Browsing by Author "Kayem, Anne"

Now showing 1 - 8 of 8
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    Open Access
    Access and information flow control to secure mobile web service compositions in resource constrained environments
    (2015) Maziya, Lwazi Enock; Kayem, Anne
    The growing use of mobile web services such as electronic health records systems and applications like twitter, Facebook has increased interest in robust mechanisms for ensuring security for such information sharing services. Common security mechanisms such as access control and information flow control are either restrictive or weak in that they prevent applications from sharing data usefully, and/or allow private information leaks when used independently. Typically, when services are composed there is a resource that some or all of the services involved in the composition need to share. However, during service composition security problems arise because the resulting service is made up of different services from different security domains. A key issue that arises and that we address in this thesis is that of enforcing secure information flow control during service composition to prevent illegal access and propagation of information between the participating services. This thesis describes a model that combines access control and information flow control in one framework. We specifically consider a case study of an e-health service application, and consider how constraints like location and context dependencies impact on authentication and authorization. Furthermore, we consider how data sharing applications such as the e-health service application handle issues of unauthorized users and insecure propagation of information in resource constrained environments¹. Our framework addresses this issue of illegitimate information access and propagation by making use of the concept of program dependence graphs (PDGs). Program dependence graphs use path conditions as necessary conditions for secure information flow control. The advantage of this approach to securing information sharing is that, information is only propagated if the criteria for data sharing are verified. Our solution proposes or offers good performance, fast authentication taking into account bandwidth limitations. A security analysis shows the theoretical improvements our scheme offers. Results obtained confirm that the framework accommodates the CIA-triad (which is the confidentiality, integrity and availability model designed to guide policies of information security) of our work and can be used to motivate further research work in this field.
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    Open Access
    Automating user privacy policy recommendations in social media
    (2016) Abuelgasim, Ammar; Kayem, Anne
    Most Social Media Platforms (SMPs) implement privacy policies that enable users to protect their sensitive information against privacy violations. However, observations indicate that users find these privacy policies cumbersome and difficult to configure. Consequently, various approaches have been proposed to assist users with privacy policy configuration. These approaches are however, limited to either protecting only profile attributes, or only protecting user-generated content. This is problematic, because both profile attributes and user-generated content can contain sensitive information. Therefore, protecting one without the other, can still result in privacy violations. A further drawback of existing approaches is that most require considerable user input which is time consuming and inefficient in terms of privacy policy configuration. In order to address these problems, we propose an automated privacy policy recommender system. The system relies on the expertise of existing social media users, as well as the user's privacy policy history in order to provide him/her with personalized privacy policy suggestions for both profile attributes, and user-generated content. Results from our prototype implementation indicate that the proposed recommender system provides accurate privacy policy suggestions, with minimum user input.
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    Designing an architecture for secure sharing of personal health records : a case of developing countries
    (2014) Ssembatya, Richard; Kayem, Anne; Marsden, Gary
    While there has been an increase in the design and development of Personal Health Record (PHR) systems in the developed world, little has been done to explore the utility of these systems in the developing world. Despite the usual problems of poor infrastructure, PHR systems designed for the developing world need to conform to users with different models of security and literacy than those designed for developed world. This study investigated a PHR system distributed across mobile devices with a security model and an interface that supports the usage and concerns of low literacy users in developing countries. The main question addressed in this study is: “Can personal health records be stored securely and usefully on mobile phones?” In this study, mobile phones were integrated into the PHR architecture that we/I designed because the literature reveals that the majority of the population in developing countries possess mobile phones. Additionally, mobile phones are very flexible and cost efficient devices that offer adequate storage and computing capabilities to users for typically communication operations. However, it is also worth noting that, mobile phones generally do not provide sufficient security mechanisms to protect the user data from unauthorized access.
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    Enabling anonymous crime reporting on mobile phones in the developing world
    (2013) Burke, Mark John; Kayem, Anne
    Various campaigns indicate that a need exists for a convenient and anonymous crime reporting framework for the context of the developing world. In this thesis a contribution is made by means of a framework that facilitates reporting crime anonymously based on a secure platform. The framework comprises of two main components namely, a reporting module that is facilitated by unstructured supplementary service data (USSD) on a mobile phone and an anonymization module that is supported by a k-anonymity algorithm. The advantage of using USSD is that it is available to all mobile phones (including the more basic/nonsmart phones that are used by a large percentage of the poorer population in developing countries); and reports made via USSD cannot be traced to the participant. Anonymization has the advantage of guaranteeing user privacy in the management of the reported data. In order to decide on an appropriate anonymization technique for the crime reporting system, we implemented and compared existing popular k-anonymity based algorithms as well as suggesting a crime data anonyimzation algorithm tailored for specific sets of data. The proposed crimemod algorithm is found to provide satisfactory performance and security results. Our results indicate that anonymization algorithms that use hierarchy based generalization techniques, are the best suited to crime reporting scenarios.
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    Open Access
    On supporting K-anonymisation and L-diversity of crime databases with genetic algorithms in a resource constrained environment
    (2015) Verster, Cornelis Thomas; Kayem, Anne
    The social benefits derived from analysing crime data need to be weighed against issues relating to privacy loss. To facilitate such analysis of crime data Burke and Kayem [7] proposed a framework (MCRF) to enable mobile crime reporting in a developing country. Here crimes are reported via mobile phones and stored in a database owned by a law enforcement agency. The expertise required to perform analysis on the crime data is however unlikely to be available within the law enforcement agency. Burke and Kayem [7] proposed anonymising the data(using manual input parameters) at the law enforcement agency before sending it to a third party for analysis. Whilst analysis of the crime data requires expertise, adequate skill to appropriately anonymise the data is also required. What is lacking in the original MCRF is therefore an automated scheme for the law enforcement agency to adequately anonymise the data before sending it to the third party. This should, however, be done whilst maximising information utility of the anonymised data from the perspective of the third party. In this thesis we introduce a crime severity scale to facilitate the automation of data anonymisation within the MCRF. We consider a modified loss metric to capture information loss incurred during the anonymisation process. This modified loss metric also gives third party users the flexibility to specify attributes of the anonymised data when requesting data from the law enforcement agency. We employ a genetic algorithm(GA) approach called "Crime Genes"(CG) to optimise utility of the anonymised data based on our modified loss metric whilst adhering to notions of privacy denned by k-anonymity and l-diversity. Our CG implementation is modular and can therefore be easily integrated with the original MCRF. We also show how our CG approach is designed to be suitable for implementation in a developing country where particular resource constraints exist.
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    A practical key management and distribution system for IPTV conditional access
    (2013) Harding, Gregory Leighton; Kayem, Anne
    Conditional Access (CA) is widely used by pay-television operators to restrict access to content to authorised subscribers. Commercial CA solutions are available for structured broadcast and Internet Protocol Television (IPTV) environments, as well as Internet-based video-on-demand services, however these solutions are mostly proprietary, often inefficient for use on IP networks, and frequently depend on smartcards for maintaining security. An efficient, exible, and open conditional access system that can be implemented practically by operators with large numbers of subscribers would be beneficial to those operators and Set-Top-Box manufacturers in terms of cost savings for royalties and production costs. Furthermore, organisations such as the South African Broadcasting Corporation that are transitioning to Digital-Terrestrial-Television could use an open Conditional Access System (CAS) to restrict content to viewing within national borders and to ensure that only valid TV licence holders are able to access content. To this end, a system was developed that draws from the area of group key management. Users are grouped according to their subscription selections and these groups are authorised for each selection's constituent services. Group keys are updated with a key-tree based approach that includes a novel method for growing full trees that outperforms the standard method. The relations that are created between key trees are used to establish a hierarchy of keys which allows exible selection of services whilst maintaining their cryptographic protection. Conditions for security without dependence on smartcards are defined, and the system is expandable to multi-home viewing scenarios. A prototype implementation was used to assess the proposed system. Total memory consumption of the key-server, bandwidth usage for transmission of key updates, and client processing and storage of keys were all demonstrated to be highly scalable with number of subscribers and number of services.
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    Scalable attack modelling in support of security information and event management
    (2014) Dennie, Keiran; Hutchison, Andrew; Kayem, Anne
    While assessing security on single devices can be performed using vulnerability assessment tools, modelling of more intricate attacks, which incorporate multiple steps on different machines, requires more advanced techniques. Attack graphs are a promising technique, however they face a number of challenges. An attack graph is an abstract description of what attacks are possible against a specific network. Nodes in an attack graph represent the state of a network at a point in time while arcs between nodes indicate the transformation of a network from one state to another, via the exploit of a vulnerability. Using attack graphs allows system and network configuration information to be correlated and analysed to indicate imminent threats. This approach is limited by several serious issues including the state-space explosion, due to the exponential nature of the problem, and the difficulty in visualising an exhaustive graph of all potential attacks. Furthermore, the lack of availability of information regarding exploits, in a standardised format, makes it difficult to model atomic attacks in terms of exploit requirements and effects. This thesis has as its objective to address these issues and to present a proof of concept solution. It describes a proof of concept implementation of an automated attack graph based tool, to assist in evaluation of network security, assessing whether a sequence of actions could lead to an attacker gaining access to critical network resources. Key objectives are the investigation of attacks that can be modelled, discovery of attack paths, development of techniques to strengthen networks based on attack paths, and testing scalability for larger networks. The proof of concept framework, Network Vulnerability Analyser (NVA), sources vulnerability information from National Vulnerability Database (NVD), a comprehensive, publicly available vulnerability database, transforming it into atomic exploit actions. NVA combines these with a topological network model, using an automated planner to identify potential attacks on network devices. Automated planning is an area of Artificial Intelligence (AI) which focuses on the computational deliberation process of action sequences, by measuring their expected outcomes and this technique is applied to support discovery of a best possible solution to an attack graph that is created. Through the use of heuristics developed for this study, unpromising regions of an attack graph are avoided. Effectively, this prevents the state-space explosion problem associated with modelling large scale networks, only enumerating critical paths rather than an exhaustive graph. SGPlan5 was selected as the most suitable automated planner for this study and was integrated into the system, employing network and exploit models to construct critical attack paths. A critical attack path indicates the most likely attack vector to be used in compromising a targeted device. Critical attack paths are identifed by SGPlan5 by using a heuristic to search through the state-space the attack which yields the highest aggregated severity score. CVSS severity scores were selected as a means of guiding state-space exploration since they are currently the only publicly available metric which can measure the impact of an exploited vulnerability. Two analysis techniques have been implemented to further support the user in making an informed decision as to how to prevent identified attacks. Evaluation of NVA was broken down into a demonstration of its effectiveness in two case studies, and analysis of its scalability potential. Results demonstrate that NVA can successfully enumerate the expected critical attack paths and also this information to establish a solution to identified attacks. Additionally, performance and scalability testing illustrate NVA's success in application to realistically sized larger networks.
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    Usability heuristics for fast crime data anonymization in resource-constrained contexts
    (2018) Sakpere, Aderonke Busayo; Kayem, Anne; Gain, James
    This thesis considers the case of mobile crime-reporting systems that have emerged as an effective and efficient data collection method in low and middle-income countries. Analyzing the data, can be helpful in addressing crime. Since law enforcement agencies in resource-constrained context typically do not have the expertise to handle these tasks, a cost-effective strategy is to outsource the data analytics tasks to third-party service providers. However, because of the sensitivity of the data, it is expedient to consider the issue of privacy. More specifically, this thesis considers the issue of finding low-intensive computational solutions to protecting the data even from an "honest-but-curious" service provider, while at the same time generating datasets that can be queried efficiently and reliably. This thesis offers a three-pronged solution approach. Firstly, the creation of a mobile application to facilitate crime reporting in a usable, secure and privacy-preserving manner. The second step proposes a streaming data anonymization algorithm, which analyses reported data based on occurrence rate rather than at a preset time on a static repository. Finally, in the third step the concept of using privacy preferences in creating anonymized datasets was considered. By taking into account user preferences the efficiency of the anonymization process is improved upon, which is beneficial in enabling fast data anonymization. Results from the prototype implementation and usability tests indicate that having a usable and covet crime-reporting application encourages users to declare crime occurrences. Anonymizing streaming data contributes to faster crime resolution times, and user privacy preferences are helpful in relaxing privacy constraints, which makes for more usable data from the querying perspective. This research presents considerable evidence that the concept of a three-pronged solution to addressing the issue of anonymity during crime reporting in a resource-constrained environment is promising. This solution can further assist the law enforcement agencies to partner with third party in deriving useful crime pattern knowledge without infringing on users' privacy. In the future, this research can be extended to more than one low-income or middle-income countries.