Unified Model for Data Security -- A Position Paper

Raja Naeem Akram, Ryan K. L. Ko

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

1 Citation (Scopus)


One of the most crucial components of modern Information Technology (IT) systems is data. It can be argued that the majority of IT systems are built to collect, store, modify, communicate and use data, enabling different data stakeholders to access and use it to achieve different business objectives. The confidentiality, integrity, availability, auditability, privacy, and quality of the data is of paramount concern for end-users ranging from ordinary consumers to multi-national companies. Over the course of time, different frameworks have been proposed and deployed to provide data security. Many of these previous paradigms were specific to particular domains such as military or media content providers, while in other cases they were generic to different verticals within an industry. There is a much needed push for a holistic approach to data security instead of the current bespoke approaches. The age of the Internet has witnessed an increased ease of sharing data with or without authorisation. These scenarios have created new challenges for traditional data security. In this paper, we study the evolution of data security from the perspective of past proposed frameworks, and present a novel Unified Model for Data Security (UMDS). The discussed UMDS reduces the friction from several cross-domain challenges, and has the functionality to possibly provide comprehensive data security to data owners and privileged users.
Original languageEnglish
Title of host publicationIEEE 13th International Conference on Trust, Security and Privacy in Computing and Communications
PublisherIEEE Computer Society Press
Number of pages9
ISBN (Electronic)978-1-4799-6513-7
Publication statusPublished - 1 Sept 2014


  • Security
  • Data
  • Data Security
  • Access Control
  • Cloud Security
  • Digital Rights Management
  • Cryptography
  • Data Ownership


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