled by setting parameters such as the number of instances and the number of samples used in the system. The system can then be operated to match security threat levels. It is shown that for optimal values of these parameters, the fused system also has a lower total error rate.

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The health system is one sector dealing with very large amount of complex data. Many healthcare organisations struggle to utilise these volumes of health data effectively and efficiently. Therefore, there is a need for very effective system to capture, collate and distribute this health data. There are number of technologies have been identified to integrate data from different sources. Data warehousing is one technology can be used to manage clinical data in the healthcare. This paper addresses how data warehousing assist to improve cardiac surgery decision making. This research used the cardiac surgery unit at the Prince Charles Hospital (TPCH) as the case study. In order to deal with other units efficiently, it is important to integrate disparate data to a single point interrogation. We propose implementing a data warehouse for the cardiac surgery unit at TPCH. The data warehouse prototype developed using SAS enterprise data integration studio 4.2 and data was analysed using SAS enterprise edition 4.3. This improves access to integrated clinical and financial data with, improved framing of data to the clinical context, giving potentially better informed decision making for both improved management and patient care.

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The main theme of this thesis is to allow the users of cloud services to outsource their data without the need to trust the cloud provider. The method is based on combining existing proof-of-storage schemes with distance-bounding protocols. Specifically, cloud customers will be able to verify the confidentiality, integrity, availability, fairness (or mutual non-repudiation), data freshness, geographic assurance and replication of their stored data directly, without having to rely on the word of the cloud provider.

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The Transport Layer Security (TLS) protocol is the most widely used security protocol on the Internet. It supports negotiation of a wide variety of cryptographic primitives through different cipher suites, various modes of client authentication, and additional features such as renegotiation. Despite its widespread use, only recently has the full TLS protocol been proven secure, and only the core cryptographic protocol with no additional features. These additional features have been the cause of several practical attacks on TLS. In 2009, Ray and Dispensa demonstrated how TLS renegotiation allows an attacker to splice together its own session with that of a victim, resulting in a man-in-the-middle attack on TLS-reliant applications such as HTTP. TLS was subsequently patched with two defence mechanisms for protection against this attack. We present the first formal treatment of renegotiation in secure channel establishment protocols. We add optional renegotiation to the authenticated and confidential channel establishment model of Jager et al., an adaptation of the Bellare--Rogaway authenticated key exchange model. We describe the attack of Ray and Dispensa on TLS within our model. We show generically that the proposed fixes for TLS offer good protection against renegotiation attacks, and give a simple new countermeasure that provides renegotiation security for TLS even in the face of stronger adversaries.

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Advances in Information and Communication Technologies have the potential to improve many facets of modern healthcare service delivery. The implementation of electronic health records systems is a critical part of an eHealth system. Despite the potential gains, there are several obstacles that limit the wider development of electronic health record systems. Among these are the perceived threats to the security and privacy of patients’ health data, and a widely held belief that these cannot be adequately addressed. We hypothesise that the major concerns regarding eHealth security and privacy cannot be overcome through the implementation of technology alone. Human dimensions must be considered when analysing the provision of the three fundamental information security goals: confidentiality, integrity and availability. A sociotechnical analysis to establish the information security and privacy requirements when designing and developing a given eHealth system is important and timely. A framework that accommodates consideration of the legislative requirements and human perspectives in addition to the technological measures is useful in developing a measurable and accountable eHealth system. Successful implementation of this approach would enable the possibilities, practicalities and sustainabilities of proposed eHealth systems to be realised.

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Big Data is a rising IT trend similar to cloud computing, social networking or ubiquitous computing. Big Data can offer beneficial scenarios in the e-health arena. However, one of the scenarios can be that Big Data needs to be kept secured for a long period of time in order to gain its benefits such as finding cures for infectious diseases and protecting patient privacy. From this connection, it is beneficial to analyse Big Data to make meaningful information while the data is stored securely. Therefore, the analysis of various database encryption techniques is essential. In this study, we simulated 3 types of technical environments, namely, Plain-text, Microsoft Built-in Encryption, and custom Advanced Encryption Standard, using Bucket Index in Data-as-a-Service. The results showed that custom AES-DaaS has a faster range query response time than MS built-in encryption. Furthermore, while carrying out the scalability test, we acknowledged that there are performance thresholds depending on physical IT resources. Therefore, for the purpose of efficient Big Data management in eHealth it is noteworthy to examine their scalability limits as well even if it is under a cloud computing environment. In addition, when designing an e-health database, both patient privacy and system performance needs to be dealt as top priorities.

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A significant amount of speech data is required to develop a robust speaker verification system, but it is difficult to find enough development speech to match all expected conditions. In this paper we introduce a new approach to Gaussian probabilistic linear discriminant analysis (GPLDA) to estimate reliable model parameters as a linearly weighted model taking more input from the large volume of available telephone data and smaller proportional input from limited microphone data. In comparison to a traditional pooled training approach, where the GPLDA model is trained over both telephone and microphone speech, this linear-weighted GPLDA approach is shown to provide better EER and DCF performance in microphone and mixed conditions in both the NIST 2008 and NIST 2010 evaluation corpora. Based upon these results, we believe that linear-weighted GPLDA will provide a better approach than pooled GPLDA, allowing for the further improvement of GPLDA speaker verification in conditions with limited development data.

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Speaker attribution is the task of annotating a spoken audio archive based on speaker identities. This can be achieved using speaker diarization and speaker linking. In our previous work, we proposed an efficient attribution system, using complete-linkage clustering, for conducting attribution of large sets of two-speaker telephone data. In this paper, we build on our proposed approach to achieve a robust system, applicable to multiple recording domains. To do this, we first extend the diarization module of our system to accommodate multi-speaker (>2) recordings. We achieve this through using a robust cross-likelihood ratio (CLR) threshold stopping criterion for clustering, as opposed to the original stopping criterion of two speakers used for telephone data. We evaluate this baseline diarization module across a dataset of Australian broadcast news recordings, showing a significant lack of diarization accuracy without previous knowledge of the true number of speakers within a recording. We thus propose applying an additional pass of complete-linkage clustering to the diarization module, demonstrating an absolute improvement of 20% in diarization error rate (DER). We then evaluate our proposed multi-domain attribution system across the broadcast news data, demonstrating achievable attribution error rates (AER) as low as 17%.

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Techniques to improve the automated analysis of natural and spontaneous facial expressions have been developed. The outcome of the research has applications in several fields including national security (eg: expression invariant face recognition); education (eg: affect aware interfaces); mental and physical health (eg: depression and pain recognition).

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This project was a step forward in developing intrusion detection systems in distributed environments such as web services. It investigates a new approach of detection based on so-called "taint-marking" techniques and introduces a theoretical framework along with its implementation in the Linux kernel.

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Numerous statements and declarations have been made over recent decades in support of open access to research data. The growing recognition of the importance of open access to research data has been accompanied by calls on public research funding agencies and universities to facilitate better access to publicly funded research data so that it can be re-used and redistributed as public goods. International and inter-governmental bodies such as the ICSU/CODATA, the OECD and the European Union are strong supporters of open access to and re-use of publicly funded research data. This thesis focuses on the research data created by university researchers in Malaysian public universities whose research activities are funded by the Federal Government of Malaysia. Malaysia, like many countries, has not yet formulated a policy on open access to and re-use of publicly funded research data. Therefore, the aim of this thesis is to develop a policy to support the objective of enabling open access to and re-use of publicly funded research data in Malaysian public universities. Policy development is very important if the objective of enabling open access to and re-use of publicly funded research data is to be successfully achieved. In developing the policy, this thesis identifies a myriad of legal impediments arising from intellectual property rights, confidentiality, privacy and national security laws, novelty requirements in patent law and lack of a legal duty to ensure data quality. Legal impediments such as these have the effect of restricting, obstructing, hindering or slowing down the objective of enabling open access to and re-use of publicly funded research data. A key focus in the formulation of the policy was the need to resolve the various legal impediments that have been identified. This thesis analyses the existing policies and guidelines of Malaysian public universities to ascertain to what extent the legal impediments have been resolved. An international perspective is adopted by making a comparative analysis of the policies of public research funding agencies and universities in the United Kingdom, the United States and Australia to understand how they have dealt with the identified legal impediments. These countries have led the way in introducing policies which support open access to and re-use of publicly funded research data. As well as proposing a policy supporting open access to and re-use of publicly funded research data in Malaysian public universities, this thesis provides procedures for the implementation of the policy and guidelines for addressing the legal impediments to open access and re-use.

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The purpose of the current study was to develop a measurement of information security culture in developing countries such as Saudi Arabia. In order to achieve this goal, the study commenced with a comprehensive review of the literature, the outcome being the development of a conceptual model as a reference base. The literature review revealed a lack of academic and professional research into information security culture in developing countries and more specifically in Saudi Arabia. Given the increasing importance and significant investment developing countries are making in information technology, there is a clear need to investigate information security culture from developing countries perspective such as Saudi Arabia. Furthermore, our analysis indicated a lack of clear conceptualization and distinction between factors that constitute information security culture and factors that influence information security culture. Our research aims to fill this gap by developing and validating a measurement model of information security culture, as well as developing initial understanding of factors that influence security culture. A sequential mixed method consisting of a qualitative phase to explore the conceptualisation of information security culture, and a quantitative phase to validate the model is adopted for this research. In the qualitative phase, eight interviews with information security experts in eight different Saudi organisations were conducted, revealing that security culture can be constituted as reflection of security awareness, security compliance and security ownership. Additionally, the qualitative interviews have revealed that factors that influence security culture are top management involvement, policy enforcement, policy maintenance, training and ethical conduct policies. These factors were confirmed by the literature review as being critical and important for the creation of security culture and formed the basis for our initial information security culture model, which was operationalised and tested in different Saudi Arabian organisations. Using data from two hundred and fifty-four valid responses, we demonstrated the validity and reliability of the information security culture model through Exploratory Factor Analysis (EFA), followed by Confirmatory Factor Analysis (CFA.) In addition, using Structural Equation Modelling (SEM) we were further able to demonstrate the validity of the model in a nomological net, as well as provide some preliminary findings on the factors that influence information security culture. The current study contributes to the existing body of knowledge in two major ways: firstly, it develops an information security culture measurement model; secondly, it presents empirical evidence for the nomological validity for the security culture measurement model and discovery of factors that influence information security culture. The current study also indicates possible future related research needs.

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Non-linear feedback shift register (NLFSR) ciphers are cryptographic tools of choice of the industry especially for mobile communication. Their attractive feature is a high efficiency when implemented in hardware or software. However, the main problem of NLFSR ciphers is that their security is still not well investigated. The paper makes a progress in the study of the security of NLFSR ciphers. In particular, we show a distinguishing attack on linearly filtered NLFSR (or LF-NLFSR) ciphers. We extend the attack to a linear combination of LF-NLFSRs. We investigate the security of a modified version of the Grain stream cipher and show its vulnerability to both key recovery and distinguishing attacks.