Dynamic searchable symmetric encryption (DSSE) enables the data owner to outsource its database (document sets) to an untrusted server and make searches and updates securely and efficiently. Conjunctive DSSE can process conjunctive queries that return the documents containing multiple keywords. However, a conjunctive search could leak the keyword pair result pattern (KPRP), where attackers can learn which documents contain any two keywords involved in the query. File-injection attack shows that KPRP can be utilized to recover searched keywords. To protect data effectively, DSSE should also achieve forward privacy, i.e., hides the link between updates to previous searches, and backward privacy, i.e., prevents deleted entries being accessed by subsequent searches. Otherwise, the attacker could recover updated/searched keywords and records. However, no conjunctive DSSE scheme in the literature can hide KPRP in sub-linear search efficiency while guaranteeing forward and backward privacy. In this work, we propose the first sub-linear KPRP-hiding conjunctive DSSE scheme (named HDXT) with both forward and backward privacy guarantees. To achieve these three security properties, we introduce a new cryptographic primitive: Attribute-updatable Hidden Map Encryption (AUHME). AUHME enables HDXT to efficiently and securely perform conjunctive queries and update the database in an oblivious way. In comparison with previous work that has weaker security guarantees, HDXT shows comparable, and in some cases, even better performance.

Verifiable Dynamic Searchable Symmetric Encryption (VDSSE) enables users to securely outsource databases (document sets) to cloud servers and perform searches and updates. The verifiability property prevents users from accepting incorrect search results returned by a malicious server. However, we discover that the community currently only focuses on preventing malicious behavior from the server but ignores incorrect updates from the client, which are very likely to happen since there is no record on the client to check. Indeed most existing VDSSE schemes are not sufficient to tolerate incorrect updates from the client. For instance, deleting a nonexistent keyword-identifier pair can break their correctness and soundness. In this paper, we demonstrate the vulnerabilities of a type of existing VDSSE schemes that fail them to ensure correctness and soundness properties on incorrect updates. We propose an efficient fault-tolerant solution that can consider any DSSE scheme as a black-box and make them into a fault-tolerant VDSSE in the malicious model. Forward privacy is an important property of DSSE that prevents the server from linking an update operation to previous search queries. Our approach can also make any forward secure DSSE scheme into a fault-tolerant VDSSE without breaking the forward security guarantee. In this work, we take FAST [1] (TDSC 2020), a forward secure DSSE, as an example, implement a prototype of our solution, and evaluate its performance. Even when compared with the previous fastest forward private construction that does not support fault tolerance, the experiments show that our construction saves 9× client storage and has better search and update efficiency.

Recently, several practical attacks raised serious concerns over the security of searchable encryption. The attacks have brought emphasis on forward privacy, which is the key concept behind solutions to the adaptive leakage-exploiting attacks, and will very likely to become a must-have property of all new searchable encryption schemes. For a long time, forward privacy implies inefficiency and thus most existing searchable encryption schemes do not support it. Very recently, Bost (CCS 2016) showed that forward privacy can be obtained without inducing a large communication overhead. However, Bost's scheme is constructed with a relatively inefficient public key cryptographic primitive, and has poor I/O performance. Both of the deficiencies significantly hinder the practical efficiency of the scheme, and prevent it from scaling to large data settings. To address the problems, we first present FAST, which achieves forward privacy and the same communication efficiency as Bost's scheme, but uses only symmetric cryptographic primitives. We then present FASTIO, which retains all good properties of FAST, and further improves I/O efficiency. We implemented the two schemes and compared their performance with Bost's scheme. The experiment results show that both our schemes are highly efficient.

The features of GGO nodules need to be obtained such as volume, mean, variance of Ground-Glass Opacity Nodules by boundaries of GGO nodules to judge malignant or benign of lung tumors. However, radiologists need to look for the slices including the GGO nodule in CT volume data. It is time-consuming. This paper proposes a semi-supervised learning method based on the label propagation. First, a GGO nodule was labeled in one slice. Secondly, similarities were found by comparing with the labeled GGO nodule using the values of pixels. Finally, the GGO nodule of the other slices was labeled by iteration. Experimental results showed that the approach of this paper can find slices including the GGO nodule. The approach is better than the nearest neighbor algorithm in performance.