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Aiming at the problems of being vulnerable to internal attacks and frequent link interruption in flying ad hoc networks (FANETs), a trust-based ad hoc on-demand multipath distance vector routing protocol (TAOMDV) is proposed. Firstly, a trust evaluation model is established. The packet forward ratio, trusted interaction and probe packet receive ratio are introduced as trust evaluation factors. An adaptive fuzzy trust aggregation network (AFTAN) is designed to calculate the direct trust of nodes, while the indirect trust of reliable neighbor nodes is integrated as well to calculate node trust. Secondly, the trust fluctuation penalty mechanism is introduced to resist the on-off attack in the trust model. Finally, the trust model is applied to ad hoc on-demand multipath distance vector (AOMDV) protocol. In the route discovery phase, the path trust is introduced as the basis for routing selection to establish a trusted path. In the route maintenance phase, the path alarm mechanism is applied to respond to malicious nodes in a timely manner. The simulation results show that the TAOMDV can not only defend against common attacks, such as black hole attack, gray hole attack and on-off attack, but also reduce the impact of topology changes and link interruptions. Compared with light-weight trust-enhanced ad hoc on-demand multipath distance vector (TEAOMDV), the proposed protocol effectively improves the delivery ratio and throughput of the network, which contributes to the better performance in routing overhead and average end-to-end delay.

Among many biometric technologies, fingerprint identification is the earliest, most pervasively applied, and cheapest biometric technology. It seamlessly corporates integrates sensors, biotechnology, electronic technology, digital image processing and pattern recognition. Fingerprint based identity authentication has expanded from the traditional criminal investigation to e-commerce, attendance, access control, credit card, endowment insurance system and other fields, and has become the popular biometric technology. As for the existing matching algorithm such as feature-point-based or image-based and so on, the accuracy and speed of fingerprint automatic identification are far from the satisfaction of many practical applications. In this work, we investigate the fingerprint feature extraction, and optimize the performance of fingerprint login authentication system by introducing a new feature extractor based on binary image through a brief thinning process. Aiming at the problems of low flexibility, high cost and low efficiency of algorithm in embedded chip of current fingerprint identification system, the automatic fingerprint identification system is comprehensively analyzed. Our proposed method can improve the design and optimization of the automatic fingerprint identification system. Our method can improve the accuracy of fingerprint image recognition in the automatic fingerprint identification system. Meanwhile, it can also improve the adaptability and stability of the automatic fingerprint identification system in various domains. Also, our method can substantially improve the feature extraction of agriculture products. Thereby, the classification task can be enhanced accordingly.

It is widely known that the analysis of fingerprints is a method which can lead to the correct identification of a person. It is lesser known that the accuracy of this method is endangered, when it comes to using digital technology, in order to store and compare information regarding fingerprints. The use of digital technology in analysing fingerprints is very important, because it enables various activities which are vital for a criminal investigation, for example the comparison between a certain fingerprint, found at crime scene, with the fingerprints which are stored in databases. However, storing fingerprints in a digital form is not a simple task, as the information must be protected from potential threats. A simple way to protect the information regarding fingerprints is to encrypt the information, but this means that, when information is transferred, the receptor must have the appropriate key, in order to decrypt the information. This leads to the necessity of a standard algorithm, which must be used by both the sender and the receiver. This paper analyses the challenges of creating such a standard algorithm and assesses the implications of standardization in fingerprinting.

Abstract: Watermarking is a process of embedding a message inside a digital signal like an image, video or text. It is used for several key reasons such as authenticity verification, ownership recognition and hidden communication. In this paper, we discuss about image watermarking, where secret messages are stored in images. Introduction: We propose a dual watermarking approach, which is based on Discrete Cosine Transform, Discrete Wavelet Transform and Singular Value Decomposition methods. This paper considers one watermark as robust and other water mark as fragile. Method: The robust watermark is embedded in Discrete Wavelet Transform- Singular Value Decomposition - domain and is used to transmit hidden messages. The fragile watermark is embedded in Discrete Cosine Transform domain and is used for verification of secret message of the robust watermark. The proposed algorithm is tested in the experimental results section and shows promising results against denoising, rotation, translation and cropping attacks. Result: The results show that the performance of the proposed algorithm in terms of mean squared error, structural similarity and peak signal to noise ratio is S4considerable as compared with the existing methods. Discussion: We present the comparison results with Himanshu et. al. in table 10, from which we can see that our method performs better with gaussian noise and rotational attack only lacking with Salt and Pepper noise. Fig. 7 and Fig. 8, in terms of resulting PSNR shows the variation of noise variance and degree of rotation. From the graphs it is evident that out method performs better against Gaussian and rotational attack. Conclusion: In this paper a dual watermarking method is proposed in which one watermark is fragile which is called as authentication watermark whereas the other watermark is robust and is called as the information watermark. The authentication watermark is embedded in the fractional part of DCT domain in the cover image and the information watermark is embedded in the diagonal vector of the LL sub-band.

The FIDO2 protocol allows users to perform online authentication by setting a public key and avoids the shortcomings of the traditional password authentication mechanism in terms of security. During transaction confirmation with the FIDO2 protocol, users must confirm the transaction message and then sign this message using a cryptographic signature scheme. However, it is a challenge to show that transaction messages are correct or trusted in practice. No available authenticator that supports the FIDO2 protocol uses trusted display hardware to guarantee the correctness of transaction messages. This paper proposes a trusted display of transaction messages by developing a lightweight and trusted base on hardware without a trusted execution environment (TEE). The proposed trusted display is easily applied in the FIDO2 protocol and resists four types of well-known attacks, such as malicious process tampering with display and occupying an authenticator. The experimental results indicate that the improved FIDO2 protocol slightly increases the processing overhead compared to the traditional protocol.

The need for developing a robust image watermarking method remains relevant. This is caused by the fact that existing watermarking methods are either not robust enough to various types of attacks on images, or computationally complex, or they are subject to the so-called numerical instability, i.e., accumulation of errors. This paper proposes the use of polar harmonic transformations as the basis of the method for image watermarking, including algorithms for embedding and extracting a watermark, and methods for multiple marking are proposed: multiple embedding and extracting by majority rule, multiple embedding and extracting according to the rule of greater similarity, embedding and extracting fragments of a watermark. The performance characteristics, such as robustness to various attacks, embedding and extraction time for a fixed area size, and maximum size of watermark, are measured using attacks implemented in StirMark BenchMark 4. The proposed method has been proven to be robust to many types of geometric attacks, JPEG-compression and other attacks, to have a high embedding and extraction rate, and to be numerically stable. The proposed method can be used to watermark JPEG images for copyright protection.

The safety of cloud services within a Trust Model System (TMS) is certainly compromised by a lack of defense against security threats as well as by inaccuracy of the trust results. Our proposed model addresses well-known security threats to the reputation trust model system, and is shown to deal with all possible potential attack threats, such as Sybil, on–off, and collusion attacks, by specifying the identity of users and tracking activities undertaken by them in order to easily track unauthorized consumers or attackers and to provide proof of any kind of data leakage. The TMS can also oversee the authorization of whoever uploads feedback into the system. It can also identify invalid feedback and discard it from the system. The algorithms of the TMS first establish a variety of trust criteria in which trustworthiness is calculated. Then, feedback from the cloud service provider nodes is accepted only according to the rules of the TMS. A consumer’s trust value is finally computed using a flexible system capable of guaranteeing a good balance of consumer trust and owners' feedback. Furthermore, a majority of the existing TMS models do not take full account of interaction importance, thus impeding the accuracy of the trust values, a shortcoming that has been rectified in our proposed model.

The design of Data Grids allows grid facilities to manage data files and their corresponding replicas from all around the globe. Replica selection in Data Grids is a complex service that selects the best replica place amongst several scattered places based on quality of service parameters. All replica selection algorithms look for the best replica for the requesting users without taking into account the limitation of their network or hardware capabilities to find the best fit. This leaves capable users with limited ability to connect with the best replica places without fully utilizing their download speed. It furthermore compromises the best replica places and shifts capable users to lower quality replica places and degrades the whole Data Grid environment. To improve quality of service parameters the solution we propose is, a matching algorithm that matches the capabilities of grid user with replica providers that are the best fit. This best-fit approach takes into account both the capabilities of grid users and the capabilities of replica places and creates matches of almost similar capabilities. Simulation results proved that the best-fit algorithm outperforms previous replica selection algorithms.

Digital Image Watermarking plays an important role when it comes to maintaining digital color picture authentication information. The proposed paper consists mainly of a digital watermarking scheme consisting of discrete wavelet transformation and involving the generation of pn sequence number to embed the watermark and also to extract the watermark from the host image. The technique suggested includes both embedding the watermark and removing it from the host file. Both the method of embedding and extraction consists of generating the pn sequence number values using the random numbers. The technique for all three of the RGB signal sources is included. The watermark symbol is located independently within the RGB image's red, green, and blue channels. The suggested technique further reveals the improved mode of digital watermarking of images through fragile watermarking of images and semi-fragile digital watermarking of images.

Biometrics is a statistical analysis of people's unique behavioral characteristics. The technology is used for CYBERSECURITY. The basics of biometric authentication is that to stop security breaches by analyzing a person’s unique behavioral characteristics. The term biometrics is derived from the Greek word’s “bios” meaning life and “metricos” meaning to measure. It refers to measurements of physical and biological characteristics of the human body. In this paper, we have studied some biometric methods such as facial recognition, iris recognition, Retinal Recognition, voice recognition. Keywords: Biometrics, Cybersecurity, Biometric Scan, Retinal Scan, Iris Scan, Gait, Voice Recognition.

The concept of cloud computing becomes more popular in latest years. Data storage is very important and valuable research field in cloud computing. Cloud based file sharing is a file sharing security in cloud. The required security from unauthorized access of the file in the cloud is provided by the encryption and decryption function. The admin can provide file access option to the authorized users. This facility limits the number and time of access of the shared files by the admin for the authorized user. Cloud data storage technology is the core area in cloud computing and solves the data storage mode of cloud environment. This project introduces the concept of cloud computing and cloud storage as well as the architecture of cloud storage firstly. Then we analyze the cloud data storage technology amazon web services, wasabi, Digital Ocean etc. We will improve the traditional file storage method and we will make a platform which will get more privileges. Keywords: Cloud, Storage, AWS, Wasabi, File Management, Files Storage, Files Sharing, DMS, CMS, Drive store, Private Cloud.

Seeking low distortion maps, it is usual to assume that areal and angular distortions are equally undesirable on the map. However, this might not be the case for certain map thematics. Should angular distortions be a bit less preferred to areal distortions, maps of unbalanced distortions may be developed. In this paper, the known analytic solution for the best cylindrical map projection is extended to such more general requirements by utilizing calculus of variations. The overall distortion of the resulted mappings are calculated and compared to each other to explore the distortion characteristics of these intentionally unbalanced map projections.

Biometric based remote authentication has been widely deployed. However, there exist security and privacy issues to be addressed since biometric data includes sensitive information. To alleviate these concerns, we design a privacy-preserving fingerprint authentication technique based on Diffie-Hellman (D-H) key exchange and secret sharing. We employ secret sharing scheme to securely distribute fragments of critical private information around a distributed network or group, which softens the burden of the template storage center (TSC) and the users. To ensure the security of template data, the user’s original fingerprint template is stored in ciphertext format in TSC. Furthermore, the D-H key exchange protocol allows TSC and the user to encrypt the fingerprint template in each query using a random one-time key, so as to protect the user’s data privacy. Security analysis indicates that our scheme enjoys indistinguishability against chosen-plaintext attacks and user anonymity. Through experimental analysis, we demonstrate that our scheme can provide secure and accurate remote fingerprint authentication.

In an age where e-commerce can provide a huge variety of different products online, customers still face the issue of the last mile challenge. The purpose of this paper is to find out if the last-m...

This article examines the impact of crowd logistics on the last mile parcel delivery for courier, express and parcel service providers. As the use of crowd logistics for the last mile holds both opportunities and challenges, it is unclear if the providers make use of the concept and how this might affect their business model. To identify the most important challenges and opportunities and to provide a definition for crowd local delivery, a systematic literature review was carried out. Findings from the review show that the integration of a crowd component offers good opportunities to create value. However, a number of problems still need to be solved. The findings have strategic importance for courier, express and parcel service providers and (new) crowd-based providers that aim to enter the market. For both, it is critical to determine an appropriate compensation scheme.

Privacy-preserving outsourced image sharing schemes can help relieve the local storage of image owners and protect images’ privacy by sending encrypted images to receivers, but they cannot prevent the decrypted image from being illegally distributed by illegal distributors. To cope with this issue, we propose a privacy-preserving image sharing scheme with illegal distributor detection (POISIDD). POISIDD embeds the authentication information of image receiver in the encrypted form based on discrete cosine transform (DCT) and privacy-preserving outsourced calculation on floating point numbers (POCF) . Moreover, in order to prevent all operations from being carried out by the single cloud which may lead to privacy disclosure, we adopt two platforms (Storage Center and Authentication Center) to achieve the embedding of authentication information(AI) by the communications between them. Furthermore, in order to better defend against attackers, we generate random vectors based on the original AI and use them instead of the AI as the embedded data. The aim of identifying illegal distributor will be achieved with the help of Authentication Center. The scheme is secure under the defined attack model, and its robustness under different attacks has been shown by experiments.

Authentication is needed for vital applications around the world. Applications that deal with sensitive information need to be kept secret through anyone type of authentication mode. Password-based smart card authentication is a generic model of authentication. Many password-based smart card authentication protocols have been proposed by Sangeetha et al., Giri et al., Jia et al. , Das et al. and so on. Those protocols provide protection against many type of attacks such as offline password guessing attack, server masquerading attack, user impersonation attack, privileged insider attack, but they are open to Crypt analytic attack, Cloning attack, and Reverse engineering attack. This paper proposes an authentication protocol that is termed as hrngRO- hybrid RNG by RO-PUF and SHA-256 for eUASBP simulated using AVISPA tool. It provides Ring Oscillator PUF based random number generator using the SHA-256 hash function. This hybrid combination of RNG makes hrngRO more secure against Crypt analytic attack, Cloning attack, Reverse engineering attack and makes the system even faster. Pre Early Wrong Password Detection is supported by hrngRO using bloom filters. hrngRO provides protection against many types of attacks like other authentication protocols and it also provides additional security by avoiding the above-mentioned attacks. Security of hrngRO is tested using AVISPA tool.

Wi-Fi device authentication is crucial for defending against impersonation attacks and information forgery attacks. Most of the existing authentication technologies rely on complex cryptographic algorithms. However, they cannot be supported well on the devices with limited hardware resources. A fine-grained device authentication technology based on channel state information (CSI) provides a noncryptographic method, which uses the CSI fingerprints for authentication since CSI can uniquely identify the devices. But long-term authentication based on CSI fingerprints is a challenging work. First, the CSI fingerprints are environment-sensitive, which means that the local authenticator should be updated to adapt to the changing channel state. Second, the local authenticator trained with old CSI fingerprints is outdated when users reconnect to the network after being offline for a long time, thus, it needs to be retrained in the access phase with new fingerprints. To tackle these challenges, we propose a CSI-based enhancing Wi-Fi device authentication protocol and an authentication framework. The protocol helps to collect new CSI fingerprints for authenticator’s training in access phase and performs the fingerprints’ dispersion analysis for authentication. In the association phase, it provides packet-level authentication and updates the authenticator with valid CSI fingerprints. The authenticator consists of an ensemble of small-scale autoencoders, which has high enough time efficiency for packet-level authentication and authenticator’s update. Experiments show that the accuracy of the framework is up to 98.7%, and the authenticator updating method can help the framework maintains high accuracy.

The privacy and utility are treated as a major factor in influencing the role of data privacy preservation in cloud environments. There exists a trade-off between these two factors, where one factor should compromise its functionality over the other. It is hence necessary to maintain both utility and privacy for a data offloaded or accessed across cloud computing environment. In this paper, we develop a utility privacy model that established utility using Deep Adaptive Clustering (DAC) and privacy using Elliptic Curve Digital Signature Algorithm (ECDSA). The utility is performed using clustering of the input datasets using DAC and the privacy is maintained using ECDSA. The simulation is conducted on specific datasets to test the efficacy of the model and the results shows improved accuracy on clustering, and efficient privacy metrics than existing methods.

This paper addresses several foundational questions in conceptual engineering: When is conceptual engineering needed? When we engage in conceptual engineering, should we think of ourselves primaril...

Over the last half-decade or so, since 2015, data privacy has become an important concern for organizations and consumers alike. Rules and regulations associated with data protection and privacy ha...

With the digital revolution and the Web 2.0 era, web-based social networks such as Facebook and others have become popular mediums for users to do various activities. While social networks are becoming increasingly popular, concerns about trust and trust-related issues are also growing among users. There are many applications where trust plays a vital role in users’ decision-making, requiring trust evaluation. There are several trust evaluation approaches for online social networks in the literature. However, the existing approaches focus only on certain aspects and believe that direct trust between participants is known. Thus, there is a need for a comprehensive trust evaluation approach that infers indirect trust and strives to measure direct trust. This paper proposes an interaction-based and graph-based hybrid approach that attempts to measure direct trust and infer indirect trust among users. Our direct trust measure method utilizes the most important features and similarities between users to measure direct trust. The proposed indirect trust inference method uses the graph theory concept to infer indirect trust. We implement the friend-request identification and the Sybil attack detection applications using the proposed direct trust measure method. Both the applications are evaluated on synthetic and real-world datasets. The empirical results show that the friend-request identification application achieves a high accuracy of 96.17%, and the Sybil attack detection application obtains a high detection rate of 93.20%. The false rates of both applications are very low. The proposed indirect trust inference method is efficient, and it outperforms the existing approach.

Aggregation statistics in mobile sensing are very useful for many applications. Therefore, a large number of privacy-preserving data aggregation protocols have been proposed, most of which however, only consider privacy-preserving sum aggregation. Non-additive aggregation statistics are also very important for their widely applications, such as max/min value and variance. The max/min aggregation can be regarded as a kind of comparison based aggregation because to obtain the max/min value, comparison among sensed data is required. Few protocols takes comparison based aggregation into consideration for the reason that it is difficult to implement privacy-preserving comparison. In this paper, we present two methods, i.e., a distributed one and a centralized one, for comparing all the sensed data in a privacy-preserving manner. And based on the two comparison methods, we propose two privacy-preserving comparison based data aggregation protocols, respectively, which are further applied to achieve max/min aggregation and top X aggregation.

At present, clients can outsource lots of complex and abundant computation, e.g., Internet of things (IoT), tasks to clouds by the “pay as you go” model. Outsourcing computation can save costs for clients and fully utilize the existing cloud infrastructures. However, it is hard for clients to trust the clouds even if blockchain is used as the trusted platform. In this article, we utilize the verification method as SETI@home by only two rational clouds, who hope to maximize their utilities. Utilities are defined as the incomes of clouds when they provide computation results to clients. More specifically, one client outsources two jobs to two clouds and each job contains n tasks, which include k identical sentinels. Two clouds can either honestly compute each task or collude on the identical sentinel tasks by agreeing on random values. If the results of identical sentinels are identical, then client regards the jobs as correctly computed without verification. Obviously, rational clouds have incentives to deviate by collusion and provide identical random results for a higher income. We discuss how to prevent collusion by using deposits, e.g., bit-coins. Furthermore, utilities for each cloud can be automatically assigned by a smart contract. We prove that, given proper parameters, two rational clouds will honestly send correct results to the client without collusion.

Individual entrepreneurial orientation training is a promising psychological intervention based on the Theory of Action Regulation that has contributed to the success of small business owners of de...

Wearable devices equipped with a multitude of compact, lightweight, biometric sensors are helpful in tracking the real-time physiological data for healthcare-related analysis. However, a survey of ...

In this paper, a novel reversible blind dual-color image watermarking algorithm is proposed by using singular value decomposition (SVD), Hachimoji Deoxyribonucleic Acid (HDNA) biogenetic encryption, coupled map lattice-based Tent–Sine system (TSS-CML) and mathematical Julia set. For watermark embedding, the watermark image is firstly encrypted using 8-bases HDNA sequences, TSS-CML and Julia set image. Then the encrypted HDNA watermark is obtained. Next, decompose the host image into equal non-overlapping blocks and utilize SVD on the randomly selected blocks. Further, embed the HDNA watermark through modifying the relation between the elements in the first column of the matrix U or V. The watermarked image can be eventually attained by carrying out the inverse SVD on all selected blocks. Also a reliable extraction algorithm is designed to recover the watermark from the possibly attacked watermarked images without resorting to the original image. Experimental and analysis results demonstrate that the proposed watermarking scheme has not only an excellent imperceptibility but a strong robustness against the common image processing attacks, geometric attacks and some composite attacks. In addition, the running time taken for hiding and exacting is about 1 s, which is suitable for real-time network transmission and application. In conclusion, the proposed method outperforms the related dual images watermarking algorithms in terms of time performance, extraction effect and robustness.

To protect the patient information in medical images, this article proposes a robust watermarking algorithm for medical images based on Harris-SURF-DCT. First, the corners of the medical image are extracted using the Harris corner detection algorithm, and then, the previously extracted corners are described using the method of describing feature points in the SURF algorithm to generate the feature descriptor matrix. Then, the feature descriptor matrix is processed through the perceptual hash algorithm to obtain the feature vector of the medical image, which is a binary feature vector with a size of 32 bits. Secondly, to enhance the security of the watermark information, the logistic map algorithm is used to encrypt the watermark before embedding the watermark. Finally, with the help of cryptography knowledge, third party, and zero-watermarking technology, the algorithm can embed the watermark without modifying the medical image. When extracting the watermark, the algorithm can extract the watermark from the test image without the original image. In addition, the algorithm has strong robustness to conventional attacks and geometric attacks. Especially under geometric attacks, the algorithm performs better.

To improve the robustness of image watermarking algorithms against geometric attacks such as cropping, rotation, scaling, shearing, projective mapping, a robust image watermarking algorithm based on DT CWT and Schur decomposition is proposed. Firstly, we use Dual Tree Complex Wavelet Transform (DT CWT) to decompose the U component of the original image (cover image), the decomposed low frequency component is divided into non-overlapping N × N blocks, and Schur decomposition is applied in each block. Secondly, we modify maximum primary diagonal value of the upper triangular matrix of each block to embed the watermark. Finally, the Scale Invariant Feature Transform (SIFT) features of the watermarked image (stego-image) is saved as the SIFT key for watermark extraction. When extracting the watermark, we first use the SIFT features of stego-image and changed stego-image to obtain the geometric torsion, thereby a spatial synchronization can be guaranteed. And we then use the maximum election statistics to improve the quality of the extracted watermark. Experiment results show that the proposed algorithm can resist geometric attacks, and is more robust than the existing watermarking methods.

Aiming to reduce the distortion in the existing reversible watermarking for 3D mesh models, this paper generalizes two-dimensional (2D) region nesting to ${n}$ -dimensional space, and proposes a general region nesting based semi-fragile reversible watermarking for authenticating 3D mesh models by combing watermark generation based on vertex projection and mesh topology. For any ${n}$ -dimensional space, each hypercube space is partitioned into several nested watermark sub-spaces, and the watermark is embedded by placing the original vertex and the mapped vertex on a straight line. The watermark is extracted by acquiring the position of the vertices, and its original coordinates can be restored by inverse mapping. Furthermore, a new coordinate system is built for 3D mesh models based on reference vertices to achieve semi-fragility, and the watermarks generated by vertex projection and mesh topology is utilized for integrity authentication. Experimental results and analysis show that the proposed scheme can significantly reduce the distortion, achieve semi-fragility in RST (Rotation, Scaling and Translation) and vertex reordering, identify the tampering type, and accomplish tampering location at vertex level. It has great potential to be applied for content authentication of 3D mesh models.

Point cloud classification has attracted increasing attention due to the outstanding performance of elaborated networks on synthetic datasets. However, rotation invariance has been seldom investigated. In this paper, we propose a straightforward rotation-invariant network called ERINet with a novel enhanced rotation-invariant module for point cloud classification. The enhanced rotation-invariant module is composed of a representation conversion component and a feature aggregation layer. It first takes 12 well-designed rotation-invariant features as the representation of point cloud and leverages the feature aggregation layer to aggregate the features of neighbor points into a discriminative rotation-invariant representation. The enhanced rotation-invariant module is further combined with the multi-layer perceptron and the fully connected layers to form an efficient ERINet. The proposed ERINet demonstrated its advantages with a small model size and high speed. The enhanced rotation-invariant module of our ERINet is also extensible and can be easily integrated with mainstream networks to improve rotation robustness. The experimental results on rotation-augmented datasets demonstrate that our ERINet outperforms other state-of-the-art methods in rotation robustness for point cloud classification.

The current study investigated the role of sequential auditory memory and gender in auditory comprehension among a sample of (80) primary school students, who were chosen by random method. To achieve the objectives of the study, the sequential auditory memory test was used to measure the auditory memory, and another test was prepared by the researcher to measure the auditory comprehension. The findings revealed apparent differences between the average performance of students on the sequential auditory memory test and the auditory comprehension test due to the gender variable and in favor of females. The results also indicated the variation in the auditory comprehension of sequential audio memory and the superiority of females over males in auditory comprehension. The study did not reveal an effect of the interaction between the variables of sequential auditory memory and gender in auditory comprehension.

Digital watermarking is one of the techniques used for copyright protection as well as authentication purpose. In this paper, digital watermark embedding and extraction techniques have been used in which a nested type of watermarking (a watermark inside another watermark) has been presented. The main purpose of using the nested watermarking method is, it increases the embedding capacity so that a large amount of information could be embedded. In this method, one watermark is embedded into another watermark. The resultant watermark is considered as main watermark. The main watermark is encrypted and then embedded into the main image. The main goal in encrypting the watermarks before embedding is increased safety. A5/1 encryption algorithm is used for the encryption and decryption purpose. Therefore, our research work focuses on two important things i.e., increased watermark embedding capacity and increased safety.

Voice assistant systems are convenient, but attackers can mimic users’ voices to access them and steal private information. We develop an authentication system that defends against acoustic attacks by using unique characteristics captured by the accelerometers in wearable devices.

Trust is a critical characteristic of computer systems, but the traditional approach of evaluating systems has failed to deliver the required levels of confidence. We review the emerging zero trust paradigm and propose a new set of zero trust tenets and an enhanced zero trust model.

The existing privacy protection schemes for Location‐Based Service (LBS) only protect users' location privacy or query privacy, which can not adopt both of the privacy protections simultaneously in the LBS system. Moreover, these schemes cannot take into account the spatial‐temporal correlation and background knowledge. In response to the above mentioned questions, the LBS Privacy Protection Scheme Based on Differential Privacy (DPLQ) is proposed. The method contains two kinds of privacy protection algorithms: users' location privacy protection algorithm and users' query privacy protection algorithm. The users' location privacy protection algorithm divides the map using the Voronoi diagram, choosing l fake location points based on the improved k‐means algorithm and l‐diversity idea, and protects users' location privacy with the Laplace mechanism. Based on the k‐anonymous algorithm, the users' query privacy protection algorithm builds a query k‐anonymous set according to the neighbour users' query requests at the same time t in the cluster and the historical query probability of the region’s POI and protects users' query privacy with the exponential mechanism. Through setting the privacy protection intensity of the algorithm by the users, the generated location dataset and query k‐anonymous set can resist a variety of attacks from malicious attackers. Theoretical analysis and experimental results show that the scheme can effectively protect the location privacy and query privacy of users.

Recent studies highlight the vulnerability of convolutional neural networks (CNNs) to adversarial attacks, which also calls into question the reliability of forensic methods. Existing adversarial attacks generate one-to-one noise, which means these methods have not learned the fingerprint information. Therefore, we introduce two powerful attacks, fingerprint copy-move attack, and joint feature-based auto-learning attack. To validate the performance of attack methods, we move a step ahead and introduce the higher possible defense mechanism relation mismatch. which expands the characterization differences of classifiers in the same classification network. Extensive experiments show that relation mismatch is superior in recognizing adversarial examples and prove that the proposed fingerprint-based attacks are more powerful. Both proposed attacks show excellent attack transferability to unknown samples. The Pytorch® implementations of these methods can download from an open-source GitHub project https://github.com/Dlut-lab-zmn/Source-attack .

Searchable public key encryption (SPKE) is a useful public key cryptographic primitive that allows a user to perform keyword searches over publicly encrypted messages on an untrusted storage server while guaranteeing the privacy of the original messages as well as the search keywords. However, most of the previously proposed SPKE frameworks suffer from the security vulnerability caused by the keyword guessing attack and some other weaknesses. Inspired by the ideas of certificate-based cryptography and signcryption, we present a new SPKE framework called certificate-based searchable encryption. The new framework not only provides resistance to the existing known types of keyword guessing attacks, but also enjoys some appealing merits, such as implicit authentication, no key escrow and no secure channel. Under this new framework, we devise a concrete searchable certificate-based encryption scheme. In the random oracle model, it is proven to meet the keyword ciphertext indistinguishability, the keyword ciphertext unforgeability and the keyword trapdoor indistinguishability under the adaptive chosen-keyword attack. The comparisons indicate that it is secure and practicable.

In cloud, sensitive data is stored in an encrypted form, and searchable encryption is a technique which allows user to search over encrypted data by keyword and it leaks no useful information. However, the secure searchable encryption scheme which can prevent inside keyword guessing attacks (IKGA) and satisfy multi-trapdoor privacy has not been proposed. We first review the security of Wu et al.’s scheme and demonstrate that their scheme is insecure under IKGA and multi-keyword guessing attacks in this paper. To solve these issues, we propose an improved certificateless public key searchable encryption scheme. Furthermore, we give the proof of the security of our scheme under the computational bilinear Diffie-Hellman assumption. It shows that our scheme can resist IKGA successfully, and provides multi-ciphertext indistinguishability and multi-trapdoor privacy. The better performance is shown in our experiment.

Coded caching is beneficial due to its ability to leverage the multicast property of a wireless channel. Under specific network settings, the coded caching scheme has been shown to reveal the user file requests. In prior work, a privacy attack by a single attacker on coded caching was presented. In this letter, we focus on a relatively secure setting whereby only the intended users access the files. Nevertheless, we show that, even in this setting, privacy is compromised if the users are colluding. The time complexity of the attack on a network with $N$ files, $K$ users, and $l \leq K$ colluding users is shown to be in the order of $\sqrt {\ln (N(K-l))}N^{(K-l)/2}$ steps.

The ongoing normalization of digital connection has also increased the interest in digital disconnection research. The desire to disconnect is typically considered a critical reaction to the peculiar affordances and prerequisites of fully participating in digital society. While social and political potentials of disconnections as well as reasons to turn away from media are explored in various trajectories, we still know relatively little about the “what then” and “what else” of digital disconnection. In this article, we address this gap and investigate what stories are told and which imaginaries are invoked in order to commodify disconnection in an exemplary field of the growing disconnection industry, namely tourism. Drawing from interviews and analysis of online representations, we analyze how tourist marketers and accommodation providers in the Austrian province of Salzburg are communicating why people should use their vacation to disconnect and what they can expect to find once they are disconnected. Following our analysis, we identify three general themes of how disconnection is countered to living in deeply mediatized and highly connective times: (1) nature and authenticity, (2) (re-)connecting with the self, finding balance, and (3) connection to family/friends/local people. We conclude by discussing the broader implications of our analysis and what the identified ambivalences of disconnection suggest for further advancing disconnection research in the future.

SQL injection is a type of database-targeted attack for data-driven applications. It is performed by inserting malicious code in the SQL query to alter and modify its meaning, enabling the attacker...

Cloud computing uses a network of remote servers hosted on the Internet to store, manage, and process data. As the cloud is explicitly unsafe, from the time the cloud platform was utilized for stor...

Funder: NIHR MedTech, Funder: in vitro diagnostic Co-operative, Funder: nihr cambridge biomedical research centre, Funder: Wallitt Foundation and Eton College, Funder: Wellcome Trust Collaborative Award, BACKGROUND AND AIMS: Cannabis is a commonly used recreational drug in young adults. The worldwide prevalence in 18- to 25-year-olds is approximately 35%. Significant differences in cognitive performance have been reported previously for groups of cannabis users. However, the groups are often heterogeneous in terms of cannabis use. Here, we study daily cannabis users with a confirmed diagnosis of cannabis use disorder (CUD) to examine cognitive performance on measures of memory, executive function and risky decision-making. METHODS: Forty young adult daily cannabis users with diagnosed CUD and 20 healthy controls matched for sex and premorbid intelligence quotient (IQ) were included. The neuropsychological battery implemented was designed to measure multiple modes of memory (visual, episodic and working memory), risky decision-making and other domains of executive function using subtests from the Cambridge Neuropsychological Test Automated Battery (CANTAB). RESULTS: Our results showed that young adult daily cannabis users with CUD perform significantly poorer on tasks of visual and episodic memory compared with healthy controls. In addition, executive functioning was associated with the age of onset. CONCLUSIONS: Further research is required to determine whether worse performance in cognition results in cannabis use or is a consequence of cannabis use. Chronic heavy cannabis use during a critical period of brain development may have a particularly negative impact on cognition. Research into the persistence of cognitive differences and how they relate to functional outcomes such as academic/career performance is required.

As the internet-of-things (IoT) era begins, there is a significant need for low-cost access control schemes that allow humans to activate and maintain IoT systems.Traditional biometric access control systems remain, however, vulnerable to physical attacks resulting in template theft/privacy, illegal access, etc. This paper aimed to address this by expanding on a proposal called BLOcKeR, which combines biometrics with two recent advances in hardware security—physically unclonable functions (PUFs) and hardware obfuscation. Hardware obfuscation is a technique to protect electronic hardware against access control circumvention attacks through locking mechanisms. A PUF is incorporated to tie the biometrics of the owner to the system. Combining these advances with biometrics, BLOcKeR protects a biometric system from physical attacks by locking its functionality and aims at ensuring successful activation of the locked system unlike the authentication /matching in biometric systems. In addition, unlike various existing approaches, BLOcKeR does not store the raw biometric of users while providing irreversibility, unlinkability, and revocability to the templates. We present a security analysis and experiments with more than 45,000 attack variants to evaluate BLOcKeR’s security against unauthorized access.

With the rapid spread of computer networks and the wide use of multimedia technologies, many watermarking techniques are now under development and investigation for protecting owner's intellectual rights. Watermarks can be divided into two types, visible and invisible watermarks, physical visible watermarks have been used for centuries. Now days it is used in digital library, in video broad casting, and other multimedia services. The visible watermark may face several problems. Among these problems, watermark removal and unauthorized insertion are two main concern. This paper proposes a method of invisible watermark to overcome these problems. The watermarking process based on hiding a selected watermark object, that holds a little a mount of information relative to the source object, inside the cover image which has to be authenticated. The processes are based on using invisible watermarks to protect visibly watermarked images which are done by using different techniques. The experiments have shown that the proposed algorithm can provide a very effective protection for watermarked images.

In the field of data analysis, encrypting and decrypting datasets must keep the information confidential. Currently, encrypting sizable tabular datasets is time-consuming. This study proposes a sol...

The article offers analysis of the approaches in Russian and European legal doctrine to the definition of “biometric data”, as well as the evolution of the legal definition formation of biometric data in the legislative acts of the EU. The article analyzes the role of biometric data in the personal data system, their characteristics, and the determination of a list of key features that allow an individual's data to be classified as biometric data. Special attention is paid to the list of characteristics that fall under the category of biometric data in accordance with existing scientific approaches on personal data, as well as the provisions of the General Data Protection Regulation. The article highlights the main problems of interpretation of the category of biometric data in legal sources, and also suggests the author's legal definition of biometric data that meets, in the author's opinion, the main criteria that characterize specific data of an individual as biometric.

Dynamic watermarking (DW)-based detection methods can effectively detect replay attacks, however these detection methods cannot achieve the desired effectiveness for generalised replay attacks (GRA...

Today, ATMs (automated teller machines) are used in a variety of ways, including: you can withdraw cash, transfer cash, check your balance, get an account summary, and more. The main component here is security, to maintain the security we prefer cryptography and biometrics. Cryptography is a state- of-the-art technique for increasing security. Using cryptography and biometrics together creates a bio cryptographic system. Since the private key is an important component of encryption, here one is the main task to secure the private [1] key. To overcome this issue, we use a biometric fingerprint image. However, biometrics cannot protect anyone’s fingerprint template because of the many suspected attacks. Therefore, we use a fuzzy vault system that combines cryptography [2] and biometrics [4] to ensure that only authorized users can use their passwords and PINs with the legal data. Keywords: Biometrics, Cryptography, Fuzzy vault system, IP security, Java Applets.