Section: Overall Objectives
Overall Objectives
Ubiquitous and pervasive computing introduces the need for embedding and managing data in ever lighter and specialized computing devices (personal digital assistants, cellular phones, sensors and chips for the ambient intelligence, transportation, healthcare, etc). In this context, the first objective of the SMIS project is the definition of core database technologies tackling the hardware constraints of highly specialized computing devices. Alongside, by making the information more accessible and by multiplying the transparent ways of its acquisition, ubiquitous and pervasive computing induce new threats on data confidentiality. More generally, preserving the confidentiality of personal data spread among a large variety of sources (mobiles, smart objects as well as corporate, commercial and public databases) has become a major challenge for the database community. Thus, the second objective pursued by the SMIS project is the definition of access control models preserving data confidentiality and privacy and the definition of tamper-resistant database architectures enforcing this control. These two objectives are detailed below.
Ubiquitous/pervasive data management: Important research efforts must be undertaken to capture the impact of each device's hardware constraints on database techniques and to set up co-design rules helping to calibrate the hardware resources of future devices in order to match specific application's requirements. This research direction is interested in storage and indexing models, query execution and optimization strategies, transaction protocols matching strong hardware constraints in terms of RAM, energy and communication bandwidth consumption. Electronic stable storage technologies (EEPROM, Flash, MEMS, etc) have also a considerable impact on the organization of the data at rest. Problems related to the interaction of ultra-light devices with a larger information system deserve also a particular attention (e.g., querying data disseminated among a large population of ultra-light devices, defining and managing ambient databases).
Data confidentiality and privacy: The increasing amount of sensitive data gathered in databases, and in particular of personal data, imposes the definition of fine-grain access control models. While access control in client-server relational database is roughly mature, new issues appear today: fine-grain access control over hierarchical and semi-structured data (e.g., XML), integration of privacy concern in the access control policies (e.g., users consent, usage control), access control administration over multiple distributed, heterogeneous and autonomous resources. A complementary issue we are interested in is the security (i.e., tamper-resistance) of the access control itself. Cryptographic techniques can be exploited to this end. While encryption is used successfully for years to secure communications, database encryption introduces difficult theoretical and practical problems: how to execute efficiently queries over encrypted data, how to conciliate declarative (i.e., predicate based) and dynamic access rights with encryption, how to distribute encryption keys between users sharing part of the database? We aim at providing accurate answers to these questions thanks to security models based on tamper-resistant hardware to query, update and share encrypted databases.
The complementarity of these two research issues is twofold. First, ubiquitous/pervasive data management generates specific confidentiality problems that must be tackled accurately. Hence, this first area of research is expected to feed the second one with relevant motivating examples. Second, data management techniques embedded in secured devices (e.g., smart cards, secured tokens) can be the foundation for new security models. For example, remote databases can be made secure by delegating part of the data management to a secured device. Thus, a strong cross-fertilization exists between these two research areas.
Beyond the scientific objectives detailed above, which are expected to generate publications in top level database and security conferences and journals, our ambition is to develop high quality prototypes that will serve two purposes: (1) validate our results on real hardware/software platforms and (2) integrate our results on real applications where data confidentiality is a primary concern (e.g., Electronic Health Record systems).
