Milan Petkovic

Secure Data Management

In this talk we explored the economics of cloud computing. We identified cost trade-offs and postulated the key principles of cloud outsourcing that define when cloud deployment is appropriate and why. The results may surprise and are especially interesting in understanding cybersecurity aspects that impact the appeal of clouds. We outlined and investigated some of the main research challenges on optimizing for these trade-offs. If you came to this talk you were also very likely to find out exactly how many US dollars you need to spend to break your favorite cipher, or send one of your bits over the network.

Secure management of personal health records by applying attribute-based encryption

The confidentiality of personal health records is a major problem when patients use commercial Web-based systems to store their health data. Traditional access control mechanisms have several limitations with respect to enforcing access control policies and ensuring data confidentiality. In particular, the data has to be stored on a central server locked by the access control mechanism, and the data owner loses control on the data from the moment when the data is sent to the server. Therefore, these mechanisms do not fulfill the requirements of data outsourcing scenarios where the third party storing the data should not have access to the plain data, and it is not trusted to enforce access policies. In this paper, we present a new variant of ciphertext-policy attribute-based encryption (CP-ABE) scheme which is used to enforce patient/organizational access control policies. In CP-ABE, the data is encrypted according to an access policy over a set of attributes. The access policy specifies which attributes a user needs to have in order to decrypt the encrypted data. Once the data is encrypted, it can be safely stored in an untrusted server such that everyone can download the encrypted data but only authorized users who satisfy the access policy can decrypt. The novelty of our construction is that attributes can be from two security domains: social domain (e.g. family, friends, or fellow patients) and professional domain (e.g. doctors or nurses).

Security, privacy, and trust in modern data management

Privacy and Security Issues in a Digital World.- Privacy in the Law.- Ethical Aspects of Information Security and Privacy.- Data and System Security.- Authorization and Access Control.- Role-Based Access Control.- XML Security.- Database Security.- Trust Management.- Trusted Platforms.- Strong Authentication with Physical Unclonable Functions.- Privacy Enhancing.- Privacy-Preserving Data Mining.- Statistical Database Security.- Different Search Strategies on Encrypted Data Compared.- Client-Server Trade-Offs in Secure Computation.- Federated Identity Management.- Accountable Anonymous Communication.- Digital Asset Protection.- An Introduction to Digital Rights Management Systems.- Copy Protection Systems.- Forensic Watermarking in Digital Rights Management.- Person-Based and Domain-Based Digital Rights Management.- Digital Rights Management Interoperability.- DRM for Protecting Personal Content.- Enhancing Privacy for Digital Rights Management.- Selected Topics on Privacy and Security in Ambient Intelligence.- The Persuasiveness of Ambient Intelligence.- Privacy Policies.- Security and Privacy on the Semantic Web.- Private Person Authentication in an Ambient World.- RFID and Privacy.- Malicious Software in Ubiquitous Computing.

Content-based video retrieval by integrating spatio-temporal and stochastic recognition of events

As amounts of publicly available video data grow the need to query this data efficiently becomes significant. Consequently content-based retrieval of video data turns out to be a challenging and important problem. We address the specific aspect of inferring semantics automatically from raw video data. In particular, we introduce a new video data model that supports the integrated use of two different approaches for mapping low-level features to high-level concepts. Firstly, the model is extended with a rule-based approach that supports spatio-temporal formalization of high-level concepts, and then with a stochastic approach. Furthermore, results on real tennis video data are presented, demonstrating the validity of both approaches, as well us advantages of their integrated use.

Making sense of big data in health research: Towards an EU action plan

Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of “big data” for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health and healthcare for all Europeans.

Multi-modal extraction of highlights from TV Formula 1 programs

As amounts of publicly available video data grow, the need to automatically infer semantics from raw video data becomes significant. In this paper, we focus on the use of dynamic Bayesian networks (DBN) for that purpose, and demonstrate how they can be effectively applied for fusing the evidence obtained from different media information sources. The approach is validated in the particular domain of Formula I race videos. For that specific domain we introduce a robust audiovisual feature extraction scheme and a text recognition and detection method. Based on numerous experiments performed with DBN, we give some recommendations with respect to the modeling of temporal and atemporal dependences within the network. Finally, we present the experimental results for the detection of excited speech and the extraction of highlights, as well as the advantageous query capabilities of our system.

Content-Based Video Retrieval

Recent advances in multimedia technologies allow the capture and storage of video data with relatively inexpensive computers. Furthermore, the new possibilities offered by the information highways have made a large amount of video data publicly available. However, without appropriate search techniques all these data are hardly usable. Users are not satisfied with the video retrieval systems that provide analogue VCR functionality. They want to query the content instead of the raw video data. For example, a user analysing a soccer video will ask for specific events such as goals. Content-based search and retrieval of video data becomes a challenging and important problem. Therefore, the need for tools that can manipulate the video content in the same way as traditional databases manage numeric and textual data is significant.

A Home Healthcare System in the Cloud--Addressing Security and Privacy Challenges

Cloud computing is an emerging technology that is expected to support Internet scale critical applications which could be essential to the healthcare sector. Its scalability, resilience, adaptability, connectivity, cost reduction, and high performance features have high potential to lift the efficiency and quality of healthcare. However, it is also important to understand specific risks related to security and privacy that this technology brings. This paper focuses on a home healthcare system based on cloud computing. It introduces several use cases and draws an architecture based on the cloud. A comprehensive methodology is used to integrate security and privacy engineering process into the software development lifecycle. In particular, security and privacy challenges are identified in the proposed cloud-based home healthcare system. Moreover, a functional infrastructure plan is provided to demonstrate the integration between the proposed application architecture with the cloud infrastructure. Finally, the paper discusses several mitigation techniques putting the focus on patient-centric control and policy enforcement via cryptographic technologies, and consequently on digital rights management and attribute based encryption technologies.

A reference model for reputation systems

Recent advances in ICT have led to a vast and expeditious development of e-services and technology. Trust is a fundamental aspect for the acceptance and adoption of these new services. Reputation is commonly employed as the measure of the trustworthiness of users in on-line communities. However, to facilitate their acceptance, reputation systems should be able to deal with the trust challenges and needs of those services. The aim of this survey is to propose a framework for the analysis of reputation systems. We elicit the requirements for reputations metrics along with the features necessary to achieve such requirements. The identied requirements and features form a reference framework which allows an objective evaluation and comparison of reputation systems. We demonstrate its applicability by analyzing and classifying a number of existing reputation systems. Our framework can serve as a reference model for the analysis of reputation systems. It is also helpful for the design of new reputation systems as it provides an analysis of the implications of design choices.

Privacy-Preserving Digital Rights Management

DRM systems provide a means for protecting digital content, but at the same time they violate the privacy of users in a number of ways. This paper addresses privacy issues in DRM systems. The main challenge is how to allow a user to interact with the system in an anonymous/pseudonymous way, while preserving all security requirements of usual DRM systems. To achieve this goal, the paper proposes a set of protocols and methods for managing user identities and interactions with the system during the process of acquiring and consuming digital content. Furthermore, a method that supports anonymous transfer of licenses is discussed. It allows a user to transfer a piece of content to another user without the content provider being able to link the two users. Finally, the paper demonstrates how to extend the rights of a given user to a group of users in a privacy preserving way. The extension hides the group structure from the content provider and at the same time provides privacy among the members of the group.