Secure and efficient WBANs algorithm with authentication mechanism

The metaverse is a new virtual world that has the potential to significantly impact our interactions with digital content and with each other. It is a shared virtual environment where users can seamlessly and with immersive experiences create, interact, and enjoy digital assets. Nevertheless, the metaverse also poses fundamental challenges, particularly about security and privacy concerns, that require careful consideration. One of the most daunting aspects of securing the metaverse is authentication. Several solutions have been proposed, including deployment of blockchain technology and smart contracts, to address these authentication challenges. While these methods provide a secure and tamper-proof authentication mechanism, they fail to meet certain critical security and privacy requirements like interoperability and decentralization. This research proposes an enhanced privacy-preserving authentication scheme based on blockchain, elliptic curve cryptography, biohashing, and a physical unclonable function that guards against various attacks. The proposed scheme does not rely on a single central authority and consists of various phases, including user and avatar authentication, password change, and avatar generation phases. The proposed scheme underwent security assessment using the Burrows Abadi Needham (BAN) logic, ProVerif tool, and Scyther tool. The results demonstrate that it provides a better level of security against a wide range of attack vectors. The proposed scheme offers a swift and efficient authentication mechanism that adheres to the requirements of the metaverse environment, such as interoperability, decentralization, and privacy protection, and requires less computation cost as compared to state-of-the-art schemes.

This document describes two authentication mechanisms created by Sun Microsystems that are commonly used in conjunction with the ONC Remote Procedure Call (ONC RPC Version 2) protocol. WARNING The DH authentication as defined in Section 2 in this document refers to the authentication mechanism with flavor AUTH_DH currently implemented in ONC RPC. It uses the underlying Diffie-Hellman algorithm for key exchange. The DH authentication defined in this document is flawed due to the selection of a small prime for the BASE field (Section 2.5). To avoid the flaw a new DH authentication mechanism could be defined with a larger prime. However, the new DH authentication would not be interoperable with the existing DH authentication. As illustrated in [10], a large number of attacks are possible on ONC RPC system services that use non-secure authentication mechanisms. Other secure authentication mechanisms need to be developed for ONC RPC. RFC 2203 describes the RPCSEC_GSS ONC RPC security flavor, a secure authentication mechanism that enables RPC protocols to use Generic Security Expires: November 17, 1999 Informational [Page 1]^L INTERNET-DRAFT Authentication Mechanisms for ONC RPC 18-May-99 Service Application Program Interface (RFC 2078) to provide security services, integrity and privacy, that are independent of the underlying security mechanisms. Expires: November 17, 1999 Informational [Page 2]^L INTERNET-DRAFT Authentication Mechanisms for ONC RPC 18-May-99 CONTENTS

Enterprise Java applications form the backbone of many mission-critical systems in sectors such as healthcare, finance, and government. With increasing security threats targeting these applications, a comprehensive understanding of Java-based security frameworks and authentication mechanisms is essential. This paper presents an in-depth exploration of contemporary security frameworks in the Java ecosystem, such as Spring Security, Apache Shiro, and Jakarta Security. It also analyzes various authentication mechanisms, including Basic Auth, OAuth2, JWT, SAML, and mutual TLS (mTLS), and their suitability for enterprise deployment. Furthermore, the paper delves into threat modeling techniques such as STRIDE and OWASP Top 10 vulnerabilities relevant to Java applications. A case study of a Hospital Management System (HMS) demonstrates the practical application of layered security strategies using modern frameworks and secure coding practices. The paper concludes with a discussion on emerging challenges, such as API-level threats, and offers future research directions. The goal is to provide a holistic reference for developers, architects, and security analysts working on Java enterprise applications.

The increasing reliance on web applications across domains such as e-commerce, banking, healthcare, and enterprise systems has significantly amplified the importance of secure and reliable authentication mechanisms. Traditional password-based authentication methods are increasingly vulnerable to modern cyber threats, including phishing, brute force attacks, and credential stuffing, thereby necessitating the adoption of more advanced and robust authentication strategies. This study presents a comprehensive comparative analysis of modern authentication mechanisms in web applications, including Multi-Factor Authentication (MFA), OAuth 2.0, JSON Web Tokens (JWT), Single Sign-On (SSO), and biometric-based authentication systems. The research evaluates these mechanisms based on critical parameters such as security strength, usability, scalability, performance, and implementation complexity. It further examines architectural models, token-based frameworks, and federated identity systems that support secure user authentication in distributed environments. Additionally, the study reviews common vulnerabilities, threat mitigation techniques, and real-world deployment scenarios to assess the effectiveness of each approach. The findings highlight a growing shift toward hybrid authentication models that integrate multiple techniques to achieve enhanced security and user experience. However, challenges remain in balancing security with usability, ensuring interoperability across platforms, and maintaining privacy in decentralized systems. The paper concludes by identifying future research directions focused on passwordless authentication, zero-trust security models, and adaptive authentication systems for next-generation web applications.Keywords : Authentication mechanisms, Web application security, Multi-Factor Authentication (MFA), OAuth 2.0, JSON Web Tokens (JWT), Single Sign-On (SSO), Biometric authentication, Passwordless authentication, Zero Trust security, Cybersecurity

Security issues are the major concerns in the deployment of the smart grid system. One proposal of Secure, Intuitive and Low-cost Device Authentication (SILDA) mechanism designed for the Home Area Networks (HANs) in smart grid has presented an authentication protocol which is resilient against insider attackers, man-in-the-middle (MITM) attacks and impersonation attacks. However, it encounters a problem with the key management and has been proved to be vulnerable to reply attacks and unknown key sharing attacks. In this paper, we propose an Enhanced Secure Device Authentication (ESDA) scheme for the HAN in smart grid. By our proposal, t he vulnerability of the SILDA protocol can be overcome. The Burrows-Abadi-Needham Logic (BAN Logic) has been used to provide a proof on the logical correctness of the proposed scheme.

Communication between connected objects in the Internet of Things (IoT) often requires secure and reliable authentication mechanisms to verify identities of entities and prevent unauthorized access to sensitive data and resources. Unlike other domains, IoT offers several advantages and opportunities, such as the ability to collect real-time data through numerous sensors. These data contains valuable information about the environment and other objects that, if used, can significantly enhance authentication processes. In this paper, we propose a novel idea to building opportunistic sensor-based authentication factors by leveraging existing IoT sensors in a system of systems approach. The objective is to highlight the promising prospects of opportunistic authentication factors in enhancing IoT security. We claim that sensors can be utilized to create additional authentication factors, thereby reinforcing existing object-to-object authentication mechanisms. By integrating these opportunistic sensor-based authentication factors into multi-factor authentication schemes, IoT security can be substantially improved. We demonstrate the feasibility and effectivenness of our idea through illustrative experiments in a parking entry scenario, involving both mobile robots and cars, achieving high identification accuracy. We highlight the potential of this novel method to improve IoT security and suggest future research directions for formalizing and comparing our approach with existing techniques.

The Internet of Bio-Nano Things (IoBNT) is an emerging research domain with immense potential in healthcare applications. The physical protection of patients is of paramount importance to prevent malicious attacks on their bodies. Potential physical attacks include administering medicine with malicious nanomachines or injecting harmful nanomachines into patients. Additionally, the usage of terahertz waves on human skin can result in tissue damage, emphasizing the need for robust communication and sensing standards. Wearable bio-electronic devices encounter obstacles concerning their widespread acceptance and adoption. While there have been limited examples of fully functional and approved bioelectronic devices, collaboration between research teams, clinical organizations, and technology companies is crucial for progress. Challenges in bio-cyber interfaces (BCI), such as ligand-receptor selection and realistic modeling of artificial structures, need to be addressed. Biocompatibility, biodegradability, and biofouling are crucial considerations for designing devices that directly interact with the biological environment. The interconnection of millions of IoBNT devices leads to the generation of big data, requiring efficient data management and analytics. Data quality, noisy data, and missing values pose challenges that need to be addressed through data validation and advanced analytics algorithms. New data collection policies should be developed to prevent data from being linked, shared, and analyzed. The security of IoBNT is a critical challenge, considering the potential misuse of sensitive patient data and the risk of bio-cyber terrorism. Existing security mechanisms for traditional wireless networking need to be improved to meet the diverse system requirements of IoBNT. Lightweight security mechanisms and access controls that are material-constrained and compatible with nanonetworks are required. Authentication schemes and encryption techniques must be carefully selected, considering the resource limitations of IoBNT devices. Biochemical cryptography and bio-inspired algorithms offer promising solutions for secure communication and data protection. The chapter will emphasize the interdisciplinary nature of the challenges faced in IoBNT, requiring collaboration among fields such as physics, mechanical engineering, chemical engineering, biology, and information technology. Standardization initiatives can play a pivotal role in unifying information security in IoBNT, while user training and awareness are crucial for widespread adoption. Future research should focus on developing real-time security systems to detect and mitigate attacks, particularly in the context of theragnostic processes. By addressing these security challenges and capitalizing on the research opportunities, IoBNT can realize its full potential in revolutionizing healthcare by enabling early detection, remote diagnosis, targeted drug delivery, and other innovative applications.

With the rapid development of the Internet of Things (IoT) industry, the smart home is fully integrated with people’s shelter and transportation, which facilitates people’s daily life. A smart home without a security authentication mechanism will inevitably cause a series of security threats. This is essentially a problem of symmetry model worth solving. In fact, researchers have designed various authentication schemes to verify the identity of users and to ensure smart devices can be legally accessed through authorization in the smart home. In 2021, Yu proposed a three-factor anonymous authentication scheme for smart homes using lightweight symmetric encryption primitives and stated that their scheme is resistant to various known security attacks. However, after careful analysis, we found that Yu’s scheme needs further improvement in node capture attack and offline password guessing attack and that forward security cannot be guaranteed. Therefore, we first design a robust three-factor anonymous authentication scheme for smart homes based on asymmetric encryption Elliptic Curve Cryptography (ECC). Then, we perform formal and informal security analysis in which the formal analysis tools include Burrows-Abadi-Needham (BAN) logic and Scyther simulation tool to prove that the proposed scheme can achieve user anonymity, untraceability, and session key forward security. Meanwhile, mutual authentication is performed, and the scheme is resistant to all known attacks described in this article. Finally, a performance comparison is made in terms of efficiency, which shows that our scheme can have certain advantages with those newly designed schemes, achieve a delicate balance in performance and safety, and is more practical for the real smart home environment.

The technological development of artificial intelligence, Internet of Vehicles, big data, edge computing, intelligent manufacturing, 5G and other technologies will bring great prospects to the popularization of the Internet of Things. In the future, we will see more and more IoT systems of different sizes. It is particularly important to ensure the control of IoT system message transmission, ensure system security, and monitor IoT systems. The Internet of Things protocol and its system node authentication mechanism have great research value. This paper analyzes the MQTT protocol and its security authentication mechanism, and designs and implements an identity authentication mechanism based on historical information nodes. The proposed authentication mechanism can effectively prevent forgery attacks, counterfeit attacks, replay attacks, and Sybil attacks.

Handwritten signature verification is a critical aspect of personal authentication in numerous sectors, including banking, legal, and access control systems. This paper provides a comprehensive investigation into writer-dependent signature verification techniques, spanning from traditional approaches such as Histogram of Oriented Gradients (HOG) and Scale-Invariant Feature Transform (SIFT) to cutting-edge deep learning architectures like Siamese and triplet networks. Through extensive experimentation and meticulous analysis conducted on benchmark datasets, we rigorously compare and evaluate the efficacy of these approaches. Our study reveals intriguing insights into the performance characteristics of different methodologies, shedding light on their strengths, weaknesses, and areas for improvement. Notably, we observe that while traditional feature-based methods excel in capturing discriminative information from signature images, deep learning architectures offer enhanced flexibility and adaptability, particularly in scenarios with large and diverse datasets. By combining the strengths of both paradigms, we demonstrate the potential for building robust and reliable signature verification systems capable of handling real-world challenges and variations. We highlight the importance of carefully curated datasets and well-designed network architectures in achieving optimal results, thereby providing valuable guidelines for practitioners and researchers in the field. In conclusion, this study contributes significant insights to the advancement of handwritten signature verification systems, emphasizing the importance of leveraging both traditional methodologies and modern deep learning techniques for building secure and dependable authentication mechanisms. By addressing key challenges and exploring novel approaches, our research aims to foster innovation and enhance the security measures associated with handwritten signature authentication in diverse applications. Keywords—Handwritten signature verification, Writer-dependent approach, Feature-based methods, Deep learning, Siamese networks, Triplet networks, Benchmark datasets, Performance evaluation, Authentication mechanisms, Security measures.

Blog services become popular in recently years. Web users can post their articles through the services. On the other hand, the users do not have full control of the articles after posted while the services are built with client/server model. Therefore, we propose to use peer-to-peer (P2P) technology to establish blog services. However, the anonymous feature disables the P2P technology to conduct user identification. The OpenID provides secure and unified authentication mechanism to improve the anonymity. In addition, the OpenID has the single sign on procedure to reduce redundant, multiple accounts and passwords. The paper presents a blog service platform which integrates the P2P networks and the OpenID authentication mechanism together. Therefore, user scan establish their own blogs easily with full control. The platform can be utilized for other Internet applications as well.

Google's Android is one of the most popular mobile operating system platforms today, being deployed on a wide range of mobile devices from various manufacturers. It is termed as a privilege-separated operating system which implements some novel security mechanisms. Recent research and security attacks on the platform, however, have shown that the security model of Android is flawed and is vulnerable to transitive usage of privileges among applications. Privilege escalation attacks have been shown to be malicious and with the wide spread and growing use of the system, the platform for these attacks is also growing wider. This provides a motivation to design and implement better security frameworks and mechanisms to mitigate these attacks. This paper discusses; 1 the security features currently provided by the Android platform; 2 a definition, few working examples and classifications of privilege escalation attacks in Android applications; 3 a classification and comparison of different frameworks and security extensions proposed in recent research.

With rapid growth of wireless local area networks (WLAN) and computing techniques, handheld devices have become a popular tool in terms of working, entertaining and communicating in daily life. Considering the huge amounts of messages travelling in WLAN, a secure authentication scheme is definitely necessary, which is also required to be flexible across multiple organizations. Aiming for establishing a secure and flexible WLAN authentication scheme for various organizations, this paper reviews existing secure authentication mechanisms, describes the details of the proposed authentication scheme, and evaluates achievements of such a scheme.

The Message Queuing Telemetry Transport (MQTT) protocol is one of the most extended protocols on the Internet of Things (IoT). However, this protocol does not implement a strong security scheme by default, which does not allow a secure authentication mechanism between participants in the communication. Furthermore, we cannot trust the confidentiality and integrity of data. Lightweight IoT devices send more and more sensible data in areas of Smart Building, Smart City, Smart House, Smart Car, Connected Car, Health Care, Smart Retail, Industrial IoT (IIoT), etc. This makes the security challenges in the protocols used in the IoT particularly important. The standard of MQTT protocol strongly recommends implement it over Transport Layer Security (TLS) instead of plain TCP. Nonetheless, this option is not possible in most lightweight devices that make up the IoT ecosystem. Quite often, the constrained resources of IoT devices prevent the use of secure asymmetric cryptography algorithms implemented by themselves. In this article, we propose making a security schema in MQTT protocol using Cryptographic Smart Cards, for both challenges, the authentication schema and the trusted data confidentiality and data integrity. We carry out this security schema without modifying the standard protocol messages. And finally, we present a time results experiment using an example implementation model with JavaCard library.

Argumented reality (AR) has become increasingly important tools for transferring data between machines and people as a result of advances in smart gadgets and artificial intelligence (AI). Traditional rigid sensors have outpaced flexible and IoT devices that can be easily incorporated into AR systems. In recent years, adaptable IoT-based AR have been extensively studied for smart skins in the areas of physiological monitoring, motion detection, robotics, healthcare, and other applications. Researchers are focusing on developing the idea of AI in all domains. There are, of course, certain limits to AR ideas and concepts at this stage in their development. To protect AR enabled smart devices from various types of cyber threat, it is necessary to provide security and authentication mechanisms. In this context, in this paper we present a novel attack detection technology that is used to detect DDoS attacks AR-based IoT devices. The proposed approach detects malicious operations with an accuracy of 92.84%. Also works efficiently as compared to other machine learning techniques.KeywordsAugmented realitySmart devicesIoTVirtual realityDDoSMixed realityEdge computing