Zhao Fan, Peng Changgen, Xu Dequan, Liu Yicen, Niu Kun, Tang Hanlin
State Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang 550025, China.
Guizhou Big Data Academy, Guizhou University, Guiyang 550025, China.
Comput Commun. 2023 May 1;205:118-126. doi: 10.1016/j.comcom.2023.04.003. Epub 2023 Apr 13.
With the outbreak of COVID-19, the government has been forced to collect a large amount of detailed information about patients in order to effectively curb the epidemic of the disease, including private data of patients. Searchable encryption is an essential technology for ciphertext retrieval in cloud computing environments, and many searchable encryption schemes are based on attributes to control user's search permissions to protect their data privacy. The existing attribute-based searchable encryption (ABSE) scheme can only implement the situation where the search permission of one person meets the search policy and does not support users to obtain the search permission through collaboration. In this paper, we proposed a new attribute-based collaborative searchable encryption scheme in multi-user setting (ABCSE-MU), which takes the access tree as the access policy and introduces the translation nodes to implement collaborative search. The cooperation can only be reached on the translation node and the flexibility of search permission is achieved on the premise of data security. ABCSE-MU scheme solves the problem that a single user has insufficient search permissions but still needs to search, making the user's access policy more flexible. We use random blinding to ensure the confidentiality and security of the secret key, further prove that our scheme is secure under the Decisional Bilinear Diffie-Hellman (DBDH) assumption. Security analysis further shows that the scheme can ensure the confidentiality of data under chosen-keyword attacks and resist collusion attacks.
随着新冠疫情的爆发，政府被迫收集大量患者的详细信息，以有效遏制该疾病的传播，其中包括患者的私人数据。可搜索加密是云计算环境中密文检索的一项关键技术，许多可搜索加密方案基于属性来控制用户的搜索权限，以保护其数据隐私。现有的基于属性的可搜索加密（ABSE）方案仅能实现单人搜索权限符合搜索策略的情况，不支持用户通过协作获取搜索权限。本文提出了一种新的多用户环境下基于属性的协作可搜索加密方案（ABCSE-MU），该方案以访问树作为访问策略，并引入翻译节点来实现协作搜索。协作仅在翻译节点上进行，在保证数据安全的前提下实现了搜索权限的灵活性。ABCSE-MU方案解决了单个用户搜索权限不足但仍需搜索的问题，使得用户的访问策略更加灵活。我们使用随机盲化来确保密钥的保密性和安全性，进一步证明了我们的方案在判定性双线性Diffie-Hellman（DBDH）假设下是安全的。安全性分析进一步表明，该方案能够在选择关键词攻击下确保数据的保密性，并抵抗合谋攻击。
