Multi-sensor network tracking research utilizing searchable encryption algorithm in the cloud computing environment.

Presently, the focus of target detection is shifting towards the integration of information acquired from multiple sensors. When faced with a vast amount of data from various sensors, ensuring data security during transmission and storage in the cloud becomes a primary concern. Data files can be encrypted and stored in the cloud. When using data, the required data files can be returned through ciphertext retrieval, and then searchable encryption technology can be developed. However, the existing searchable encryption algorithms mainly ignore the data explosion problem in a cloud computing environment. The issue of authorised access under cloud computing has yet to be solved uniformly, resulting in a waste of computing power by data users when processing more and more data. Furthermore, to save computing resources, ECS (encrypted cloud storage) may only return a fragment of results in response to a search query, lacking a practical and universal verification mechanism. Therefore, this article proposes a lightweight, fine-grained searchable encryption scheme tailored to the cloud edge computing environment. We generate ciphertext and search trap gates for terminal devices based on bilinear pairs and introduce access policies to restrict ciphertext search permissions, which improves the efficiency of ciphertext generation and retrieval. This scheme allows for encryption and trapdoor calculation generation on auxiliary terminal devices, with complex calculations carried out on edge devices. The resulting method ensures secure data access, fast search in multi-sensor network tracking, and accelerates computing speed while maintaining data security. Ultimately, experimental comparisons and analyses demonstrate that the proposed method improves data retrieval efficiency by approximately 62%, reduces the storage overhead of the public key, ciphertext index, and verifiable searchable ciphertext by half, and effectively mitigates delays in data transmission and computation processes.

Attribute-based multi-user collaborative searchable encryption in COVID-19.

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.

Specified keywords search scheme for EHR sharing.

Searchable encryption allows data users to search for encrypted files by keywords without restriction. However, electronic health record (EHR) contains sensitive information, and data users should search for and share EHR with restriction. If data users are not restricted when EHR is searched and shared, there is a high risk that EHR will be misused and reveal large amounts of private patient information. This paper proposes a specified keywords search scheme for EHR sharing based on searchable encryption and proxy re-encryption to address this problem. In the scheme, the data user searches with the keywords specified by the doctor and obtains EHR from the medical cloud. Proxy re-encryption is used to implement the sharing of EHR and privacy preservation securely. The security proof demonstrates that our scheme is secure against chosen keyword attack. Furthermore, the experimental results show that the scheme achieves computational efficiency.

A Novel Homomorphic Approach for Preserving Privacy of Patient Data in Telemedicine.

Globally, the surge in disease and urgency in maintaining social distancing has reawakened the use of telemedicine/telehealth. Amid the global health crisis, the world adopted the culture of online consultancy. Thus, there is a need to revamp the conventional model of the telemedicine system as per the current challenges and requirements. Security and privacy of data are main aspects to be considered in this era. Data-driven organizations also require compliance with regulatory bodies, such as HIPAA, PHI, and GDPR. These regulatory compliance bodies must ensure user data privacy by implementing necessary security measures. Patients and doctors are now connected to the cloud to access medical records, e.g., voice recordings of clinical sessions. Voice data reside in the cloud and can be compromised. While searching voice data, a patient's critical data can be leaked, exposed to cloud service providers, and spoofed by hackers. Secure, searchable encryption is a requirement for telemedicine systems for secure voice and phoneme searching. This research proposes the secure searching of phonemes from audio recordings using fully homomorphic encryption over the cloud. It utilizes IBM's homomorphic encryption library (HElib) and achieves indistinguishability. Testing and implementation were done on audio datasets of different sizes while varying the security parameters. The analysis includes a thorough security analysis along with leakage profiling. The proposed scheme achieved higher levels of security and privacy, especially when the security parameters increased. However, in use cases where higher levels of security were not desirous, one may rely on a reduction in the security parameters.

Towards efficient verifiable multi-keyword search over encrypted data based on blockchain.

Searchable symmetric encryption (SSE) provides an effective way to search encrypted data stored on untrusted servers. When the server is not trusted, it is indispensable to verify the results returned by it. However, the existing SSE schemes either lack fairness in the verification of search results, or do not support the verification of multiple keywords. To address this, we designed a multi-keyword verifiable searchable symmetric encryption scheme based on blockchain, which provides an efficient multi-keyword search and fair verification of search results. We utilized bitmap to build a search index in order to improve search efficiency, and used blockchain to ensure fair verification of search results. The bitmap and hash function are combined to realize lightweight multi-keyword search result verification, compared with the existing verification schemes using public key cryptography primitives, our scheme reduces the verification time and improves the verification efficiency. In addition, our scheme supports the dynamic update of files and realizes the forward security in update. Finally, formal security analysis proves that our scheme is secure against Chosen-Keyword Attacks (CKA), experimental analysis demonstrations that our scheme is efficient and viable in practice.

Blockchain-Based Access Control Scheme for Secure Shared Personal Health Records over Decentralised Storage.

Blockchain technology provides a tremendous opportunity to transform current personal health record (PHR) systems into a decentralised network infrastructure. However, such technology possesses some drawbacks, such as issues in privacy and storage capacity. Given its transparency and decentralised features, medical data are visible to everyone on the network and are inappropriate for certain medical applications. By contrast, storing vast medical data, such as patient medical history, laboratory tests, X-rays, and MRIs, significantly affect the repository storage of blockchain. This study bridges the gap between PHRs and blockchain technology by offloading the vast medical data into the InterPlanetary File System (IPFS) storage and establishing an enforced cryptographic authorisation and access control scheme for outsourced encrypted medical data. The access control scheme is constructed on the basis of the new lightweight cryptographic concept named smart contract-based attribute-based searchable encryption (SC-ABSE). This newly cryptographic primitive is developed by extending ciphertext-policy attribute-based encryption (CP-ABE) and searchable symmetric encryption (SSE) and by leveraging the technology of smart contracts to achieve the following: (1) efficient and secure fine-grained access control of outsourced encrypted data, (2) confidentiality of data by eliminating trusted private key generators, and (3) multikeyword searchable mechanism. Based on decisional bilinear Diffie-Hellman hardness assumptions (DBDH) and discrete logarithm (DL) problems, the rigorous security indistinguishability analysis indicates that SC-ABSE is secure against the chosen-keyword attack (CKA) and keyword secrecy (KS) in the standard model. In addition, user collusion attacks are prevented, and the tamper-proof resistance of data is ensured. Furthermore, security validation is verified by simulating a formal verification scenario using Automated Validation of Internet Security Protocols and Applications (AVISPA), thereby unveiling that SC-ABSE is resistant to man-in-the-middle (MIM) and replay attacks. The experimental analysis utilised real-world datasets to demonstrate the efficiency and utility of SC-ABSE in terms of computation overhead, storage cost and communication overhead. The proposed scheme is also designed and developed to evaluate throughput and latency transactions using a standard benchmark tool known as Caliper. Lastly, simulation results show that SC-ABSE has high throughput and low latency, with an ultimate increase in network life compared with traditional healthcare systems.

Public Key Encryption with Keyword Search in Cloud: A Survey.

With the popularization of cloud computing, many business and individuals prefer to outsource their data to cloud in encrypted form to protect data confidentiality. However, how to search over encrypted data becomes a concern for users. To address this issue, searchable encryption is a novel cryptographic primitive that enables user to search queries over encrypted data stored on an untrusted server while guaranteeing the privacy of the data. Public key encryption with keyword search (PEKS) has received a lot of attention as an important branch. In this paper, we focus on the development of PEKS in cloud by providing a comprehensive research survey. From a technological viewpoint, the existing PEKS schemes can be classified into several variants: PEKS based on public key infrastructure, PEKS based on identity-based encryption, PEKS based on attribute-based encryption, PEKS based on predicate encryption, PEKS based on certificateless encryption, and PEKS supporting proxy re-encryption. Moreover, we propose some potential applications and valuable future research directions in PEKS.

A secure location-based alert system with tunable privacy-performance trade-off.

Monitoring location updates from mobile users has important applications in many areas, ranging from public health (e.g., COVID-19 contact tracing) and national security to social networks and advertising. However, sensitive information can be derived from movement patterns, thus protecting the privacy of mobile users is a major concern. Users may only be willing to disclose their locations when some condition is met, for instance in proximity of a disaster area or an event of interest. Currently, such functionality can be achieved using searchable encryption. Such cryptographic primitives provide provable guarantees for privacy, and allow decryption only when the location satisfies some predicate. Nevertheless, they rely on expensive pairing-based cryptography (PBC), of which direct application to the domain of location updates leads to impractical solutions. We propose secure and efficient techniques for private processing of location updates that complement the use of PBC and lead to significant gains in performance by reducing the amount of required pairing operations. We implement two optimizations that further improve performance: materialization of results to expensive mathematical operations, and parallelization. We also propose an heuristic that brings down the computational overhead through enlarging an alert zone by a small factor (given as system parameter), therefore trading off a small and controlled amount of privacy for significant performance gains. Extensive experimental results show that the proposed techniques significantly improve performance compared to the baseline, and reduce the searchable encryption overhead to a level that is practical in a computing environment with reasonable resources, such as the cloud.

Public key encryption with temporary and fuzzy keyword search.

Public Key Encryption with Keyword Search (PEKS) is a desirable technique to provide searchable functionality over encrypted data in public key settings, which allows a user to delegate a third party server to perform the search operation on encrypted data by means of keyword search trapdoor without learning about the data. However, the existing PEKS schemes cannot be directly applied to practice due to keyword guessing attack or the absence of a mechanism to limit the lifetime of a trapdoor. By addressing these issues at the same time, this paper presents a Public Key Encryption Scheme with Temporary and Fuzzy Keyword Search (PETFKS) by using a fuzzy function and an encryption tree. The proposed PETFKS scheme is proven adaptively secure concerning keyword confidentiality and backward and forward secrecy in the random oracle model under the Bilinear Di e-Hellman assumption. Moreover, it is also proven selectively secure with regard to the resistance of keyword guessing attack. Furthermore, the security and e ciency analyses of the proposed scheme are provided by comparing to the related works. The analyses indicate that the proposed scheme makes a threefold contribution to the practical application of public key encryption with keyword search, namely o ering secure search operation, limiting the lifetime of a trapdoor and enabling secure time-dependent data retrieval.

Searchable Encryption Scheme for Personalized Privacy in IoT-Based Big Data.

The Internet of things (IoT) has become a significant part of our daily life. Composed of millions of intelligent devices, IoT can interconnect people with the physical world. With the development of IoT technology, the amount of data generated by sensors or devices is increasing dramatically. IoT-based big data has become a very active research area. One of the key issues in IoT-based big data is ensuring the utility of data while preserving privacy. In this paper, we deal with the protection of big data privacy in the data storage phase and propose a searchable encryption scheme satisfying personalized privacy needs. Our proposed scheme works for all file types including text, audio, image, video, etc., and meets different privacy needs of different individuals at the expense of high storage cost. We also show that our proposed scheme satisfies index indistinguishability and trapdoor indistinguishability.

Exploration of design and practice of disaster medical rescue monitoring system with privacy protection mechanism / 中华危重病急救医学

On?the?premise?of?fully?studying?the?disaster?medical?rescue?monitoring?mechanism?in?emergencies?at?home?and?abroad,?the?functional?requirements?of?the?domestic?disaster?medical?rescue?monitoring?system?was?analyzed?in?this?paper,?the?logical?framework?and?data?structure?of?disaster?medical?rescue?monitoring?system?with?privacy?protection?mechanism?was?designed?by?department?of?emergency?in?Chinese?PLA?General?Hospital,?department?of?information?management?in?School?of?Economics?and?Management?of?Beijing?Jiaotong?University,?the?School?of?Information?Management?of?Nanjing?University.?Three?major?functional?modules?were?realized?in?the?system:?reporter?information?management,?disaster?medical?rescue?data?upload,?and?disaster?medical?rescue?data?search.?Android?client?and?Web?client?were?developed?for?easy?access?to?the?system.?The?system?also?had?the?function?of?privacy?protection.?Based?on?symmetric?searchable?encryption?algorithm,?the?system?realized?the?encryption?storage?of?untrusted?servers?and?ensured?the?security?of?medical?and?health?data.?It?is?beneficial?for?the?further?development?and?improvement?of?disaster?medical?rescue?data?collection?in?China.

A Hybrid Scheme for Fine-Grained Search and Access Authorization in Fog Computing Environment.

In the fog computing environment, the encrypted sensitive data may be transferred to multiple fog nodes on the edge of a network for low latency; thus, fog nodes need to implement a search over encrypted data as a cloud server. Since the fog nodes tend to provide service for IoT applications often running on resource-constrained end devices, it is necessary to design lightweight solutions. At present, there is little research on this issue. In this paper, we propose a fine-grained owner-forced data search and access authorization scheme spanning user-fog-cloud for resource constrained end users. Compared to existing schemes only supporting either index encryption with search ability or data encryption with fine-grained access control ability, the proposed hybrid scheme supports both abilities simultaneously, and index ciphertext and data ciphertext are constructed based on a single ciphertext-policy attribute based encryption (CP-ABE) primitive and share the same key pair, thus the data access efficiency is significantly improved and the cost of key management is greatly reduced. Moreover, in the proposed scheme, the resource constrained end devices are allowed to rapidly assemble ciphertexts online and securely outsource most of decryption task to fog nodes, and mediated encryption mechanism is also adopted to achieve instantaneous user revocation instead of re-encrypting ciphertexts with many copies in many fog nodes. The security and the performance analysis show that our scheme is suitable for a fog computing environment.

Towards a privacy preserving cohort discovery framework for clinical research networks.

BACKGROUND: The last few years have witnessed an increasing number of clinical research networks (CRNs) focused on building large collections of data from electronic health records (EHRs), claims, and patient-reported outcomes (PROs). Many of these CRNs provide a service for the discovery of research cohorts with various health conditions, which is especially useful for rare diseases. Supporting patient privacy can enhance the scalability and efficiency of such processes; however, current practice mainly relies on policy, such as guidelines defined in the Health Insurance Portability and Accountability Act (HIPAA), which are insufficient for CRNs (e.g., HIPAA does not require encryption of data - which can mitigate insider threats). By combining policy with privacy enhancing technologies we can enhance the trustworthiness of CRNs. The goal of this research is to determine if searchable encryption can instill privacy in CRNs without sacrificing their usability. METHODS: We developed a technique, implemented in working software to enable privacy-preserving cohort discovery (PPCD) services in large distributed CRNs based on elliptic curve cryptography (ECC). This technique also incorporates a block indexing strategy to improve the performance (in terms of computational running time) of PPCD. We evaluated the PPCD service with three real cohort definitions: (1) elderly cervical cancer patients who underwent radical hysterectomy, (2) oropharyngeal and tongue cancer patients who underwent robotic transoral surgery, and (3) female breast cancer patients who underwent mastectomy) with varied query complexity. These definitions were tested in an encrypted database of 7.1 million records derived from the publically available Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS). We assessed the performance of the PPCD service in terms of (1) accuracy in cohort discovery, (2) computational running time, and (3) privacy afforded to the underlying records during PPCD. RESULTS: The empirical results indicate that the proposed PPCD can execute cohort discovery queries in a reasonable amount of time, with query runtime in the range of 165-262s for the 3 use cases, with zero compromise in accuracy. We further show that the search performance is practical because it supports a highly parallelized design for secure evaluation over encrypted records. Additionally, our security analysis shows that the proposed construction is resilient to standard adversaries. CONCLUSIONS: PPCD services can be designed for clinical research networks. The security construction presented in this work specifically achieves high privacy guarantees by preventing both threats originating from within and beyond the network.

An Efficient Searchable Encryption Against Keyword Guessing Attacks for Sharable Electronic Medical Records in Cloud-based System.

Preserving the privacy of electronic medical records (EMRs) is extremely important especially when medical systems adopt cloud services to store patients' electronic medical records. Considering both the privacy and the utilization of EMRs, some medical systems apply searchable encryption to encrypt EMRs and enable authorized users to search over these encrypted records. Since individuals would like to share their EMRs with multiple persons, how to design an efficient searchable encryption for sharable EMRs is still a very challenge work. In this paper, we propose a cost-efficient secure channel free searchable encryption (SCF-PEKS) scheme for sharable EMRs. Comparing with existing SCF-PEKS solutions, our scheme reduces the storage overhead and achieves better computation performance. Moreover, our scheme can guard against keyword guessing attack, which is neglected by most of the existing schemes. Finally, we implement both our scheme and a latest medical-based scheme to evaluate the performance. The evaluation results show that our scheme performs much better performance than the latest one for sharable EMRs.

An Improvement to a Multi-Client Searchable Encryption Scheme for Boolean Queries.

The migration of e-health systems to the cloud computing brings huge benefits, as same as some security risks. Searchable Encryption(SE) is a cryptography encryption scheme that can protect the confidentiality of data and utilize the encrypted data at the same time. The SE scheme proposed by Cash et al. in Crypto2013 and its follow-up work in CCS2013 are most practical SE Scheme that support Boolean queries at present. In their scheme, the data user has to generate the search tokens by the counter number one by one and interact with server repeatedly, until he meets the correct one, or goes through plenty of tokens to illustrate that there is no search result. In this paper, we make an improvement to their scheme. We allow server to send back some information and help the user to generate exact search token in the search phase. In our scheme, there are only two round interaction between server and user, and the search token has [Formula: see text] elements, where n is the keywords number in query expression, and [Formula: see text] is the minimum documents number that contains one of keyword in query expression, and the computation cost of server is [Formula: see text] modular exponentiation operation.

Fine-grained Database Field Search Using Attribute-Based Encryption for E-Healthcare Clouds.

An effectively designed e-healthcare system can significantly enhance the quality of access and experience of healthcare users, including facilitating medical and healthcare providers in ensuring a smooth delivery of services. Ensuring the security of patients' electronic health records (EHRs) in the e-healthcare system is an active research area. EHRs may be outsourced to a third-party, such as a community healthcare cloud service provider for storage due to cost-saving measures. Generally, encrypting the EHRs when they are stored in the system (i.e. data-at-rest) or prior to outsourcing the data is used to ensure data confidentiality. Searchable encryption (SE) scheme is a promising technique that can ensure the protection of private information without compromising on performance. In this paper, we propose a novel framework for controlling access to EHRs stored in semi-trusted cloud servers (e.g. a private cloud or a community cloud). To achieve fine-grained access control for EHRs, we leverage the ciphertext-policy attribute-based encryption (CP-ABE) technique to encrypt tables published by hospitals, including patients' EHRs, and the table is stored in the database with the primary key being the patient's unique identity. Our framework can enable different users with different privileges to search on different database fields. Differ from previous attempts to secure outsourcing of data, we emphasize the control of the searches of the fields within the database. We demonstrate the utility of the scheme by evaluating the scheme using datasets from the University of California, Irvine.

Secure medical information sharing in cloud computing.

Medical information sharing is one of the most attractive applications of cloud computing, where searchable encryption is a fascinating solution for securely and conveniently sharing medical data among different medical organizers. However, almost all previous works are designed in symmetric key encryption environment. The only works in public key encryption do not support keyword trapdoor security, have long ciphertext related to the number of receivers, do not support receiver revocation without re-encrypting, and do not preserve the membership of receivers. In this paper, we propose a searchable encryption supporting multiple receivers for medical information sharing based on bilinear maps in public key encryption environment. In the proposed protocol, data owner stores only one copy of his encrypted file and its corresponding encrypted keywords on cloud for multiple designated receivers. The keyword ciphertext is significantly shorter and its length is constant without relation to the number of designated receivers, i.e., for n receivers the ciphertext length is only twice the element length in the group. Only the owner knows that with whom his data is shared, and the access to his data is still under control after having been put on the cloud. We formally prove the security of keyword ciphertext based on the intractability of Bilinear Diffie-Hellman problem and the keyword trapdoor based on Decisional Diffie-Hellman problem.