The Internet of Vehicles (IoVs) integrates vehicles to the enormous realm of cyberspace which introduces some intelligence and convenience in the transportation sector. However, real-time traffic related information is exchanged over the open public internet among the vehicles and with other infrastructures. This exposes these networks to a myriad of security threats that can lead to accidents and congestions. Although many solutions have been developed over the recent past, most of them are inefficient while others are still susceptible to attacks. In this paper, we leverage on the k-valued modified bilinear inverse Diffie-Hellman problem and one-way hashing function to develop an efficient authentication protocol for IoVs. To demonstrate the robustness of its semantic security, we deploy the Real or Random (ROR) model. In addition, we execute extensive informal security anaysis to show that our scheme resists typical IoVs attacks such as forgery, privileged insider, and replay. Moreover, its performance evaluation shows that it incurs the lowest computation and communication overheads among its peers. Specifically, the proposed protocol reduces the transmission overheads by 8.5%, while increasing the supported security functionalities by 88.9%. It is therefor suitable for deployment in the IoV environment to mitigate the numerous security threats at relatively lower computation and energy costs.

With the widespread application of recommender systems in personalized services, effectively capturing the complex interactions between users and items has become a key issue. Traditional recommender systems often rely on a single type of user-item interaction data, neglecting the multidimensional attributes of users and items and the rich semantic relationships between them. To address this issue, this paper proposes a recommendation method called HRAN-MKR, which combines Heterogeneous Relation Attention Networks (HRAN) with the Multi-task Knowledge Graph-based recommendation (MKR) framework. HRAN dynamically learns the importance of user-item relationship paths through attention mechanisms and selectively aggregates multi-modal features, thereby capturing richer semantic information between users and items. The core motivation of this study is that the relationships between users and items are not homogeneous but consist of various types and strengths of connections, each playing a different role in the recommendation process. By introducing HRAN, we can assign different weights to each relationship path, allowing the model to focus more on those relationships that are more important for predicting user preferences. Furthermore, introducing HRAN helps maintain high computational efficiency and generalization ability when dealing with large-scale and heterogeneous data. Through experiments on multiple real-world datasets, we verify the effectiveness of HRAN-MKR in recommender systems, particularly in handling complex user-item interactions and improving recommendation accuracy. Overall, this paper provides a new perspective for the recommendation system field by enhancing the representation power of GNN modules through relation attention mechanisms for more accurate personalized recommendations.

The Internet of Medical Things (IoMT) holds the promise of cutting costs and improving both efficiency and quality of healthcare systems. In IoMT, billions of sensitive patient physiological data are exchanged among the patients and healthcare facilities. Since open channels are used during these exchanges, attackers can compromise this data, posing serious consequences which can be fatal. Although a myriad of techniques have been developed to mitigate these threats, they are either inefficient or lack some pertinent security features. In this paper, we leverage on lightweight cryptographic primitives to develop an authentication protocol that is not only efficient but also robust against typical IoMT threats. The performance evaluation carried out shows that our approach reduced the computation complexity by 58.26% while thwarting threats such as session key disclosure, privileged insider, offline guessing, replay, side-channeling and session hijacking. In addition, the formal security analysis using Burrows–Abadi–Needham (BAN) logic demonstrates the robustness of the mutual authentication procedures.

The evolution of intelligent transport systems (ITS) has significantly enhanced driving experiences in vehicular ad-hoc networks (VANET), crucial for improving road safety and traffic efficiency. Despite these advancements, challenges persist. Trust management solutions often assume user legitimacy without verification. Moreover, the need for reauthentication as vehicles move between RSUs adds computational complexity. VANET is relatively vulnerable to security threats from multiple parties given its highly dynamic topology and its wireless and heterogeneous communication mode. We have expanded upon Maria et al.’s schema by specifically targeting and resolving significant shortcomings in their research. More precisely, we improve the features related to confirming the identity of users, preventing vehicles from being used without authorization, and continuously monitoring their current location in order to strengthen the security of vehicles and increase user involvement. We suggest implementing a schema that utilizes QR code verification to authenticate vehicle users, specifically targeting these difficulties. In VANETs, blockchain has been adopted with the authentication process for fog computing. The result is that there is no need for trusted authority (TA) while achieving privacy within the blockchain network and ensuring of the vehicle user authentication and the integrity of messages. Several key benefits have been achieved, such as blocking malicious entities and the potential damage they cause, enabling the revocation of malicious vehicles by conditional anonymization, as well as simplifying conflict resolution. Likewise, the proposed work was characterized by achieving an effective balance between effectiveness and complexity, protecting privacy, conditional tracking, ensuring integrity, and anonymous authentication.

The growing adoption of the Internet of Things (IoT) terminology in recent years in several domains, including healthcare, has yielded multiple benefits. One of the roles is to support professionals in delivering outstanding and suitable healthcare for patients, while also empowering patients to independently track their health state. However, this wide growth is accompanied by many significant security concerns and cyber risks, including unauthorized access, data leakage, information modification, and data erasure. This article outlines the advantages of employing groundbreaking blockchain technology to provide robust and verified authentication methods for different systems. Additionally, it imparts a foundational comprehension of the technologies employed in the procedure of constructing and advancing blockchain-based platforms. In addition, we explore tools like Scythe and Avispa that are employed to assess the system’s resilience against different types of attacks.

The oil and gas industry represents the beating heart of life in the world. These industries suffer from risks of unsustainability, whether they exist in infrastructure such as pipeline oil and gas leaks, vandalism, or information security for example the hacking of surveillance structures resulting in major physical losses amounting to billions of dollars. Various researchers have presented substantial work in this regard. Some of them focus on centralised systems, which struggle with a variety of issues, for instance a single point of failure, lack of privacy, and dependence on intermediaries, and others focus on decentralised systems, which have some limitations, such as delay in data retrieval; high costs; untrustworthy third-party storage; and 51 0/0, Sybil and Sniffing attacks. This paper proposes a decentralised Hyperledger Fabric blockchain based on thermal closed-circuit television (CCTV) surveillance cameras. It provides blockchain-based re-authentication, offering secure external storage by adopting an InterPlanetary File System which provides scalability and offers hash-based integrity of the data stored by utilising ECDSA, which provides low-complexity authentication, balancing between high security and complexity and resisting well-known malicious factors. Our work has been proven by security analysis. Additionally, compared with previous related works, the performance analysis achieves fewer cost results (1.624) ms for the computation cost, (1.056 bits for each administrator and user, 896 bits for CCTV) for the communication cost.

This study presents a systematic literature review on blockchain-based authentication in smart environments that include smart city, smart home, smart grid, smart healthcare, smart farming and smart transportation. The review incorporated 39 articles presenting blockchain solutions for security and privacy issues through authentication mechanisms in these smart environments. Guided by three research questions to determine the main issues in smart environment, the availability of blockchain-based authentication solutions and identified research gaps and future research endeavors, this review used PRISMA method to provide insights on the use of blockchain-based authentication schemes. The research gap is that blockchain solutions are mostly at the proposal, and sometimes conceptual stage is in the reviewed articles. In addition, solutions presented in smart environments require exploration into blockchain. The findings show similar situational issues across different smart environments and the flexibility and adaptability of blockchain to provide solutions to the identified issues pertaining to security and privacy. More clearly, the authentication problem posed across different smart environments can be adapted to blockchain technology provided that it is combined with other technologies to increase efficiency, despite the existence of large-scale authentication mechanisms. Now, blockchain still has the unique, distributed feature of converting the current database into blockchain databases. This review guided future research directions which could further contribute to the sustainable management of smart environments.

Internet of Vehicles (IoVs) has greatly improved safety and quality of services in Intelligent Transportation System (ITS). However, the deployed Dedicated Short-Range Communication (DSRC) protocol broadcasts messages after every 100-300ms. This presents some challenges in message validation within this short duration. As such, most of the current authentication schemes which incur heavy computation and communication overheads are not suitable in this environment. In this paper, an efficient authentication scheme is presented based on lightweight cryptographic primitives such as collision-resistant one-way hashing functions and exclusive OR (XOR) operations. In our protocol, two-factor authentication is attained using Physically Unclonable Function (PUF) generated identities and random nonces, as well as passwords. Extensive formal security verification using Real or Random (RoR) model shows that it is provably secure. In addition, elaborate semantic security analysis shows that it offers anonymity, untraceability and key secrecy as well as resilience against numerous IoV attack vectors. In terms of performance, comparative evaluations demonstrate that it reduces computation and energy consumptions by 42.31%. Moreover, it increases the supported security features by 26.67%.

Document retrieval plays an essential role in many real-world applications especially when the data storage is outsourced. Due to the great advantages offered by cloud computing, clients tend to outsource their personal data to remote servers maintained by external service providers. This raises serious privacy concerns about outsourced data because such providers are usually considered untrusted entities. The majority of previous schemes of document similarity search share the same limitation: they focus mainly on static collections. Dynamic searchable schemes (DSE) allow adding or removing documents at the expense of more leakage than static schemes. To thwart certain attacks, DSE schemes should support forward privacy property, which ensures that newly added documents cannot be related to previously issued search queries. We design and implement dynamic secure similarity search schemes with forward privacy for textual documents utilizing simhash method for hamming similarity. Our scheme provides an efficient search time and a sufficient level of privacy. To show the practicality of our proposed scheme, we performed excremental results with large document collections.

Document Similarity Detection (DSD) is significant in our real life applications. However, the existing methods ignore the privacy of what is contained in the documents uploaded on remote servers, thus reducing the applicability of these methods. The proposed scheme allows documents to be compared without revealing to those remote servers. For each document, the fingerprint set is calculated. The inverted index is constructed on the basis of the whole fingerprint set. The inverted index is widely used for efficient retrieval. This index is under protection by Paillier cryptosystem before it gets uploaded to the server.

Online information security is a major concern for both users and companies, since data transferred via the Internet is becoming increasingly sensitive. The World Wide Web uses Hypertext Transfer Protocol (HTTP) to transfer information and Secure Sockets Layer (SSL) to secure the connection between clients and servers. However, Hypertext Transfer Protocol Secure (HTTPS) is vulnerable to attacks that threaten the privacy of information sent between clients and servers. In this paper, we propose Enc-DNS-HTTP for securing client requests, protecting server responses, and withstanding HTTPS attacks. Enc-DNS-HTTP is based on the distribution of a web server public key, which is transferred via a secure communication between client and a Domain Name System (DNS) server. This key is used to encrypt client-server communication. The scheme is implemented in the C programming language and tested on a Linux platform. In comparison with Apache HTTPS, this scheme is shown to have more effective resistance to attacks and improved performance since it does not involve a high number of time-consuming operations.

Recently, security issues are obstructing the development and using of cloud computing services. Authentication and integrity play an important role in the cloud security, and numerous concerns have been raised to recognize any tampering with exchanges of the image document between two entities (sender and receiver) within the cloud environment. However, none of the existing solutions reduce the probability of known attacks by combining cryptographic hash function with a strong factor that should be periodically changed. For this reason, in this paper we propose a robust one-time image document authentication scheme based on combining non-interactive onetime biometric key and a robust wavelet-based cryptographic hashing scheme. The result of the combination is one-time image document authentication code (OMAC). OMAC is hidden in an image document as a cover image through reversible data embedding steganography. The proposed scheme has several important security attributes, such as key agreement, biometric key management, robust OMAC, invulnerability, and efficiency. In biometric key management, key generation, key selection, and key update algorithms are performed autonomously by the sender and the receiver; thus, no interaction between them is needed.

Outsourced data in cloud and computation results are not always trustworthy because data owners lack physical possession and control over the data as a result of virtualization, replication, and migration techniques. Protecting outsourced data from security threats has become a challenging and potentially formidable task in cloud computing; hence, many schemes have focused on ameliorating this problem and on enabling public auditability for cloud data storage security. These schemes drop into two categories: total computation cost and burden on client side. Researchers have used bilinear map technology with public key cryptography. Although this technology is highly efficient, computation time is long and overhead cost is high. The client needs to perform numerous computations to ensure the integrity of data storage. To reduce auditing cost, we propose an efficient and robust scheme to maintain data integrity in cases that involve public auditing. Our scheme adopts modern cipher cryptography with a cryptographic hash function. We consider allowing a third party auditor to preprocess data on behalf of cloud users before uploading them to cloud service providers and then verifying data integrity afterward. Our proposed scheme has important security characteristics, such as privacy, key management, low cost computation, key exchange, low overhead cost, no burden on client side, inability of cloud service providers to create correct verifier respond without data, and one-time key. Finally, efficiency analysis shows that our scheme is faster and more cost-efficient than the bilinear map-based scheme.