Authentication Scheme Research Articles

Multi-factor authentication scheme based on custom attributes

Multi-factor authentication scheme based on custom attributes

Multi-Server user Authentication Scheme for Privacy Preservation with Fuzzy Commitment

The integration of artificial intelligence technology with a scalable Internet of Things (IoT) platform facilitates diverse smart communication services, allowing remote users to access services from anywhere at any time. The multi-server environment within IoT introduces a flexible security service model, enabling users to interact with any server through a single registration. To ensure secure and privacy preservation services for resources, an authentication scheme is essential. Zhao et al. recently introduced a user authentication scheme for the multi-server environment, utilizing passwords and smart cards, claiming resilience against well-known attacks. This paper conducts cryptanalysis on Zhao et al.'s scheme, focusing on denial of service and privacy attacks, revealing a lack of user-friendliness. Subsequently, we propose a new multi-server user authentication scheme for privacy preservation with fuzzy commitment over the IoT environment, addressing the shortcomings of Zhao et al.'s scheme. Formal security verification of the proposed scheme is conducted using the ProVerif simulation tool. Through both formal and informal security analyses, we demonstrate that the proposed scheme is resilient against various known attacks and those identified in Zhao et al.'s scheme.

A Trusted Authentication Scheme Using Semantic LSTM and Blockchain in IoT Access Control System

In edge computing scenarios, due to the wide distribution of devices, complex application environments, and limited computing and storage capabilities, their authentication and access control efficiency is low. To address the above issues, a secure trusted authentication scheme based on semantic Long Short-Term Memory (LSTM) and blockchain is proposed for IoT applications. The attribute-based access control model is optimized, combining blockchain technology with access control models, effectively improving the robustness and credibility of access control systems. Semantic LSTM is used to predict environmental attributes that can further restrict user access and dynamically meet the minimum permission granting requirements. Experiments show that when the number of certificates is 60, the computational overhead of the proposed method is only 203s, which is lower than other state-of-the-art methods. Therefore, the performance of the proposed schema in information security protection in IoT environments shows promise as a scalable authentication solution for IoT applications.

A federated authentication schema among multiple identity providers

Single Sign-On (SSO) methods are the primary solution to authenticate users across multiple web systems. These mechanisms streamline the authentication procedure by avoiding duplicate developments of authentication modules for each application. Besides, these mechanisms also provide convenience to the end-user by keeping the user authenticated when switching between different contexts. To ensure this cross-application authentication, SSO relies on an Identity Provider (IdP), which is commonly set up and managed by each institution that needs to enforce SSO internally. However, the solution is not so straightforward when several institutions need to cooperate in a unique ecosystem. This could be tackled by centralizing the authentication mechanisms in one of the involved entities, a solution raising responsibilities that may be difficult for peers to accept. Moreover, this solution is not appropriate for dynamic groups, where peers may join or leave frequently.In this paper, we propose an architecture that uses a trusted third-party service to authenticate multiple entities, ensuring the isolation of the user's attributes between this service and the institutional SSO systems. This architecture was validated in the EHDEN Portal, which includes web tools and services of this European health project, to establish a Federated Authentication schema.

Behavioural Biometrics as a User Authentication Mechanism in ISMS

Securing sensitive data and mitigating cyber threats necessitates robust user authentication mechanisms within Information Security Management Systems (ISMS). Conventional authentication approaches, such as passwords and static biometric identifiers, exhibit vulnerabilities, urging the adoption of more sophisticated solutions. Behavioral biometrics, which analyzes unique behavioral patterns like typing rhythm and mouse movements, offers a promising avenue for enhancing authentication security while optimizing user experience. This paper examines the integration of behavioral biometrics into ISMS for user verification, emphasizing its advantages including continuous, multimodal, risk-based, and adaptive authentication. Additionally, it addresses considerations like data privacy, regulatory compliance, user experience enhancement, and monitoring and analysis to ensure successful implementation and efficacy. By leveraging behavioral biometrics as part of a holistic authentication strategy, organizations can fortify their security posture, mitigate threats, and adapt to evolving cybersecurity challenges.

A survey on lattice‐based security and authentication schemes for smart‐grid networks in the post‐quantum era

SummaryThe present scenario witnesses “the second quantum revolution,” which has enabled the development of revolutionary novel quantum tools. Quantum computing endeavors to establish higher computing standards that can potentially solve complex structures. Post‐quantum cryptography (PQC) has emerged as one of the new domains of cryptography, which is resilient to quantum attacks owing to the revolution in quantum computing. To ensure quantum security, the lattice‐based cryptosystem (LB‐cryptosystem) is one of the promising tools of PQC to address quantum‐based threats. The traditional security algorithms, such as RSA and Diffie–Hellman (DH), are strong enough to resist present security threats. However, it has been predicted that quantum technologies have the capability to break the security of most traditional algorithms whose security is based on prime factorization and DH‐type hard problems. Therefore, research is currently focused on addressing the security and privacy threats by using LB‐cryptosystems to secure various applications, organizations' data, and information infrastructure in the quantum era. The purpose of this article is to investigate recent advances in LB‐cryptosystems that may allow the design of secure models for smart‐grid networks (SGNs) against existing and future quantum attacks. SGNs have been explored as the bi‐directional assimilation of communication in terms of electricity generation, transmission, allocation, and utilization. This survey provides a comprehensive overview of LB‐cryptosystems, as well as their potential applications in securing SGNs. Lastly, the article summarizes the various PQC primitives, NIST selected algorithms, open‐source tools along with their packages, and various PQC industrial initiatives, and also compares traditional cryptographic schemes with other PQC.

A secure cross-domain authentication scheme based on threshold signature for MEC

The widespread adoption of fifth-generation mobile networks has spurred the rapid advancement of mobile edge computing (MEC). By decentralizing computing and storage resources to the network edge, MEC significantly enhances real-time data access services and enables efficient processing of large-scale dynamic data on resource-limited devices. However, MEC faces considerable security challenges, particularly in cross-domain service environments, where every device poses a potential security threat. To address this issue, this paper proposes a secure cross-domain authentication scheme based on a threshold signature tailored to MEC’s multi-subdomain nature. The proposed scheme employs a (t,n) threshold mechanism to bolster system resilience and security, catering to large-scale, dynamic, and decentralized MEC scenarios. Additionally, the proposed scheme features an efficient authorization update function that facilitates the revocation of malicious nodes. Security analysis confirmed that the proposed scheme satisfies unforgeability, collusion resistance, non-repudiation and forward security. Theoretical evaluation and experimental simulation verify the effectiveness and feasibility of the proposed scheme. Compared with existing schemes, the proposed scheme has higher computational performance while implementing secure authorization updates.

An Elliptic Curve Menezes–Qu–Vanston-Based Authentication and Encryption Protocol for IoT

The exponential growth of the Internet of Things (IoT) has led to a surge in data generation, critical for business decisions. Ensuring data authenticity and integrity over unsecured channels is vital, especially due to potential catastrophic consequences of tampered data. However, IoT’s resource constraints and heterogeneous ecosystem present unique security challenges. Traditional public key infrastructure offers strong security but is resource intensive, while existing cloud-based solutions lack comprehensive security and rise to latency and unwanted wastage of energy. In this paper, we propose a universal authentication scheme using edge computing, incorporating fully hashed Elliptic Curve Menezes–Qu–Vanstone (ECMQV) and PUF. This approach provides a scalable and reliable solution. It also provides security against active attacks, addressing man-in-the-middle and impersonation threats. Experimental validation on a Zybo board confirms its effectiveness, offering a robust security solution for the IoT landscape.

Data Hiding and Authentication Scheme for Medical Images Using Double POB

To protect the security of medical images and to improve the embedding ability of data in encrypted medical images, this paper proposes a permutation ordered binary (POB) number system-based hiding and authentication scheme for medical images, which includes three parts: image preprocessing, double hiding, and information extraction and lossless recovery. In the image preprocessing and double hiding phase, firstly, the region of significance (ROS) of the original medical image is segmented into a region of interest (ROI) and a region of non-interest (RONI). Then, the bit plane of the ROI and RONI are separated and cross-reorganization to obtain two new Share images. After the two new Share images are compressed, the images are encrypted to generate two encrypted shares. Finally, the embedding of secret data and attaching of authentication bits in each of these two encrypted shares was performed using the POB algorithm. In the information extraction and lossless recovery phase, the POBN algorithm is first used to extract the authentication bits to realize image tamper detection; then, the embedded secret message is extracted, and the original medical image is recovered. The method proposed in this research performs better in data embedding and lossless recovery, as demonstrated by experiments.

A Novel Authentication Scheme Based on Verifiable Credentials Using Digital Identity in the Context of Web 3.0

This paper explores the concept of digital identity in the evolving landscape of Web 3.0, focusing on the development and implications of a novel authentication scheme using verifiable credentials. The background sets the stage by placing digital identity within the broad context of Web 3.0′s decentralized, blockchain-based internet, highlighting the transition from earlier web paradigms. The methods section outlines the theoretical framework and technologies employed, such as blockchain, smart contracts, and cryptographic algorithms. The results summarize the main findings, including the proposed authentication scheme’s ability to enhance user control, security, and privacy in digital interactions. Finally, the conclusions discuss the broader implications of this scheme for future online transactions and digital identity management, emphasizing the shift towards self-sovereignty and reduced reliance on centralized authorities.

Privacy-Preserving Location Authentication for Low-altitude UAVs: A Blockchain-based Approach

Efficient and trusted regulation of unmanned aerial vehicles (UAVs) is an essential but challenging issue in the future era of Internet of Low-altitude Intelligence, due to the difficulties in UAVs' identity recognition and location matching, potential for falsified information reporting, etc. To address this challenging issue, in this paper, we propose a blockchain-based UAV location authentication scheme, which employs a distance bounding protocol to establish a location proof, ensuring the authenticity of UAV positions. To preserve the privacy of UAVs, anonymous certificates and zero-knowledge proof are used. The security of the proposed scheme is analyzed. Experiments demonstrate the efficiency and feasibility of the proposed scheme.

Quantum-resistance blockchain-assisted certificateless data authentication and key exchange scheme for the smart grid metering infrastructure

In the contemporary landscape of energy infrastructure, the “smart-grid metering infrastructure (SGMI)” emerges as a pivotal entity for efficiently monitoring and regulating electricity generation in response to client behavior. Within this context, SGMI addresses a spectrum of pertinent security and privacy concerns. This study systematically addresses the inherent research problems associated with SGMI and introduces a lattice-based blockchain-assisted certificateless data authentication and key exchange scheme. The primary aim of this scheme is to establish quantum resistance, conditional anonymity, dynamic participation, and the capacity for key updates and revocations, all of which are imperative facets for the robust implementation of mutual authentication within SGMI. Our scheme harnesses blockchain technology to mitigate the vulnerabilities associated with centralized administrative control, thus eliminating the risk of a single-point failure and distributed denial-of-service attacks. Furthermore, our proposed scheme is meticulously designed to accommodate the resource constraints of smart meters, characterized by lightweight operations. Rigorous formal security analysis is conducted within the framework of the quantum-accessible random oracle model, fortified by ’history-free reduction,’ substantiating its security credentials. Complementing this, simulation orchestration serves to underscore its superiority over existing methodologies, particularly in the realms of energy efficiency, data computation, communication, and the costs associated with private key storage.

Exploiting multimodal biometrics for enhancing password security

Abstract Digitization of every daily procedure requires trustworthy verification schemes. People tend to overlook the security of the passwords they use, i.e. they use the same password on different occasions, they neglect to change them periodically or they often forget them. This raises a major security issue, especially for elderly people who are not familiar with modern technology and its risks and challenges. To overcome these drawbacks, biometric factors were utilized, and nowadays, they have been widely adopted due to their convenience of use and ease of hardware installation. Many biometric-based authentication schemes were proposed, but despite the advantages that they offer, recent research has shown that biometrics by itself cannot be considered as an inviolable technique. Recently, we have proposed StegoPass, a novel method that obtains the 68 facial points of a user and utilizes them as a stego message to an image. This produced stego image was the password. Although the experiments conducted showed maximum security, it would be challenging to enhance the robustness of the proposed model for even more attacks. This paper examines the utilization of multimodal biometrics as the secret message embedded in the image. More specifically, besides the extraction of the facial points, we extract the unique minutiae moments and combine them in a feature vector. This feature vector is then embedded in the image. Two different datasets were used, and the security of the method was tested against state-of-the-art deep learning models, i.e. generative adversarial networks, to test whether the image could be digitally synthesized and fool the proposed verification scheme. The results proved that the new enhanced version of StegoPass offers an extremely secure method as its predecessor.

Highly secured authentication and fast handover scheme for mobility management in 5G vehicular networks

The Fifth Generation (5 G) networks exhibit high flexibility and diversity in their design and deployment strategies. Transitions between base stations (BSs), heterogeneous networks (HetNets) and other cellular networks provide significant vulnerabilities and expose users to substantial risks associated with cybersecurity attacks. This article evaluates current handover authentication methods in the context of 5 G networks while proposing a set of security criteria for handover authentication. This study presents a novel authentication technique called SHK (Secure Handover Key) that utilizes SDNs (Software Defined networks). The proposed scheme integrates recycled lightweight dynamic key cryptography and combines security features such as perfect forward secrecy and robustness to leakages. The significance of the proposed approach is assessed in terms of computations, communications, signals, and energy costs on 5 G mobility applications and Vehicular Communication Networks (VCNs). The scheme employed in this study demonstrates enhanced security measures and improved changeover performance compared to conventional schemes.

Security-Enhanced Lightweight and Anonymity-Preserving User Authentication Scheme for IoT-Based Healthcare

Security-Enhanced Lightweight and Anonymity-Preserving User Authentication Scheme for IoT-Based Healthcare

Improved LTE-R Access Authentication Scheme Based on Blockchain and Secgear

Improved LTE-R Access Authentication Scheme Based on Blockchain and Secgear

Enhancing 802.1X authentication with identity providers using EAP-OAUTH and OAuth 2.0

EAP-OAUTH is a novel Extensible Authentication Protocol (EAP) method that integrates the OAuth 2.0 framework to provide a secure and flexible authentication mechanism for LANs and WLANs that implement the IEEE 802.1X framework. EAP-OAUTH leverages existing, OAuth 2.0-enabled Identity Providers (IdPs) and their single sign-on (SSO) capabilities, thus offering a streamlined authentication experience for both users and organizations. The advantages of EAP-OAUTH for users include an SSO experience and enhanced privacy, while organizations benefit from simplified identity management, reduced operational costs, consistent security policies, and easier compliance. Furthermore, EAP-OAUTH represents a promising solution for addressing the challenges of authentication in modern wireless networks, such as the deployment of various multi-factor or risk-based, adaptive authentication strategies. This article presents an in-depth analysis of the EAP-OAUTH method, its design, implementation, and use cases in enterprise networks and public hotspots. It explores the OAuth 2.0 Device Authorization Grant flow and allows network clients to perform fast re-authentications without resorting to sessions on IdPs or even their SSO features. The implementation of EAP-OAUTH is demonstrated in real-world scenarios, using two IdPs (Google and Auth0), confirming its effectiveness, suitable performance and compatibility with various components of typical Wi-Fi infrastructures.

A Robust Privacy Preserving Authentication Scheme for IOT Environment by 5G Technology

In recent years, secure communication between the interconnected components of the internet of things has become an important and worrying issue due to some attacks on the IoT. The Internet of Things (IOT) is the integration of things with the world of the Internet, where this integration takes place by adding devices or programs to be smart and, as a result, they will be able to communicate with one another and participate in all elements of life quite efficiently. Accordingly, we've developed an authentication protocol for the IoT ecosystem; it's primary function is to ensure the safety of data exchange between the many devices that make up the IoT. Our proposed protocol is based on the elliptic curve cipher (ECC) algorithm, which greatly aids in protecting IoT components from physical assault. Our informal protocol analysis demonstrates that our solution not only protects users' privacy by concealing their devices' identities but also thwarts impersonation, counterattacks, and tracking and suggestion attacks directed at IoT devices. Security characteristics of the proposed protocol are also explicitly examined with the help of the ( SCYTHER) program. In addition, the effectiveness of the suggested protocol is evaluated by determining both its excess costs and its communication costs. Therefore, it appears that the protocol is vastly superior than the many other equivalent protocols by assessing its performance and security.

Secure multi-cloud resource allocation with SDN and self-adaptive authentication

The multi-cloud-based resource allocation is based on multiple constraints and multiple configurations that may vary based on customer requirements and cloud service providers' schemes. Here, security is a serious concern that can be ensured by an authentication scheme based on the Self-Adaptive Flower Pollination based RSA (SA-FPRSA) scheme to ensure data integrity. The SA-FPRSA plays an initial role in ensuring security by enabling authenticated data availability. On the other hand, the resource allocation to the Virtual Machine (VM) is a challenging task due to overwhelmed data in a VM that may face unnecessary energy consumption and time complexity issues. Therefore, the proposed model has introduced a Self-adaptive Heap-based optimizer (HBO) for Multi-Cloud based resource allocation. The performance of the models is evaluated. The proposed model attained an Efficiency of 99.09% and Security of 98.72%. Thus, from the results, the recommended model is proven to be better than the existing models.

Optimizing IoT security via TPM integration: An energy efficiency case study for node authentication

The widespread adoption of Internet of Things (IoT) applications in different technical fields has resulted in a significant increase in connected devices while amplifying concerns regarding security and privacy. The presence of security vulnerabilities in various layers of IoT design has emerged as an important issue. Trusted computing, particularly leveraging the Trusted Platform Module (TPM), is seen as a promising approach to counter these vulnerabilities. This paper investigates thoroughly the utilization of TPM technology to enhance node authentication with a focus on energy efficiency. Researchers closely examine each layer to carefully outline an adversary model that is tailored to the IoT ecosystem. The node authentication scheme that is proposed leverages TPM, which has advantages both in terms of processing time and energy. The outcome of this study can be applied to Flying AdHoc Network (FANET) nodes that operate in areas with high levels of traffic, where there are strict safety and reliability standards. Experiments conducted present the essential significance of TPM in ensuring secure node authentication across various application environments. The adoption of TPM technology is validated through rigorous performance assessments, revealing significant improvements in both energy efficiency and security.