Projects per year
Privacy on the Web is typically managed by giving consent to individual Websites for various aspects of data usage. This paradigm requires too much human effort and thus is impractical for Internet of Things (IoT) applications where humans interact with many new devices on a daily basis. Ideally, software privacy assistants can help by making privacy decisions in different situations on behalf of the users. To realize this, we propose an agent-based model for a privacy assistant. The model identifies the contexts that a situation implies and computes the trustworthiness of these contexts. Contrary to traditional trust models that capture trust in an entity by observing large number of interactions, our proposed model can assess the trustworthiness even if the user has not interacted with the particular device before. Moreover, our model can decide which situations are inherently ambiguous and thus can request the human to make the decision. We evaluate various aspects of the model using a real-life data set and report adjustments that are needed to serve different types of users well.
|Title of host publication||Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, IJCAI-22|
|Editors||Luc De Raedt|
|Publisher||International Joint Conferences on Artificial Intelligence Organization|
|Number of pages||7|
|Publication status||Published - 29 Jul 2022|
|Event||The 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence - Vienna, Austria|
Duration: 23 Jul 2022 → 29 Jul 2022
|Conference||The 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence|
|Abbreviated title||IJCAI-ECAI 2022|
|Period||23/07/22 → 29/07/22|
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- 1 Finished
CONTEXT: Understanding the Role of Contexts in Managing Privacy Online Project
Kokciyan, N. & Ogunniye, G.
1/06/21 → 31/05/22