Biblio
Filters: Author is Adi, Kamel [Clear All Filters]
Access Pattern Hiding in Searchable Encryption. 2021 8th International Conference on Future Internet of Things and Cloud (FiCloud). :107—114.
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2021. Cloud computing is a technology that provides users with a large storage space and an enormous computing power. For privacy purpose, the sensitive data should be encrypted before being outsourced to the cloud. To search over the outsourced data, searchable encryption (SE) schemes have been proposed in the literature. An SE scheme should perform searches over encrypted data without causing any sensitive information leakage. To this end, a few security constraints were elaborated to guarantee the security of the SE schemes, namely, the keyword privacy, the trapdoor unlinkability, and the access pattern. The latter is very hard to be respected and most approaches fail to guarantee the access pattern constraint when performing a search. This constraint consists in hiding from the server the search result returned to the user. The non respect of this constraint may cause sensitive information leakage as demonstrated in the literature. To fix this security lack, we propose a method that allows to securely request and receive the needed documents from the server after performing a search. The proposed method that we call the access pattern hiding (APH) technique allows to respect the access pattern constraint. An experimental study is conducted to validate the APH technique.
A Privacy-Preserving Authentication Model Based on Anonymous Certificates in IoT. 2021 Wireless Days (WD). :1–6.
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2021. This paper proposes an anonymity based mechanism for providing privacy in IoT environment. Proposed scheme allows IoT entities to anonymously interacting and authenticating with each other, or even proving that they have trustworthy relationship without disclosing their identities. Authentication is based on an anonymous certificates mechanism where interacting IoT entities could unlinkably prove possession of a valid certificate without revealing any incorporated identity-related information, thereby preserving their privacy and thwarting tracking and profiling attacks. Through a security analysis, we demonstrate the reliability of our solution.