Now showing 1 - 4 of 4
  • Publication
    Protecting organizational data confidentiality in the cloud using a high-performance anonymization engine
    Data security remains a top concern for the adoption of cloud-based delivery models, especially in the case of the Software as a Service (SaaS). This concern is primarily caused due to the lack of transparency on how customer data is managed. Clients depend on the security measures implemented by the service providers to keep their information protected. However, not many practical solutions exist to protect data from malicious insiders working for the cloud providers, a factor that represents a high potential for data breaches. This paper presents the High-Performance Anonymization Engine (HPAE), an approach to allow companies to protect their sensitive information from SaaS providers in a public cloud. This approach uses data anonymization to prevent the exposure of sensitive data in its original form, thus reducing the risk for misuses of customer information. This work involved the implementation of a prototype and an experimental validation phase, which assessed the performance of the HPAE in the context of a cloud-based log management service. The results showed that the architecture of the HPAE is a practical solution and can efficiently handle large volumes of data.
  • Publication
    Ontology-Based Quality Evaluation of Value Generalization Hierarchies for Data Anonymization
    In privacy-preserving data publishing, approaches using Value Generalization Hierarchies (VGHs) form an important class of anonymization algorithms. VGHs play a key role in the utility of published datasets as they dictate how the anonymization of the data occurs. For categorical attributes, it is imperative to preserve the semantics of the original data in order to achieve a higher utility. Despite this, semantics have not being formally considered in the specification of VGHs. Moreover, there are no methods that allow the users to assess the quality of their VGH. In this paper, we propose a measurement scheme, based on ontologies, to quantitatively evaluate the quality of VGHs, in terms of semantic consistency and taxonomic organization, with the aim of producing higher-quality anonymizations. We demonstrate, through a case study, how our evaluation scheme can be used to compare the quality of multiple VGHs and can help to identify faulty VGHs.
  • Publication
    Enabling IPTV service assurance using OpenFlow
    One difficulty facing Internet Protocol Television (IPTV) service providers is the issue of monitoring and managing their service delivery network. An in-depth monitoring regime is required, which performs measurements within different networking devices. When network conditions deteriorate to the point where they could disrupt IPTV services, Network Operators (NOs) can use the measurements as a basis to reconfigure the network with minimal delay. OpenFlow (OF) presents a potential solution to this problem as it provides vendor-neutral access to the packet forwarding interface of the different hardware device types. This work investigates how OF can leverage video packet inspection measurements taken from within the IPTV service delivery network and combine these with of statistics to make decisions regarding routing in order to assure service quality.
      546Scopus© Citations 14
  • Publication
    Experience of developing an openflow SDN prototype for managing IPTV networks
    IPTV is a method of delivering TV content to endusers that is growing in popularity. The implications of poor video quality may ultimately be a loss of revenue for the provider. Hence, it is vital to provide service assurance in these networks. This paper describes our experience of building an IPTV Software Defined Network testbed that can be used to develop and validate new approaches for service assurance in IPTV networks. The testbed is modular and many of the concepts detailed in this tutorial may be applied to the management of other end-to-end services.
      1230Scopus© Citations 9