Public-Key Encryption with Keyword Search (PEKS) enables servers to search over encrypted files without decrypting them and without leaking any additional information. To date, numerous PEKS schemes have been proposed in the literature; however, most of them fail to support fine-grained search permission control, especially in the time dimension. The few existing schemes that support time-based search permission control typically rely on trusted hardware, making them impractical for large-scale deployment. In this paper, we propose a novel cryptographic primitive called Delay Public-Key Encryption with Keyword Search (DPEKS), which leverages time-lock puzzles to achieve time-based access control. We formally define the system and security models of DPEKS, where the latter explicitly incorporates the time dimension. Even if an adversary obtains the user's private key, it cannot generate a valid search trapdoor before the designated time. We give an instance of this cryptographic primitive and prove its security under the defined security model. We conduct simulation experiments across three platforms—personal computers, mobile phones, and IoT devices—and compare the performance of our scheme with that of the PETKS scheme and the classical PEKS scheme. Experimental results demonstrate that the proposed scheme effectively enforces time-based search permissions and is suitable for deployment across a variety of application scenarios.

Wildcard keyword search enables the client to perform wildcard queries over the encrypted database. Wildcard symmetric searchable encryption (wildcard SSE) appears to be a practical solution. However, it is vulnerable to false positives in query results due to its reliance on keyword feature extraction and approximate membership data structures. In contrast, wild-card asymmetric searchable encryption (wildcard ASE) ensures accuracy, but its practicality is limited by the high search latency incurred by public-key operations. To achieve the best of wildcard SSE and ASE, we propose F-WSSE, a novel false-positive-free wildcard SSE scheme in the symmetric-key setting that offers both high search efficiency and guaranteed accuracy. Specifically, we design a new cryptographic construction, ciphertext-masked symmetric-key hidden vector encryption (CM-SHVE), which ensures ciphertext randomness and features a concise secret key. Based on CM-SHVE, F-WSSE achieves query results without false positives in the symmetric-key setting. Additionally, we leverage a fragmentation technique to support dual-wildcard keyword queries, i.e., queries containing both single-and multi-character wildcards. Our evaluation demonstrates that the search efficiency of F-WSSE outperforms the existing wildcard ASE scheme by several orders of magnitude, while delivering comparable search performance to the state-of-the-art wildcard SSE schemes.

Wildcard symmetric searchable encryption enables the server to perform efficient wildcard keyword search over encrypted data while preserving data privacy. Currently, one of the most promising wildcard SSE framework can achieve sublinear search complexity by combining characteristic extraction techniques with the traditional membership test structure Bloom filter. However, all existing constructions consume significant storage space due to the storage expansion inherent in Bloom filters. In this paper, we initially consider the storage compression for wildcard SSE based on characteristic extraction while maintaining its sublinear search efficiency. Specifically, we propose a new practical wildcard SSE scheme, , which achieves optimized storage by using xor filter. On average, each characteristic saves 15 . Finally, we implement and compare our proposed scheme to the state-of-the-art scheme presented by Zhang et al. obtains an 86 22× , and speeds up search time by three orders of magnitude.

Volume-hiding encrypted multi-map (EMM) allows the client to efficiently search on encrypted data while concealing the real volume of values for the queried key, thereby mitigating privacy-compromising attacks that depend on volume knowledge. However, most of the volume-hiding EMMs focus on single keyword queries, leaving the design of a volume-hiding conjunctive-keyword EMM a significant challenge. In this paper, we first propose a performance-optimized volume-hiding single-keyword EMM by adopting binary fuse filter, BF2 MM, which serves as the crucial component for volume-hiding conjunctive-keyword EMM. We then introduce a generic construction dubbed vCMM for volume-hiding conjunctive query, relying on a novel index structure from merely symmetric-key cryptographic tools. We further instantiate it to a practical volume-hiding conjunctive-keyword EMM, (BFCMM)-C-2, which features nearly optimal query communication complexity and storage overhead. In addition, we extend our proposals to non-interactive DP-variants DP-BF2 MM and DP-(BFCMM)-C-2 to provide tunable trade-offs between performance and privacy. Finally, we provide a thorough comparison with the existing volume-hiding conjunctive-keyword EMM OXTMM. Experimental results show a significant performance improvement of (BFCMM)-C-2, with over a 2x storage saving, a 90x increase in setup efficiency, and roughly 180x speedup in search latency compared to OXTMM, respectively.

Vector Commitment (VC) enables one to commit to a vector, and then the element at a specific position can be opened, with proof of consistency to the initial commitment. VC is a powerful primitive with various applications, including stateless cryptocurrencies. Recently, matrix commitment Matproofs (Liu and Zhang CCS 2022), as an extension of VC, has been proposed to reduce the communication and computation complexity of VC-based cryptocurrencies. However, Matproofs requires linear-sized public parameters, and the aggregated proof size may also increase linearly with the number of individual proofs aggregated. Additionally, the proof updating process involves a third party, known as Proof-Serving Nodes (PSNs), which leads to extra storage and communication overhead. In this paper, we first propose a multi-dimensional variant of matrix commitment and construct a new matrix commitment scheme for two-dimensional matrix, called 2D-Xproofs, which achieves optimal aggregated proof size without using PSNs. Furthermore, we present a highly maintainable three-dimensional scheme, 3D-Xproofs, which updates all proofs within sublinear time in the size of the committed matrix without PSNs’ assistance. More generally, we could further increase the matrix dimensionality to achieve more efficient proof updates. Finally, we demonstrate the security of our schemes, showing that both schemes are position binding. We also implement both schemes, and the results indicate that our schemes enjoy constant-sized aggregated proofs and sublinear-sized public parameters, and the proof update time in 3D-Xproofs is 2.5 × faster than Matproofs.

Secure join queries over encrypted databases, the most expressive class of SQL queries, have attracted extensive attention recently. The state-of-the-art JXT (Jutla et al. ASIACRYPT 2022) enables join queries on encrypted relational databases without pre-computing all possible joins. However, JXT can merely support join queries over two tables (in encrypted databases) with some high-entropy join attributes. In this paper, we propose an equi-join query protocol over two tables dubbed JXT+, that allows the join attributes with arbitrary names instead of JXT requiring the identical name for join attributes. JXT+ reduces the query complexity from.. (l(1) center dot l(2)) to.. (l(1)) as compared to JXT, where l(1) and l(2) denote the numbers of matching records in two tables respectively. Furthermore, we present JXT++, the first equi-join queries across three or more tables over encrypted databases without pre-computation. Specifically, JXT++ supports joins of arbitrary attributes, i.e., all attributes (even low-entropy) can be candidates for join, while JXT requires high-entropy join attributes. In addition, JXT++ can alleviate sub-query leakage on three or more tables, which hides the leakage from the matching records of two-table join. Finally, we implement and compare our proposed schemes with the state-of-the-art JXT. The experimental results demonstrate that both of our schemes are superior to JXT in search and storage costs. In particular, JXT+ (resp., JXT++) brings a saving of 49% (resp., 68%) in server storage cost and achieves a speedup of 51.7x (resp., 54.3x) in search latency.

Dynamic multi-user searchable symmetric encryption (DMUSSE) enables the data owner to dynamically outsource encrypted database to the cloud server and selectively share the search capability with data users. However, inter-user state synchronization is expensive but often necessary in multi-user setting. In addition, only a few works are proposed against the malicious servers that achieve verifiability (guarantee the integrity of query results) by deploying a Merkle tree for all database entries in a straightforward way, which is inevitably subject to logarithmic communication overhead. In this work, we propose a new verifiable DMUSSE scheme with improved performance, while maintaining user-server collusion resistance. Concretely, we first design an efficient and forward-and-backward-secure DMUSSE scheme with the aid of Hyperledger Fabric (a permissioned blockchain), greatly reducing synchronous communication and computation. In particular, our scheme does not reveal any information about uncorrupted users when corrupted users collude with an adversarial server. Then, we achieve efficient verifiability of query results based on multiset hash functions with O(1) communication cost. Finally, we compare our scheme with the state-of-the-art solutions O-μSE and Q-μSE (Chamani et al. TDSC 2021). Experimental results show that our scheme brings at least 90.9% communication savings, 2.75×, 109.2×, and 11.67× speedup in search, update, and verify time, respectively.

Data owners outsource their data to remote storage providers without keeping local replicas to save their precious storage resources. However, the ownership and management of data are separated after outsourcing. How to ensure the integrity and recoverability of outsourced data becomes a significant problem. Provable Data Possession (PDP) and Proofs of Retrievability (POR) are two cryptographic protocols that enable users to verify the integrity of outsourced data. Nevertheless, the state-of-the-art PDP and POR schemes either need users to perform the complicated audit tasks by themselves or delegate these tasks to a Third-Party Auditor (TPA). Moreover, these schemes are constructed on a centralized storage framework which vulnerably suffers single-point-of-failure. In this paper, we propose a blockchain-based decentralized self-auditing scheme with batch verification. Firstly, data owners outsource their data to decentralized storage nodes, which can achieve self-auditing based on blockchain without TPA. Secondly, our scheme uses Pedersen-based polynomial commitment to significantly reduce the number of authenticators. Furthermore, we propose a batch verification algorithm, which can verify multiple proofs from different storage nodes to improve the verification efficiency. Finally, we analyze the security of our scheme and implement a gas-efficient system prototype using the smart contracts of the Ethereum Reposten test network. The results demonstrate that the scheme is practical.

Verifiable Data Streaming (VDS) enables a resource-limited client to continuously outsource data to an untrusted server in a sequential manner while supporting public integrity verification and efficient update. However, most existing VDS schemes require the client to generate all proofs in advance and store them at the server, which leads to a heavy computation burden on the client. In addition, all the previous VDS schemes can perform batch query (i.e., retrieving multiple data entries at once), but are subject to linear communication cost l, where l is the number of queried data. In this paper, we first introduce a new cryptographic primitive named Double-trapdoor Chameleon Vector Commitment (DCVC), and then present an unbounded VDS scheme VDS1 with optimal communication cost in the random oracle model from aggregatable cross-commitment variant of DCVC. Furthermore, we propose, to our best knowledge, the first unbounded VDS scheme VDS2 with optimal communication and storage overhead in the standard model by integrating Double-trapdoor Chameleon Hash Function (DCH) and Key-Value Commitment (KVC). Both of our schemes enjoy constant-size public key. Finally, we demonstrate the efficiency of our two VDS schemes with a comprehensive performance evaluation.

The wide deployment of Internet of Things (IoT) devices enables the controller to continuously collect massive volume data in automation systems, and makes it possible to make intelligent decisions based on machine learning techniques. In fact, data‐driven intelligent automation systems have been common in the industrial community. Nevertheless, how to effectively store the collected stream data and ensure their integrity is still challenging. To this end, the notion of verifiable data streaming (VDS) protocol, which enables a client to outsource the stream data to an untrusted server in a verifiable manner, was introduced. However, we argue that existing VDS protocols based on the chameleon authentication tree (CAT) are inefficient in the data update, since the whole CAT must be updated accordingly to avoid acute exposure of chameleon hashing. Thus, they are infeasible for intelligent automation systems that need to frequently update data. In this article, we first introduce a new primitive called double‐trapdoor chameleon hash tree (DCHT) based on the double‐trapdoor chameleon hash families, where each leaf of DCHT is calculated and fixed by using a double‐trapdoor chameleon hash family, making the entire DCHT always unchanged. Furthermore, we propose a novel VDS protocol based on the DCHT. Due to the distinctive properties of the underlying DCHT, the proposed VDS protocol has a constant update cost and more efficient than previous VDS protocols based on CAT. Besides, we prove that the proposed VDS protocol is secure in the standard model.

Verifiable conjunctive search in Searchable Symmetric Encryption (VSSE) allows a client to search multiple keywords with sublinear computation overhead and ensures the integrity of search results. However, the state-of-the-art VSSE schemes are either probabilistically verifiable or have significant communication overhead. In this paper, we propose an efficient VSSE scheme that achieves a balance between communication and computation overheads. Our scheme supports public and private verification for different scenarios by utilizing RSA accumulator and has constant-size public parameters. Finally, we prove that our scheme is secure against malicious servers and conclude that our scheme is efficient by comparing and analyzing the performance.

Structured Encryption (STE), introduced by Chase and Kamara (ASIACRYPT 2010), enables to perform efficient private queries over an encrypted data structure. Very recently, Kamara and Moataz (EUROCRYPT 2019) formalized the notion of volume-hiding STE to mitigate the volume attack, and presented the first concrete volume-hiding encrypted multi-map (EMM) scheme with densest subgraph transform, which can ensure that the volume of values associated with the queried key is hidden to the adversary. To achieve better performance, Patel et al. (CCS 2019) designed a volume-hiding EMM scheme from cuckoo hash dubbed dprfMM. However, we observe that all the existing volume-hiding EMMs focus only on queries over a single key. Although the state-of-the-art conjunctive queries scheme OXT (CRYPTO 2013) can achieve sub-linear search complexity for conjunctive queries, it reveals the real volumes of the queried keys. Therefore, it is desirable to explore the volume-hiding encrypted multi-maps supporting conjunctive queries. In this paper, we initiate the study of volume-hiding EMM supporting conjunctive queries. We present, to our best knowledge, the first volume-hiding conjunctive EMM scheme OXTMM. Compared with the state-of-the-art volume-hiding single-key EMM scheme dprfMM, our proposed OXTMM can guarantee that the real volume of each key is hidden while supporting efficient conjunctive queries, the query communication overhead is 2ℓ encrypted key/value pairs together with a succinct data structure Bloom filter, where ℓ is the maximum volume of all keys. In addition, we prove the security of our proposed OXTMM and give a thorough efficiency analysis between our proposal and the existing constructions. Finally we implement OXTMM and compare it with the most efficient scheme . Experiments result demonstrates that OXTMM can achieve volume-hiding conjunctive queries with a moderate efficiency loss.

Blockchain allows clients to query and verify any transactions, which requires the clients to maintain the entire blockchain database locally. This approach is inadvisable because the blockchain database is an append-only ledger and incurs significant maintenance overhead. Very recently, blockchain light client has attracted considerable concerns, which relies on a third party (i.e., a full node) to perform query processing and verification. However, the dishonest full node may return an incorrect and incomplete result of the query requests. Therefore, it remains a challenging issue to achieve secure, efficient, and rich verifiable queries for light clients. In this paper, we propose an efficient verifiable Boolean range query scheme for light clients on the blockchain database. Firstly, we design a new authenticated data structure, polynomial commitment B $$^+$$ -tree (PCB-tree), which efficiently ensures the correctness and completeness of Boolean range queries for blockchain light clients. Secondly, we provide a tunable trade-off between query time and communication overhead by autonomously setting the fanout size of the PCB-tree. Moreover, our scheme can support batch processing to reduce query complexity and proof size. Finally, security analysis and performance evaluation show that our proposed scheme is secure and practical.

With the widespread use of Internet-of-Things (IoT) devices, edge computing is becoming a popular technology for processing and storing data distributed at the edge of the networks. However, the new paradigm also faces a major security challenge: how to ensure the reliability and integrity of data in distributed edge storage servers? In this paper, we propose a robust and auditable distributed data storage (Radds) scheme to support a secure and dependable edge storage in edge computing. Firstly, based on homomorphic verifiable authenticator and regenerating code technique, the proposed scheme allows to check the integrity of data in distributed edge storage servers and guarantees data repairability in case of data corruption. Moreover, the server with corrupted data also can be deduced from integrity proofs, and a proxy is introduced for data reparation to release edge nodes from online burden and computation costs. Secondly, the proposed scheme can protect the privacy of original data from the third party auditor by blinding the encoding coefficients with a keyed pseudorandom function. Thirdly, the proposed scheme supports flexible scalability, i.e., dynamic joining and exiting of the edge nodes. Moreover, even if some data are not collected temporarily, they still can be supplemented to the encoded data file by an efficient way and the integrity checking and data reparation can be performed normally. Finally, security analysis and performance evaluation demonstrate that the proposed scheme is secure and highly efficient.

Insects are exposed to cadmium stress since cadmium pollution has increasingly become a serious global environmental issue. However, until now few studies have paid attention to the effect of heavy metals on insect reproductive behaviors. In our study, the courtship behaviors, mating behaviors and fecundity of beet armyworm Spodoptera exigua (Lepidoptera: Noctuidae) exposed to different concentrations of cadmium in artificial diets at larval stage were studied. The results showed that cadmium stress changed the courtship rhythm by significantly advancing or delaying the courtship starting time. Low dose of cadmium (0.2 mg/kg) increased the courtship frequency in the first two scotophases, but in the fourth phase, the two cadmium treatments reduced the frequency. The total courtship duration was significantly shortened in the first six scotophases except high dose of cadmium treatment (51.2 mg/kg) in the sixth dark phase. Paired adults did not mate after the seventh scotophase under low cadmium exposure, while high cadmium stress made the paired adults just copulate in the first four scotophases. The daily mating rate and total mating rate decreased with the increase in cadmium concentration. The number of eggs of low cadmium treatment was higher than that of control, but the difference was not significant; the number of eggs in high cadmium treatment was lower than that of control and low cadmium treatment. Our results indicate that cadmium exposure can disrupt the courtship rhythm for females and has negative influences on copulation behavior and high cadmium stress can reduce fecundity. Hence, the insect population increase will be affected by heavy metal pollution. Our study will provide scientific reference for environmental risk assessment of heavy metal pollution.

Heavy metal pollution is becoming an increasingly serious problem globally, and cadmium pollution ranks first in the world. Reproduction in insects is affected by cadmium stress in a dose-dependent manner. However, no previous studies have examined the molecular mechanisms underlying the influence of cadmium exposure on insect reproduction. In this study, RNA-Seq was used to investigate changes in ovary gene expression in newly emerged female beet army worms. The beet armyworms were reared under 4 cadmium concentrations: 0 mg/kg (control), low 0.2 mg/kg (L), medium 12.8 mg/kg (M) and high 51.2 mg/kg (H). Compared with the control (CK), a total of 3453 differentially expressed genes (DEGs) were identified in L cadmium stress, including 1791 up-regulated and 1662 down-regulated candidates; in L versus M groups, 982 up-regulated and 658 down-regulated DEGs; and in M versus H groups, 6508 up-regulated and 2000 down-regulated DEGs were identified and the expression patterns of ten genes were verified by q PCR. Many of the identified DEGs were relevant to juvenile hormone and molting hormone biosynthesis, insulin secretion, estrogen signaling, amino acid metabolism and lipid biosynthesis. These data will provide a molecular prospective to understand the ecological risk of heavy metal pollution and are a resource for selecting key genes as targets in gene-editing/silencing technologies for sustainable pest management.

Three transgenic maize events (IE09S034, Shuangkang 12–5 and C0030.3.5) produced Cry1le, Cry1Ab/Cry2Aj and G10-EPSPS, Cry1Ab and EPSPS, respectively, all of which target the Asian corn borer. The oriental armyworm Mythimna separata (Walker) is the secondary target. In this study, the effects of the three Bt maizes on the development and survival of armyworm were studied. The results showed that IE09S034 had insecticidal activity against 1st instar larvae, and the survival rate of armyworm fed with Bt maize for 10 days was 46.2%, significantly lower than that of the control. The larvae at 3rd–6th instar were more tolerant of the Bt toxin than the early instar larvae. However, Shuangkang 12-5 had good insecticidal activity against 1st–5th instar larvae. The mortality was nearly 100% when the larvae were fed with Shuangkang 12-5 before 3rd instar, and the toxin had quick-acting efficacy. This event significantly inhibited the development of armyworm; that is, the larval duration of the 3rd and 4th instar larvae fed with Shuangkang 12-5 was prolonged by 4.5 and 3.0 days, respectively. The pupal weight and egg number were also significantly lower than those of the control. For C0030.3.5, it could control 1st–5th instar larvae effectively. The mortality rates were all over 50% if 1st–3rd larvae were fed with this event. The pupal weight of 4th–6th instar larvae fed with Bt maize were only 53.9, 56.8 and 54.6%, respectively, compared to that of the control. The number of eggs laid was significantly less than the control. The results indicate that all three transgenic maize events exhibit the potential to provide effective control of early instar larvae of armyworm, which can be commercialized in future to control lepidoptera pests such as Asian corn borer and armyworm.

In this paper we investigate the block numerical range and the existences of estimable decompositions of bounded linear operators on a separable Hilbert space. By using spectral measure, we show that there exists an estimable decomposition for the spectrum of every bounded normal operator. Furthermore, the corresponding result also holds for hyponormal operators with totally disconnected spectra. Finally, we obtain that for spectral operator, there exists an estimable decomposition, under quasi-nilpotent equivalence.

With growing popularity of cloud storage, the number of users of outsourcing data to cloud servers has increased dramatically. On the one hand, the rapidly increasing volume of data in the cloud is accompanied by a lot of data duplication. On the other hand, the cloud server stores only a unique copy of outsourced data in deduplication cloud storage system and the corruption or missing of the unique copy may bring immeasurable loss. Therefore, the file deduplication and integrity auditing are very important and how to securely and efficiently achieve them simultaneously needs to be settled urgently in academia and industry. In this paper, we propose a confidentiality-preserving deduplication cloud storage with public cloud auditing (CPDA). Firstly, our CPDA scheme achieves secure file deduplication on encrypted file, which supports public integrity auditing for the unique copy in the deduplication cloud storage system. Particularly, our CPDA scheme also realizes secure authentication tag deduplication. Secondly, our CPDA scheme utilizes the convergent encryption and random masking techniques to ensure data confidentiality during the file deduplication and integrity auditing process. Thirdly, our scheme not only supports each data owner to independently launch the integrity auditing of their own files, but also supports cloud server to periodically delegate the third party auditor to concurrently handle multiple auditing tasks to ensure the integrity of the outsourced files. Finally, the security of our scheme is formally proved and its performance is confirmed by numerical analyses and simulation experiments.