Verification Scheme Research Articles

Searchable encryption scheme for multiple cloud storage using double‐layer blockchain

SummaryWith the emergence of cloud storage security, how to ensure the security of cloud storage has become a research focus. The typical searchable encryption model consists of a single cloud service provider and has some unsolvable drawbacks. In this article, a new searchable encryption scheme in multi‐cloud was proposed based on blockchain. We first define a system model in multiple clouds and combine multiple cloud service providers to store data through a consortium chain. Then we store the encrypted documents and indexes in The Interplanetary File System (IPFS) and store the hash value and IPFS address of the documents in the blockchain. Our scheme can provide outsourced encrypted data retrieval based on multiple keywords, as well as verification schemes for the integrity of retrieved files. The theoretical analysis and experiments on real‐world data show the security and high performance of our scheme.

RETRACTED ARTICLE: A multimodal biometric authentication scheme based on feature fusion for improving security in cloud environment

In recent days, due to the advent of advanced technologies such as cloud computing, accessing data can be done anywhere at any time. Meanwhile, ensuring the data security is highly significant. Authentication plays a major role in preserving security via different access control mechanisms. As a recent trend, the biological information of the individual user is considered as verification scheme for the authentication process. Traits such as fingerprint, iris, ear or palm print are widely used to develop the authentication systems from its patterns. But, to increase the complexity of the user authentication and to ensure high security, more than a trait is combined together. In this paper, a multimodal authentication system is proposed by fusing the feature points of fingerprint, iris and palm print traits. Each trait has undergone the following procedures of image processing techniques such as pre-processing, normalization and feature extraction. From the extracted features, a unique secret key is generated by fusing the traits in two stages. False Acceptance Rate (FAR) and False Rejection Rate (FRR) metrics are used to measure the robustness of the system. This performance of the model is evaluated using three standard symmetric cryptographic algorithms such as AES, DES and Blowfish. This proposed model provides better security and access control over data in cloud environment.

A verifiable and privacy‐preserving multidimensional data aggregation scheme in mobile crowdsensing

AbstractMobile crowdsensing has become a popular data collection paradigm and has been extensively studied. Since the analysis of sensory data usually reveals privacy of mobile users, data aggregation technology is widely used to avoid privacy disclosure. However, traditional privacy‐preserving data aggregation schemes cannot provide aggregate statistics of multidimensional data in fine‐grained areas or resist collusive attacks. Moreover, the cloud platform is not fully trusted, and it is challenging to verify the correctness of data aggregation results. To provide privacy‐preserving multidimensional statistics within fine‐grained areas and verify results of data aggregation, we propose a verifiable privacy‐preserving data aggregation scheme in this article, which is based on data double‐masking, Shamir's secret sharing, and bilinear mapping. Specifically, a key agreement is utilized to establish mask seeds for users, while the users are required to extend mask values and generate the verification key with bilinear mapping. The cloud platform aggregates masked data and provides proof of computational results. Theoretical analysis demonstrates our scheme can protect data and location privacy, verify the aggregation results, and improve the rubustness to failure. The simulation results show that the computational overhead of mobile devices by using the proposed anticollusion scheme is better than that of homomorphic encryption. In addition, the computational complexity of task requesters is less than that of the PVPA scheme for verification of multidimensional aggregation results.

Improved algorithm for management of outsourced database

In cloud storage, clients outsource data storage to save local resources. Clients lose the controllability to manage data, and cloud service providers are usually untrusted. When clients want to know the correctness of data anytime, they have to verify the data. In this paper, we focus on the validation of outsourced data. We propose a data correctness verification scheme to verify the correctness of cloud storage data. By calculating the validation data, when the user queries the data, it is easy to determine whether the cloud server returns the correct data. In addition, clients can update outsourced data. When updating the database, the clients can verify the correctness of the updated file by calculating and producing a new proof. The efficiency of data validation is very high, and the computational overhead on the client side is very low. This scheme is suitable for the resource-constrained devices, such as wearable devices. This scheme can be applied in the IoT perception layer with limited computing resources.

Cloud based security on outsourcing using blockchain in E-health systems

Recently, Electronic Health Records (EHR) plays a significant role in E-health care system that allows data exchange of patient's health records via a portal designated by healthcare professionals. In this, the lack of confidentiality and integrity factors leads to different security issues on sensitive health information and causes a serious impact on a patient's life. To accomplish the security of medical data, we propose a new scheme named Elliptical Curve Certificateless Aggregate Cryptography Signature scheme (EC-ACS) for the public verification and auditing in the Medical Cloud Server (MCS) to secure EHR using authorized blockchain technology. In this, we use Elliptic Curve Cryptography (ECC) to encrypt medical data and the Certificateless Aggregate Signature scheme (CAS) to generate the digital signature for sharing and storing data in the cloud storage. This proposed scheme ensures security, privacy and safeguards the confidential information from unauthorized access in the cloud health system. Furthermore, the blockchain technique guarantees the integrity, traceability and secure storage of medical records in the cloud environment.

Region-Level Visual Consistency Verification for Large-Scale Partial-Duplicate Image Search

Most recent large-scale image search approaches build on a bag-of-visual-words model, in which local features are quantized and then efficiently matched between images. However, the limited discriminability of local features and the BOW quantization errors cause a lot of mismatches between images, which limit search accuracy. To improve the accuracy, geometric verification is popularly adopted to identify geometrically consistent local matches for image search, but it is hard to directly use these matches to distinguish partial-duplicate images from non-partial-duplicate images. To address this issue, instead of simply identifying geometrically consistent matches, we propose a region-level visual consistency verification scheme to confirm whether there are visually consistent region (VCR) pairs between images for partial-duplicate search. Specifically, after the local feature matching, the potential VCRs are constructed via mapping the regions segmented from candidate images to a query image by utilizing the properties of the matched local features. Then, the compact gradient descriptor and convolutional neural network descriptor are extracted and matched between the potential VCRs to verify their visual consistency to determine whether they are VCRs. Moreover, two fast pruning algorithms are proposed to further improve efficiency. Extensive experiments demonstrate the proposed approach achieves higher accuracy than the state of the art and provide comparable efficiency for large-scale partial-duplicate search tasks.

An Efficient Integrity Verification and Authentication Scheme over the Remote Data in the Public Clouds for Mobile Users

The digitalization of the modern world and its applications seem to be integrated more with the mobile phones than with any other communication devices. Since the mobile phones have become ubiquitous with applications for nearly all users, they have become a preferred choice for uploading the sensitive information to the cloud servers. Though the drive for data storage in cloud servers is implicit due to its pay-per-use policies, the manipulation of the data present in the cloud servers by hackers and hardware failure incidents, as happened in Amazon cloud servers in 2011, necessitates the demand for data verification at regular intervals over the data stored in the remote servers. In this line, modern day researchers have proposed many novel schemes for ensuring the remote data integrity, but they suffer from attacks or overheads due to computation and communication. This research paper provides solutions in three dimensions. Firstly, a novel scheme is introduced to verify the integrity of the data stored in the remote cloud servers in the context of mobile users. The second dimension is that of reducing the computational and communication overheads during the auditing process than the previous works. The third dimension securely authenticates the mobile user during the auditing process and the dynamic data operations such as block modification, insertion, and deletion. Moreover, the proposed protocol is provably secure exhibiting soundness, completeness, and data privacy making it an ideal scheme for implementation in the real-world applications.

Sanctuary Novel Mechanism for Data Verification Scheme of Email Services

The paper is all about data verification scheme of E-mail services for a company by developing an intranet mail service for the company through the generation of password. Project is based on sending and delivering the mail. This sequence is faced in a company when a manager has to deliver an authentified mail to a client, which sometime delivered to unknown recipients. To maintain confidential document or record of a company, it is must the mails are authentified by correct user credentials. If any confidential mails are sent by clients, it should not be viewed by the personal assistant. The confidential mails will be blocked which can be viewed only by the permission of the admin. The intranet mail service application will contain User Registration, User Login and Admin Login for providing a better mailing service to the company with more security. The possible outcomes of the project are creating an intranet mail service application for maintaining confidential documents, creating required authentication to send or receive restricted mails

Cloud data integrity verification scheme for associated tags

In typical cloud storage systems such as storage systems for electronic health records (EHRs), users must regularly update sensitive files that are stored in the cloud. Leakage of the operation logs (OLs) will cause severe damage to users. Therefore, it is critical to develop secure auditing techniques for verifying users OLs. Under this scenario, we propose a novel auditing scheme that realizes secure detection for users OLs. In this design, the OLs are grouped according to the types of operations, the verification tags (VTs) of the OLs are calculated by associating an operation relationship, and the cloud data integrity verification is realized by randomly detecting the correctness of VTs. We introduce a homomorphic hash function into the integrity verification of the OLs, and the verification result for the sensitive information is derived from the verification result for the public information, thereby realizing stronger privacy protection. Furthermore, our scheme also achieves efficient handling of data dynamics. The security analysis and experimental verification indicate that our scheme is secure and efficient.

A secure and efficient certificateless batch verification scheme with invalid signature identification for the internet of things

With the continuously developing wireless communication technique, the Internet of Things (IoT) has been deployed in various domains. In the IoT, numerous smart devices exchange information transparently and seamlessly via the open channel to provide intelligent and convenient services for the citizens. Due to the vulnerable nature of the communication channel, ensuring data authenticity of the transmitted information is a challenging issue. Certificateless signature (CLS) is regarded as an appropriate cryptographical primitive to protect data authenticity in the IoT. However, the existing CLS schemes are infeasible for the practical IoT systems, since individual verification causes network congestion and service delay in the face of massive service requests. To improve the verification efficiency, plenty of CLS schemes with batch verification have been investigated to verify multiple signatures quickly at once. Despite the improvement of verification efficiency, these schemes have poor efficiency or security issue. Furthermore, the batch verification failure cannot be settled in these schemes, which reduces the advantage of batch verification significantly. Motivated by the above problems, this paper presents a secure and efficient CLS scheme with batch verification and invalid signature identification. The proposed scheme is provably secure under the random oracle model. The comprehensive comparison analysis demonstrates that the presented scheme is superior to the related works in security and performance.

Immunohistochemical Validation of Rare Tissues and Antigens With Low Frequency of Occurrence: Recommendations From The Anatomic Pathology Patient Interest Association (APPIA).

Laboratories worldwide find it challenging to identify enough tissues and cases for verification and validation studies of low-incidence, rare antigens. These antigens have a low frequency of occurrence in the population, or have little or no expression in normal tissues. Validation studies are essential to assure testing standardization before introducing a new instrument, product, or test into the clinical laboratory. The College of American Pathologists has published comprehensive guidelines for the verification and validation of new immunohistochemical tests introduced into the laboratory menu. Within the guidelines, varied numbers of cases are required for nonpredictive versus predictive markers. However, regarding low-incidence antigens, the laboratory medical director determines the extent of validation required. Recommended practical solutions available to clinical laboratories for low-incidence validation include developing internal resources using the laboratory information system with retrospective and prospective search(s) of archival material and purchase of tissue microarray blocks, slides, or cell lines from external resources. Utilization of homemade multitissue blocks has proved to be extremely valuable in biomarker research and demonstrated great utility in clinical immunohistochemistry laboratories. Participation in External Quality Assessment program(s) may provide insufficient numbers or the ability to calculate concordance rates. However, supplementation with in-house tissues can allow a laboratory to reach the optimal number of cases needed for verification and/or validation schemes. An alternative approach is conducting a thorough literature search and correlating staining patterns of the new test to the expected results. These solutions may be used uniquely or together to assure consistent standardized testing.

Analysis on the performance of aldosterone testing and the results of EQA in China

Objective To evaluate the performance of aldosterone testing in China through the External Quality Assessment (EQA) and improve the testing quality of aldosterone. Methods Two kinds of EQA program for aldosterone were carried out in China, one of which is Routine EQA and the other is Trueness verification scheme. Lyophilized sera with 5 concentration levels were used as quality control of Routine EQA. The results were grouped according to the instrument. Target values and the coefficient of variation (CV) were calculated in each group. Trueness verification scheme was verified by using frozen human sera of 3 concentration levels determined by the reference method, and the bias of each instrument group from the target value was calculated. Results 272 laboratories submitted the testing results, and 91.6% of laboratories used chemiluminescence method. The maximum CV was obtained by radioimmunoassay and liquid chromatography mass spectrometry, and the robust CVs were 14.6%-33.4% and 43.5%-53.9%, respectively. For chemiluminescence methods, the robust group CV was less than 10%. The results of the Trueness verification scheme showed that liquid chromatography mass spectrometry method was the most accurate method, with biases of -7.9%, 8.9% and -0.7% for the three quality controls. Diasorin system had the more accurate results deviated from the target by 58.7%, 7.9% and -2.1%, respectively. The results of other chemiluminescence methods were negatively correlated with the sample concentration, and one of them with a bias of 479%. Conclusions The accuracy and comparability of aldosterone among laboratories in China are not satisfactory. Reagent manufacturers and laboratories should pay more attention to EQA, with the aldosterone results traceable to SI unit, and improve the test quality of aldosterone. Key words: Aldosterone; Quality control; Reference standards

Outsourced data integrity verification based on blockchain in untrusted environment

Outsourced data, as the significant component of cloud service, has been widely used due to its convenience, low overhead, and high flexibility. To guarantee the integrity of outsourced data, data owner (DO) usually adopts a third party auditor (TPA) to execute the data integrity verification scheme. However, during the verification process, DO cannot fully confirm the reliability of the TPA, and handing over the verification of data integrity to the untrusted TPA may lead to data security threats. In this paper, we focus on the problem of integrity verification of outsourced data in untrusted environment, that is, how to improve the security and efficiency of data integrity verification without utilizing untrusted TPA. To address the problem, we design a decentralized model based on blockchain consisting of some collaborative verification peers (VPs), each of which maintains a replication of the entire blockchain to avoid maliciously tampering with. Based on the model, we present an advanced data integrity verification algorithm which allows DO to store and check the verification information by writing and retrieving the blockchain. In addition, in order to improve the concurrent performance, we extend the algorithm by introducing the verification group (VG) constituting by some VPs organized by Inner-Group and Inter-Group consensus protocols. We conduct a completed security analysis as well as extensive experiments of our proposed approach, and the evaluation results demonstrate that our proposed approaches achieve superior performance.

Verification of security measures for smart substations based on visualized simulation

Due to the application of network communication for smart substations, the security measures of secondary equipment become implicit and complicated, which makes it difficult to verify the security measures. This article proposes a strategy for the verification of security measures for smart substations. Firstly, based on SCD, ICD and SPCD, the model for smart substations is constructed. Secondly, a formalized description mechanism for security measures is presented for computer processing. Finally, the security measures are verified through the simulation on MATLAB/Simulink. Through the application of a 220kV smart substation, it proves that the verification scheme is intuitional and effective.

Issues of privacy policy conflict in mobile social network

Privacy protection in mobile social networks is a hot issue in current research. Various privacy protection policies have been proposed. However, the conflict of privacy protection policies inevitably occurs. In this article, aiming at the personalized privacy protection model proposed in our published paper, we analyzed the possible conflict between privacy policies and comprehensively considered the policy conflict brought by the resource-level relationship; meanwhile, we proposed a scheme of consistency verification for privacy policy to improve the previous personalized privacy protection model. We also verified the practical effects of the improved model by experiments on synthetic data sets.

Encryption-Then-Compression-Based Copyright Protection Scheme for E-Governance

This article discusses a joint encryption-then-compression-based watermarking scheme for copyright protection and content verification in variety of applications. In this scheme, redundant discrete wavelet transform is first performed to decompose the nonsubsampled contourlet transform host image, and then, the singular value decomposition is applied on transformed coefficients of the host image. Furthermore, same procedure is applied for both watermarks (image and PAN No.). The PAN number is encoded by the quick response (QR) code before hiding into the host image. Finally, 2D hyperchaotic encryption is used to encrypt the watermarked image to make our method more secure against attacks. After this, the encrypted image is then compressed via Huffman compression to reduce the size of the image at an acceptable quality of the reconstructed image. Furthermore, performance outcomes confirm better robustness and security of the method while preserving the image quality.

Identifying smartphone users based on how they interact with their phones

The continuous advancement in the Internet of Things technology allows people to connect anywhere at any time, thus showing great potential in technology like smart devices (including smartphones and wearable devices). However, there is a possible risk of unauthorized access to these devices and technologies. Unfortunately, frequently used authentication schemes for protecting smart devices (such as passwords, PINs, and pattern locks) are vulnerable to many attacks. USB tokens and hardware keys have a risk of being lost. Biometric verification schemes are insecure as well as they are susceptible to spoofing attacks. Maturity in sensor chips and machine learning algorithms provides a better solution for authentication problems based on behavioral biometrics, which aims to identify the behavioral traits that a user possesses, such as hand movements and waving patterns. Therefore, this research study aims to provide a solution for passive and continuous authentication of smartphone users by analyzing their activity patterns when interacting with their phones. The motivation is to learn the physical interactions of a smartphone owner for distinguishing him/her from other users to avoid any unauthorized access to the device. Extensive experiments were conducted to test the performance of the proposed scheme using random forests, support vector machine, and Bayes net. The best average recognition accuracy of 74.97% is achieved with the random forests classifier, which shows the significance of recognizing smartphone users based on their interaction with the phones.

Generic Dynamic Data Outsourcing Framework for Integrity Verification

Ateniese et al. proposed the Provable Data Possession (PDP) model in 2007. Following that, Erway et al. adapted the model for dynamically updatable data and called it the Dynamic Provable Data Possession (DPDP) model. The idea is that a client outsources her files to a cloud server and later challenges the server to obtain a proof of the integrity of her data. Many schemes have later been proposed for this purpose, all following a similar framework. We analyze dynamic data outsourcing schemes for the cloud regarding security and efficiency and show a general framework for constructing such schemes that encompasses existing DPDP-like schemes as different instantiations. This generalization shows that a dynamic outsourced data integrity verification scheme can be constructed given black-box access to an implicitly-ordered authenticated data structure. Moreover, for blockless verification efficiency, a homomorphic verifiable tag scheme is also needed. We investigate the requirements and conditions these building blocks should satisfy, using which one may easily check the applicability of a given building block for dynamic data outsourcing. Our framework serves as a guideline/tutorial/survey and enables us to provide a comparison among different building blocks that existing schemes employ.

Predicting Low-Level Wind Shear Using 200-m-Resolution NWP at the Hong Kong International Airport

Abstract“Low-level wind shear” is a known aviation safety hazard and refers to a sustained change in head wind encountered by an aircraft during takeoff or landing. Because of their small spatiotemporal scales and high variability, automatic alerting of wind shears at airports around the world is almost exclusively detection based (using remote sensing equipment). Numerical modeling studies so far mainly cover individual cases and lack systematic validation. This paper presents the first statistical evaluation of numerical weather prediction (NWP) model performance in predicting low-level wind shear at a major international airport over a 2-yr continuous period. The 200-m-resolution Aviation Model (AVM) of the Hong Kong Observatory is used to generate runway-specific wind shear forecasts at 1-min output intervals for the Hong Kong International Airport (HKIA), known for its susceptibility to wind shear occurrence. The AVM forecasts are then validated against over 800 actual reports of wind shear by aircraft pilots over the two major arrival runway corridors, 07LA and 25RA, at HKIA between 2014 and 2015 using a verification scheme with the same level of spatiotemporal stringency as operational alerting systems at HKIA. With “relative operating characteristic” analysis, positive skill is consistently observed across both runway corridors throughout the study period and across all considered forecast lead times out to 6 h ahead. This study serves to establish and document the current capability of fine-resolution NWP in predicting the phenomenon of low-level wind shear for aviation weather applications.

Towards trusted and efficient SDN topology discovery: A lightweight topology verification scheme

Discovering network topology is critical for Software-defined Networking (SDN) controllers to establish the centralized network visibility. However, during the process of SDN topology discovery, SDN controllers tend to suffer from the topology poisoning attacks due to a lack of authentication. Existing methods can hardly solve the problems of SDN topology poisoning attacks in a comprehensive and lightweight manner. To fill this gap, we propose TrustTopo, a lightweight and efficient SDN topology verification scheme. Specifically, we first establish a security threat model to analyze key service vulnerabilities in the SDN controller. Then, we design two verification strategies (i.e., host location verification and link verification) to cope with the host hijacking attack and link fabrication attack, respectively. In more detail, our host location verification strategy is based on the path tracking and asynchronous rollback technique, while our link verification strategy is designed using the chaotic model and dynamic password generation technique. We implement TrustTopo in the mainstream SDN controller (i.e., Floodlight). Experimental results in the Mininet virtual network environment show that TrustTopo can effectively secure the network topology against the representative topology poisoning attacks, while bringing negligible runtime overhead.