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Continuous and emerging advances in Information and Communication Technology (ICT) have enabled Internet-of-Things (IoT)-to-Cloud applications to be induced by data pipelines and Edge Intelligence-based architectures. Advanced vehicular networks greatly benefit from these architectures due to the implicit functionalities that are focused on realizing the Internet of Vehicle (IoV) vision. However, IoV is susceptible to attacks, where adversaries can easily exploit existing vulnerabilities. Several attacks may succeed due to inadequate or ineffective authentication techniques. Hence, there is a timely need for hardening the authentication process through cutting-edge access control mechanisms. This paper proposes a Blockchain-based Multi-Factor authentication model that uses an embedded Digital Signature (MFBC_eDS) for vehicular clouds and Cloud-enabled IoV. Our proposed MFBC_eDS model consists of a scheme that integrates the Security Assertion Mark-up Language (SAML) to the Single Sign-On (SSO) capabilities for a connected edge to cloud ecosystem. MFBC_eDS draws an essential comparison with the baseline authentication scheme suggested by Karla and Sood. Based on the foundations of Karla and Sood’s scheme, an embedded Probabilistic Polynomial-Time Algorithm (ePPTA) and an additional Hash function for the Pi generated during Karla and Sood’s authentication were proposed and discussed. The preliminary analysis of the proposition shows that the approach is more suitable to counter major adversarial attacks in an IoV-centered environment based on the Dolev–Yao adversarial model while satisfying aspects of the Confidentiality, Integrity, and Availability (CIA) triad.

The rise of AI-generated synthetic media, or deepfakes, has introduced unprecedented opportunities and challenges across various fields, including entertainment, cybersecurity, and digital communication. Using advanced frameworks such as Generative Adversarial Networks (GANs) and Diffusion Models (DMs), deepfakes are capable of producing highly realistic yet fabricated content, while these advancements enable creative and innovative applications, they also pose severe ethical, social, and security risks due to their potential misuse. The proliferation of deepfakes has triggered phenomena like “Impostor Bias”, a growing skepticism toward the authenticity of multimedia content, further complicating trust in digital interactions. This paper is mainly based on the description of a research project called FF4ALL (FF4ALL-Detection of Deep Fake Media and Life-Long Media Authentication) for the detection and authentication of deepfakes, focusing on areas such as forensic attribution, passive and active authentication, and detection in real-world scenarios. By exploring both the strengths and limitations of current methodologies, we highlight critical research gaps and propose directions for future advancements to ensure media integrity and trustworthiness in an era increasingly dominated by synthetic media.

Secure user authentication has grown importance in today’s modern culture. It is significant to authenticate the user identity in numerous consumer applications particularly financial transactions. Traditional authentication methods rely on easy-to-guess passwords, PIN numbers, or tokens with several security flaws, such as those printed on the back of credit cards for PIN numbers. As an alternative to current systems, biometric authentication techniques based on physical and behavioral characteristics have been proposed. Multibiometric systems, which combine several biometrics, are developed as a result of the difficulties that single-biometric authentication systems encountered in real-world applications including lack of precision and noisy data. The proposed system provides better performance and greater accuracy compared with other authentication techniques. The majority of them is inconvenient and demand complicated user interactions. This paper proposes Enhanced Elman Spike Neural Network along Glowworm Swarm Optimization (EESNN-GSO-AMT) for Multiple Transaction Authentication. The images are collected via SDUMLA-HMTalong CASIA V5 dataset. The pictures are provided to pre-processing to enhance the images quality utilizing Learnable Edge Collaborative Filter (LECF). The preprocessed images are fed to feature extraction using Adaptive and concise empirical wavelet transform (ACEWT) and the features are extracted such as entropy, homogeneity, energy and contrast. The extracting features are provided to EESNN classifier to categorize authorized or unauthorized persons. In general, the EESNN classifier does not express adapting optimization methods to determine ideal parameters to ensure accurately. Therefore, it is proposed to utilize the Glowworm Swarm Optimization to enhanceEESNN, which accurately categorizes the authorized and unauthorized person. The efficiency of the proposed approach is assessed usingsome metrics. The proposed EESNN-GSO-AMT method attains higher accuracy 20.54%, 21.76% and 23.89%; greater sensitivity 20.12% 20.34% and 21.43%; higher precision 23.34%, 22.68% and 24.34% are analyzed to the existing methods, like Optimal feature level fusion for safe human authentication in multimodal biometric scheme (OptGWO-AMT-FV), Joint attention network for finger vein authentication (JAnet-AMT-FV), Finger Vein Recognition Utilizing Deep Learning Technique (DCNN-AMT-FV) respectively.

In the last decade, complex engineering systems have been made automatic, smart, and intelligent by adding computation, communication, and monitoring into systems such as Grid systems, Surveillance systems, Health infrastructure, and Vehicular traffic systems. Systems with computation, communication, and monitoring in the feedback loop are called Cyber-Physical Systems (CPS). Smart Grid System is one of the applications of CPS. Smart Grid (SG) produces a service to adjust power production, manage power distribution, monitor power consumption, and supervise consumer behavior. With the increase in openness of the smart grid, large amounts of power entities have to communicate with each other via different modes like wired, wireless, and satellites. The major challenge of the SG environment is Cyber threats to messages transmitted, information to be controlled, and privacy breaches of the consumer that cause severe consequences in the real world. An authentication protocol is a key solution to these cyber threats. Mutual authentication between different entities sates up safe communication. There are various authentication schemes designed previously in the literature but all of them are either computationally inefficient or enabled to be known to security attacks. In this manuscript, we have designed an improved authentication protocol for the SG environment that is powerful against all the security features. This also lends a session key establishment phase for secure communication and substantially lesser computation and communication overhead.

The study introduces the novel message authentication schemes for the smart meter system, where the symmetric cryptography-based physical layer-assisted message authentication (PLAA) scheme and the public key infrastructure- based PLAA scheme are introduced. The proposed schemes integrate the conventional message authentication schemes and the physical layer authentication mechanisms by taking advantage of temporal and spatial uniqueness in physical layer channel responses, aiming to achieve fast authentication while minimising the packet transmission overhead. The authors also verify their claims through extensive analysis and simulation via comparing with proposed PLAA scheme with traditional upper layer authentication schemes. The proposed novel schemes yield the lower time delay for authenticating each message, which can satisfy the requirement of the real-time control over the smart grid.

There are continued advances in the internet and communication fields regarding the deployment of 5G-based applications. It is expected that by 2030, 6G applications will emerge as a continued evolution of the mobile network. Blockchain technology is one of the leading supporting technologies predicted to provide a secure and unique network to 6G-enabled devices, transactions, and applications. It is anticipated that the 6G mobile networks will be virtualized, have cloud-based systems, and aim to be the foundation for the Internet of Everything. However, along with the development of communication technologies, threats from malicious parties have become more sophisticated, making security a significant concern for the 6G era in the future. Despite enormous efforts by researchers to improve security and authentication protocols, systems still face novel intrusion and attacks. Recently, multifactor authentication techniques (MFA) have been deployed as potential solutions to attacks in blockchains. The 6G applications and the cellular network have specific vulnerabilities that need to be addressed using blockchain-based MFA technologies. The current paper is a systematic review that discusses the three technologies under consideration; then, several studies are reviewed that discuss MFA techniques in general and use blockchains as potential solutions to future security and authentication issues that may arise for 6G applications.

Purpose Currency usage either in the physical or electronic marketplace through chip-based or magnetic strip-based plastic card becoming the vulnerable point for the handlers. Proper education and awareness can only thrive when concrete fraud detection techniques are being suggested together with potential mitigation possibilities. The purpose of this research study is tendering in the same direction with a suitable plan of action in developing the authentication strength metric to give weightage marks for authentication techniques. Design/methodology/approach In this research study, a qualitative in-depth exploration approach is being adapted for a better description, interpretation, conceptualization for attaining exhaustive insights into specific notions. A concrete method of observation is being adopted to study various time boxed reports on plastic card fraud and its possible impacts. Content and narrative analysis are being followed to interpret more qualitative and less quantitative story about existing fraud detection techniques. Moreover, an authentication strength metric is being developed on the basis of time, cost and human interactions. Findings The archived data narrated in various published research articles represent the local and global environment and the need for plastic card money. It gives the breathing sense and capabilities in the marketplace. The authentication strength metric gives a supporting hand for more solidification of the authentication technique with respect to the time, cost and human ease. Practical implications The research study is well controlled and sufficient interpretive. The empirical representation of authentication technique and fraud detection technique identification and suggestive mitigation gives this research study an implication view for the imbibing research youths. An application and metric based pathway of this research study provides a smoother way to tackle futuristic issues and challenges. Originality/value This research study represents comprehensive knowledge about the causes of the notion of plastic card fraud. The authentication strength metric represents the novelty of a research study which produced on the basis of rigorous documentary and classified research analysis. The creativity of the research study is rendering the profound and thoughtful reflection of the novel dimension in the same domain.

Phenolic compounds are well-known bioactive compounds in plants that can have a protective role against cancers, cardiovascular diseases and many other diseases. To promote local food development, a comprehensive overview of the phenolic compounds’ composition and their impact on human health from typical Mediterranean plants such as Punica granatum L., Ziziphus jujuba Mill., Arbutus unedo L., Celtis australis L., Ficus carica L., Cynara cardunculus var. Scolymus L. is provided. Moreover, the potential use of these data for authenticity determination is discussed. Some of the plants’ phenolic compounds and their impact to human health are very well determined, while for others, the data are scarce. However, in all cases, more data should be available about the content, profile and health impacts due to a high variation of phenolic compounds depending on genetic and environmental factors. Quantifying variation in phenolic compounds in plants relative to genetic and environmental factors could be a useful tool in food authentication control. More comprehensive studies should be conducted to better understand the importance of phenolic compounds on human health and their variation in certain plants.

In this paper, we have proposed a secure handoff procedure by generating and assessing the tickets for each mesh client which are divided among various zones of mesh routers depending on their transmission range. Further, a trusted third party authentication server is proposed that is responsible for generating and assigning the tickets of each mesh client which are stored distributively at mesh routers. However, during the mobility whenever the range of current serving mesh router decreases, the mesh client needs to connect to a foreign mesh router by authenticating itself in order to continue its network services. The foreign mesh router validates the authenticity of its handoff mesh client by verifying its ticket. The proposed mechanism reduces the potential issue of storage overhead and security threats at mesh clients as all the tickets are stored distributively in the database of each mesh router. The proposed technique is validated with a commercial simulator NS2 over certain network parameters and different probabilistic scenarios of authentication.

Mobile edge computing (MEC) effectively integrates wireless network and Internet technologies and adds computing, storage, and processing functions to the edge of cellular networks. This new network architecture model can deliver services directly from the cloud to the very edge of the network while providing the best efficiency in mobile networks. However, due to the dynamic, open, and collaborative nature of MEC network environments, network security issues have become increasingly complex. Devices cannot easily ensure obtaining satisfactory and safe services because of the numerous, dynamic, and collaborative character of MEC devices and the lack of trust between devices. The trusted cooperative mechanism can help solve this problem. In this paper, we analyze the MEC network structure and device-to-device (D2D) trusted cooperative mechanism and their challenging issues and then discuss and compare different ways to establish the D2D trusted cooperative relationship in MEC, such as social trust, reputation, authentication techniques, and intrusion detection. All these ways focus on enhancing the efficiency, stability, and security of MEC services in presenting trustworthy services.