Browsing by Author "Srivatsa, M."

Now showing 1 - 4 of 4

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How to trust a few among many
(Springer International Publishing, 2017) Etuk, A.; Norman, T. J.; Şensoy, Murat; Srivatsa, M.; Computer Science; ŞENSOY, Murat
The presence of numerous and disparate information sources available to support decision-making calls for efficient methods of harnessing their potential. Information sources may be unreliable, and misleading reports can affect decisions. Existing trust and reputation mechanisms typically rely on reports from as many sources as possible to mitigate the influence of misleading reports on decisions. In the real world, however, it is often the case that querying information sources can be costly in terms of energy, bandwidth, delay overheads, and other constraints. We present a model of source selection and fusion in resource-constrained environments, where there is uncertainty regarding the trustworthiness of sources. We exploit diversity among sources to stratify them into homogeneous subgroups to both minimise redundant sampling and mitigate the effect of certain biases. Through controlled experiments, we demonstrate that a diversity-based approach is robust to biases introduced due to dependencies among source reports, performs significantly better than existing approaches when sampling budget is limited and equally as good with an unlimited budget.
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Location attestation and access control for mobile devices using GeoXACML
(Elsevier, 2017-02) Arunkumar, S.; Soyluoglu, Berker; Şensoy, Murat; Srivatsa, M.; Rajarajan, M.; Computer Science; ŞENSOY, Murat; Soyluoglu, Berker
Access control has been applied in various scenarios in the past for negotiating the best policy. Solutions with XACML for access control has been very well explored by research and have resulted in significant contributions to various sectors including healthcare. In controlling access to the sensitive data such as medical records, it is important to guarantee that the data is accessed by the right person for the right reason. Location of access requestor can be a good indication for his/her eligibility and reasons for accessing the data. To reason with geospatial information for access control, Geospatial XACML (eXtensible Access Control Markup Language) is proposed as a standard. However, there is no available implementation and architecture for reasoning with Geospatial XACML policies. This paper proposes to extend XACML with geohashing to implement geospatial policies. It also proposes an architecture for checking reliability of the geospatial information provided by clients. With a case study, we demonstrate how our framework can be used to control the privacy and data access of health service data in handheld devices.
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Privacy enforcement through policy extension
(IEEE, 2016) Arunkumar, S.; Srivatsa, M.; Soyluoglu, Berker; Şensoy, Murat; Cerutti, F.; Computer Science; ŞENSOY, Murat; Soyluoglu, Berker
Successful coalition operations require contributions from the coalition partners which might have hidden goals and desiderata in addition to the shared coalition goals. Therefore, there is an inevitable risk-utility trade-off for information producers due to the need-to-know vs. need-to-hide tension, which must take into account the trustworthiness of the other coalition partners. A balance is often achieved by deliberate obfuscation of the shared information. In this paper, we show how to integrate obfuscation capabilities within the current OASIS standard for access control policies, namely XACML.
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TIDY: A trust-based approach to information fusion through diversity
(IEEE, 2013) Etuk, A.; Norman, T. J.; Şensoy, Murat; Bisdikian, C.; Srivatsa, M.; Computer Science; ŞENSOY, Murat
Trust and reputation are significant components in open dynamic systems for making informed and reliable decisions. State-of-the-art information fusion models that exploit these mechanisms generally rely on reports from as many sources as possible. Situations exist, however, where seeking evidence from all possible sources is unrealistic. Querying information sources is costly especially in resource-constrained environments, in terms of time and bandwidth. In addition, reports from multiple sources expose one to the risk of double-counting evidence, introducing an extra challenge of distinguishing fact from rumour. This paper describes TIDY (Trust-based Information fusion through DiversitY), a trust-based approach to information fusion that exploits diversity among information sources in order to select a small number of candidates to query for evidence, and to minimise the effect of correlated evidence and bias. We demonstrate that reliable decisions can be reached using evidence from small groups of individuals. We show empirically that our approach is robust in contexts of variable trust in information sources, and to a degree of deception.