User Authentication Techniques Research Articles

MERN Stack Based User Authentication Technique for Evernote Application

The MERN (MongoDB, Express.js, React, Node.js) stack gives a solid foundation for building web applications, and executing client affirmation may be a imperative point of numerous applications, checking the Evernote application. Inside the setting of Evernote, a MERN stack- based client confirmation procedure incorporates utilizing MongoDB as the database to store client qualifications securely. Express.js, a backend framework for Node.js, is utilized to create a exit API that handles client enrollment, login, and affirmation. The confirmation handle incorporates creating and endorsing JSON Web Tokens (JWT), confirming secure communication between the client (React front conclusion) and the server. React is utilized for building the client interface, enabling a steady and responsive association for clients affiliation with Evernote. The Node.js server, fueled by Express.js, manages client sessions, favors tokens, and communicates with the MongoDB database to confirm clients and authorize get to to their Evernote data. In this MERN stack-based affirmation strategy for Evernote, the integration of these developments ensures a reliable ,modifible and capable course of action. Clients can securely enroll, log in, and get to their Evernote accounts with certainty, knowing that their affirmation data is taken care of with industry-standard security sharpens. The combination of MongoDB for data capacity, Express.js for server-side method of reasoning, React for a lively client interface, and Node.js for server runtime shapes a competent and cohesive designing for executing client confirmation inside the Evernote application, progressing both security and client inclusion. KeyWords: MERN Stack, Authentication, Evernote, Nodemailer, JsonWebToken, BcryptJS, Axios

A Privacy-Preserving Scheme for Managing Secure Data in Healthcare System

In the world of modern technology and the huge spread of its use, it has been combined with healthcare systems and the establishment of electronic health records (EHR) to follow up on patients. This merging of technology with healthcare has allowed for more accurate EHRs that follow a patient to different healthcare facilities. Timely exchange of electronic health information (EHR) between providers is critical for aiding medical research and providing fast patient treatment. As a result, security issues and privacy problems are viewed as significant difficulties in the healthcare system. Several remote user authentication methods have been suggested. In this research, we present a feasible patient EHR migration solution for each patient. finally, each patient may securely delegate their current hospital’s information system to a hospital certification authority in order to receive migration proof that can be used to transfer their EHR to a different hospital. In addition, the proposed scheme is based on crypto-hash functions and asymmetric cryptosystems by using homomorphic cryptography. The proposed scheme carried out two exhaustive formal security proofs for the work that was provided. Using Scyther, a formal security tool, we present a secure user authentication technique in the proposed healthcare scheme that ensures security and informal analysis.

SLMAS: A Secure and Light Weight Mutual Authentication Scheme for the Smart Wheelchair

The modern innovation called the Internet of Things (IoT) empowers individuals to connect to anybody and anything at any point, wherever. The application of the IoT in smart cities concerning smart healthcare management can improve patient welfare, user acceptance, the standard of living, and accurate illness monitoring. Powered wheelchairs (PW) with sensors, computers, and other connected assistive technologies are called smart wheelchairs. Smart wheelchairs with sensing abilities are intended to offer universal connectivity using cloud and edge computing technology. Numerous outstanding people were impacted by paralyzing phenomena, including Stephen Hawking and Max Brito. The issue of legitimacy is one of the most important difficulties in e-health applications, because of how sensitive the technology is, and this needs to be appropriately handled. To safeguard the data transport, usage, and interchange between sensor nodes/smart wheelchairs and servers, e-health applications require an authentication method. As all conversations use wireless channels, e-health apps are exposed to various vulnerabilities. Additionally, the IoT has limited computational and power capacity limitations. To combat the various security risks, the present research offers a user authentication technique that is efficient and ensures anonymity. The suggested method creates a safe connection for the authorized entity and forbids unauthorized entities from accessing the Internet of Things sensor nodes. The suggested approach has lower communication and computation overheads than the traditional techniques, making it more effective. In addition, the security verification of the presented protocol is scrutinized through AVISPA. The proposed scheme, on average, requires only 12.4% more computation cost to execute. Compared to the existing approaches, the suggested protocol’s extra computational cost can be compensated for by its enhanced security, while the suggested method’s communication cost is 46.3% smaller.

Encryption with User Authentication Model for Internet of Medical Things Environment

Internet of Medical Things (IoMT) enabled e-healthcare has the potential to greately improve conventional healthcare services significantly. However, security and privacy become major issues of IoMT because of the restricted processing abilities, storage, and energy constraints of the sensors. Therefore, it leads to infeasibility of developing traditional cryptographic solutions to the IoMT sensors. In order to ensure security on sensitive medical data, effective encryption and authentication techniques need to be designed to assure security of the patients and healthcare service providers. In this view, this study designs an effective metaheuristic optimization based encryption with user authentication (EMOE-UA) technique for IoMT environment. This work proposes an EMOE-UA technique aims to accomplish mutual authentication for addressing the security issues and reducing the computational complexity. Moreover, the EMOE-UA technique employs optimal multikey homomorphic encryption (OMKHE) technique to encrypt the IoMT data. Furthermore, the improved social spider optimization algorithm (ISSOA) was employed for the optimal multikey generation of the MKHE technique. The experimental result analysis of the EMOE-UA technique takes place using benchmark data and the results are examined under various aspects. The simulation results reported the considerably better performance of the EMOE-UA technique over the existing techniques.

Security vulnerabilities analysis of improved user authentication techniques for electronic medical record systems in aging society

Security vulnerabilities analysis of improved user authentication techniques for electronic medical record systems in aging society

User Authentication Techniques of the Internet of Things

Internet of Things (IoT) is a growing technology that has got the attention of researchers from different fields. As more of IoT resources increasing, the number of users' sensitive data also increasing. Authentication process is one of the security factors which used to protect the users' sensitive data and identify whether the user is legitimate or not. IoT facing many authentication challenges due to its complicated environment it contains a massive number of connected devices, different layers, big data, cloud computing, and the open channels. The truly important challenge of the user authentication process for IoT resources is how to do it more securely and easily utilize for computer-illiterate users. In general, the password is the first defense line of user confidentiality, but the use of alphanumeric-based passwords is still widely, even with the existence of alternatives designed to overcome its weakness. Graphical-based Password is one of the practical alternatives which is developed to improve the security of the user authentication. This paper aims to explore the various authentication aspects that can be used in the IoT technology. Also, an overview of the graphical passwords which can be used as an alternative of the weak alphanumeric-based passwords in IoT technology.

A Robust User Authentication Technique in Online Examination

User authentication in the online environment is promoting a hugely challenging issue. This has contributed to the realization of a user authentication where the exams can be performed over the Internet at any time and from any place and by using any digital device. Consequently, further investigations are required to focus on improving user authentication methods to enhance online security mechanisms, especially in the field of e-exams. This research proposes a new user authentication technique based on the user interface (UI). The novel idea is created based on the design preferences of candidates who are taking the e-exams. Several design features are used to design a special user interface for e-exams, for example, the font attributes, back colour, number of questions per page, group categories for questions based on difficulties, and timer setting. The introduced technique can be used to support the user authentication process in the e-exams environment. Furthermore, the proposed technique provides the ability to login to the e-exam without the need to remember the login information, but to select what the student prefers according to his/her personal information. Based on the literature review, a primary evaluation claiming that the students have differences in their preferences and that each user has stable design preferences within different sessions is revealed. In regard to these facts, they become the resource and essence of this research. The security performance of the proposed method is evaluated. The results of the experiments show a false positive (FP) rate of 0.416% and a false negative (FN) rate of 0%.

Secure user authentication mechanism for IoT-enabled Wireless Sensor Networks based on multiple Bloom filters

In this article, we propose an efficient Bloom filter and fuzzy extractor based user authentication technique, which is significant for an Internet of Things (IoT)-enabled multi-hop Wireless Sensor Networks (IoT-WSNs). The novelty of the proposed authentication technique is that it prevents fraudulent querying data delivery at the starting phase (i.e., at the querying sensor node itself) to stop false or counterfeit data flooding (which can exhaust the resources of IoT-WSNs) from the resource-constrained IoT-enabled sensor nodes to the nearby gateway node. The proposed authentication technique has the ability to significantly reduce the Bloom filter based false positive for user authentication in IoT-WSNs, while also preserving the constraint resources of WSNs. To estimate the security robustness of the proposed protocol based on the security goals of IoT-WSNs, we perform the formal security analysis using the random oracle and Real-Or-Random (ROR) models, informal security analysis and also the formal security verification using a widely-recognized automated software validation tool, known as Automated Validation of Internet Security Protocols and Applications (AVISPA). Next, communication and computational overheads analysis reveal that the proposed protocol is appropriate for resource-constrained sensor nodes. Furthermore, a correlative security feature and complexity analysis outcomes validate that the proposed protocol is reliable, secure, and efficient in comparison with other existing state of art related user authentication protocols.

Recent advances in biometrics-based user authentication for wearable devices: A contemporary survey

In recent years, wearable technology is interwoven with our everyday lives because of its commoditization and comfort. Security and privacy become a big concern as many user-sensitive data have been stored in such devices, such as personal emails and bank accounts. Traditional user authentication techniques like PIN entry are unfriendly and vulnerable to shoulder surfing attacks. To address these problems, a number of new authentication methods have been proposed. In this survey, we review and categorize recent advances in user authentication for wearable devices. We classify existing studies into physiological biometrics based and behavioral biometrics based methods. For each category, we review how signal processing techniques have been used to extract features in various wearable devices. Leveraging these extracted features, specifically designed classification methods can be used to realize user authentication. Finally, we review evaluation metrics for user authentication in wearable devices. Overall, in this survey, we systematically study assorted state-of-the-art user authentication methods for wearable devices, aiming to provide guidance and directions for future research in this area.

A Biometric based Remote User Authentication Technique Using Smart Card in Multi-Server Environment

Remote user authentication is an efficient technique to perform secure communication over an insecure network.In this current research article, a lightweight remote user authentication scheme using smart card is proposed. The proposed scheme is a multi-server authentication mechanism where user biometric plays a prominent role. Here, the user is provided the freedom of selecting his or her service according to its requirement. Registration center selects the server according to the service selected by the user and provides a handshaking between user and server. Both user and server have to mutually authenticate each other to an authorized registration center by message passing. By this technique, finally a session key is generated which is used to perform further communication. Security analysis of the proposed method proves its robustness and comparative analysis with some existing schemes provides the superiority.

Wau: A User Authentication System Based on Channel State Information and Deep Neural Networks

Recently, user authentication techniques have attracted more attention and played a more important role in human-computer interaction applications. In this paper, we propose a user authentication system based on CSI (channel state information) called Wau. This system works in a device-free way and has no privacy violation because it facilitates the crucial characteristics of CSI that the unique CSI variation from different user activity can be measured and recognized. We adopt deep neural networks to realize the authentication of 8 people in three environments, including a through-the-wall scenario. The highest recognition accuracy reaches up to 98%. These results validate the feasibility and effectiveness of the user authentication system using CSI and deep neural networks.

Smartwatch User Authentication Based on the Arm-Raising Gesture

Abstract Smartwatches have arguably become a popular wearable device nowadays. It is important to protect privacy data stored in smartwatches from being stolen. This study proposes a novel smartwatch user authentication technique based on the arm-raising gesture, which is the process of moving the arm from one side of the body to the chest height. We conducted two experiments to verify the effectiveness of the proposed technique. In Experiment 1, we investigated the performance of identifying users with the arm-raising gesture. We selected a set of features and applied them to five basic machine learning algorithms (i.e. random forest, simple logistic, naive Bayes, multilayer perceptron and linear classifier). Results with 32 participants show that with combined features, these classifiers generally achieved high authentication accuracy with high true accept rate (TAR) ($\geq $92.1% for random forest, simple logistic and multilayer perceptron), low false accept rate (FAR) ($\leq $0.6%) and large area under the curve (AUC) of receiver operating characteristics) ($\geq $92.4%). In Experiment 2, we examined the performance of identifying the arm-raising gesture across different day-to-day gestures. Results show that the arm-raising gesture can be identified from other eight common gestures with high TAR ($\geq $99.5%), low FAR ($\leq $3.6%) and large AUC ($\geq $99%). Overall, the results indicate that our technique could be a viable alternative for smartwatch user authentication.

Efficient user authentication, server allocation and secure data storage in cloud

With the increased popularity and the need to store the sensitive data over the cloud, the security of stored data is a very big challenge. This work has not only investigated and rectified the susceptibility of the data in the cloud, but also proposed the technique for user authentication and server allocation efficiently. Cuckoo search algorithm (CSA) is applied for efficiently allocating the server. For maintaining the privacy of client's data over the cloud, improved attribute-based encryption (IABE) can effectively do attribute adjunction/revocation, reduce the time complexity as well as safeguard from collusion attacks. The minimum set generation, proxy key generation, file updation, and secret key updation, is modified for efficient attribute revocation/adjunction. The combination of IABE with CSA achieves the security objective and the process is enhanced efficiently.

Efficient user authentication, server allocation and secure data storage in cloud

With the increased popularity and the need to store the sensitive data over the cloud, the security of stored data is a very big challenge. This work has not only investigated and rectified the susceptibility of the data in the cloud, but also proposed the technique for user authentication and server allocation efficiently. Cuckoo search algorithm (CSA) is applied for efficiently allocating the server. For maintaining the privacy of client's data over the cloud, improved attribute-based encryption (IABE) can effectively do attribute adjunction/revocation, reduce the time complexity as well as safeguard from collusion attacks. The minimum set generation, proxy key generation, file updation, and secret key updation, is modified for efficient attribute revocation/adjunction. The combination of IABE with CSA achieves the security objective and the process is enhanced efficiently.

Elliptic Curve Cryptography based Secure and Efficient Authentication Protocol for Smart Card Users

Communication scheme which is used to have communication between authorized remote users over an insecure network is generally the authentication scheme which uses the password for the authentication. Remote user authentication techniques using the smart card have been proposed by many researchers. The main benefit of using the smart card is the storage availability and the computation speed. Huang et al. proposed a scheme for user authentication with smart cards which uses the concept of the timestamp. In Huang et al.’s protocol authors argued that their protocol is secure and efficient against any type of attack. Unfortunately Jung et al. show that Huang et al.’s model fails against the offline password guessing attack and with this scheme wrong password detection is not easy. In Huang et al.’s scheme, RSA cryptosystem is used to offer the authentication. In this article, advanced and secure smart card based authentication protocol using elliptic curve cryptography (ECC) is proposed. This proposed scheme thus overcomes all the possible drawbacks of Huang et al.’s scheme, and it has faster computation as compared to the available schemes

Research and Development of User Authentication using Graphical Passwords: A Prospective Methodology

Nowadays in information security user authentication is a very important task. In most of the computer, user authentication depends on the alphanumeric username and password. It means text-based password. But, this is not highly secure because of hackers can easily break the password. Brute force attack, dictionary attack, guessing attack etc. these all are some possible attacks on the password. If the user chooses a difficult password to prevent the system from the attackers which is very much harder for the user to remember such a difficult password. So, to resolve this problem introduced a new technique called graphical password authentication. This paper presents a detailed survey of user authentication techniques using a graphical password. It contains basically two type approaches. They are recognition-based and recall-based approaches. This survey discusses the different techniques about Graphical password authentication and their advantages and limitations. The survey provides a roadmap for the development of new graphical authentication scheme.

An Enhanced and Secure Biometric Based User Authentication Scheme in Wireless Sensor Networks Using Smart Cards

Over the last two?decades, several researchers have recommended many remote user authentication schemes, following since introducing the concept way back in 1981. Researchers are continuously trying to enhance the security in authentication protocols by incorporating the several features into their work. A few years back, Turkanovic et al. (Ad Hoc Netw 20:96---112, 2014) have presented a novel work for authenticating users in IOT environment using smart cards for wireless sensor networks. In this paper, we have demonstrated that their scheme doesn't resist many possible security threats and have numerous flaws, and also proposed an enhanced and secure biometric-based user authentication technique to overcome their weaknesses. The stated protocol not only overcome from the flaws of Turkanovic et al.'s scheme but also reduce the computation overhead as well. Later, to proving the mutual authentication among the entities and session key secrecy of the proposed scheme has also been verified by ProVerif (2.0) simulation tool.

Memristors for Secret Sharing-Based Lightweight Authentication

User authentication is one of the most fundamental security problems that design effective ways of identifying single or multiple entities using shared information, signatures, or intrinsic properties of the user(s). Password-based authentication is standard in the computer systems; however, passwords usually have low entropy content, and therefore vulnerable to dictionary attacks. Furthermore, password storage and simultaneous multiparty authentication also pose security and privacy concerns. Secret sharing-based techniques during password enrollment are found to be helpful in securing key storage in the authentication server, and in assisting multiparty authentication without exposing individual identity. However, secret sharing techniques, such as Shamir’s secret sharing, are computationally expensive; therefore, its implementation in power-constrained systems is elusive. To address these problems, we have demonstrated how secure and lightweight user authentication techniques can be designed using several well-known properties of memristive devices. For developing our secret sharing-based computationally lightweight user authentication protocols, first, we define essential utility functions, such as Read State, SET Pulse Count, Preconditioning, and so on, for controlling conductive filament formation in memristive devices. Next, we demonstrate the implementation of hardware-dependent simple authentication protocols that can ensure secure key storage using secret sharing protocol derived from Shamir and Naor’s visual cryptographic constructs. Then, we lay out the required hardware design and discuss the potential attacks to these protocols and the corresponding countermeasures. We conclude that, under realistic attacking assumptions, the proposed protocols are secure. Finally, using PTM’s 65-nm MOSFET models and Stanford’s variation-aware memristor models, we perform HSPICE simulation of the secret-reconstruction and authentication units to demonstrate the reliability of the hardware designs against SET–RESET unbalance, noise, temperature fluctuations, and aging.

Authenticating Users Through Fine-Grained Channel Information

User authentication is the critical first step in detecting identity-based attacks and preventing subsequent malicious attacks. However, the increasingly dynamic mobile environments make it harder to always apply cryptographic-based methods for user authentication due to their infrastructural and key management overhead. Exploiting non-cryptographic based techniques grounded on physical layer properties to perform user authentication appears promising. In this work, the use of channel state information (CSI), which is available from off-the-shelf WiFi devices, to perform fine-grained user authentication is explored. Particularly, a user-authentication framework that can work with both stationary and mobile users is proposed. When the user is stationary, the proposed framework builds a user profile for user authentication that is resilient to the presence of a spoofer. The proposed machine learning based user-authentication techniques can distinguish between two users even when they possess similar signal fingerprints and detect the existence of a spoofer. When the user is mobile, it is proposed to detect the presence of a spoofer by examining the temporal correlation of CSI measurements. Both office building and apartment environments show that the proposed framework can filter out signal outliers and achieve higher authentication accuracy compared with existing approaches using received signal strength (RSS).

Evaluating authentication options for mobile health applications in younger and older adults.

ObjectiveApps promoting patient self-management may improve health outcomes. However, methods to secure stored information on mobile devices may adversely affect usability. We tested the reliability and usability of common user authentication techniques in younger and older adults.MethodologyUsability testing was conducted in two age groups, 18 to 30 years and 50 years and older. After completing a demographic questionnaire, each participant tested four authentication options in random order: four-digit personal identification number (PIN), graphical password (GRAPHICAL), Android pattern-lock (PATTERN), and a swipe-style Android fingerprint scanner (FINGERPRINT). Participants rated each option using the Systems Usability Scale (SUS).ResultsA total of 59 older and 43 younger participants completed the study. Overall, PATTERN was the fastest option (3.44s), and PIN had the fewest errors per attempt (0.02). Participants were able to login using PIN, PATTERN, and GRAPHICAL at least 98% of the time. FINGERPRINT was the slowest (26.97s), had an average of 1.46 errors per attempt, and had a successful login rate of 85%. Overall, PIN and PATTERN had higher SUS scores than FINGERPRINT and GRAPHICAL. Compared to younger participants, older participants were also less likely to find PATTERN to be tiring, annoying or time consuming and less likely to consider PIN to be time consuming. Younger participants were more likely to rate GRAPHICAL as annoying, time consuming and tiring than older participants.ConclusionsOn mobile devices, PIN and pattern-lock outperformed graphical passwords and swipe-style fingerprints. All participants took longer to authenticate using the swipe-style fingerprint compared to other options. Older participants also took two to three seconds longer to authenticate using the PIN, pattern and graphical passwords though this did not appear to affect perceived usability.