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Since Vehicular ad hoc networks (VANETs) are vulnerable to various kinds of attacks, there is a need to fulfill the security requirements like message privacy, integrity, and authentication. The authentication technique is said to be efficient if it detects compromised nodes accurately with less complexity, reduced authentication delay, and keying overhead. In this paper, a trust-based authentication scheme for cluster-based VANETs is proposed. The vehicles are clustered, and the trust degree of each node is estimated. The trust degree is a combination of direct trust degree and indirect trust degree. Based on this estimated trust degree, cluster heads are selected. Then, each vehicle is monitored by a set of verifiers, and the messages are digitally signed by the sender and encrypted using a public/ private key as distributed by a trusted authority and decrypted by the destination. This verifies the identity of sender as well as receiver thus providing authentication to the scheme. By simulation results, we prove that the proposed technique provides high security with less overhead and delay.

The quantum key distribution (QKD) technique provided a promising resolution to the current security threats in Quantum Communication. However, the conventional QKD approach is vulnerable to hacker attacks and the Quantum particles used in QKD lose their energy during long-distance communication. To increase the distance coverage of quantum communication, our system proposed a Multi-layer Proxy Encryption Scheme (MPES) using entangled quantum particles. The main advantage of MPES over other conventional communication techniques is that each quantum repeater in the network acts as a different source of encryption with both sender and receiver nodes. For effective long-distance communication, this system adopted a trust-based short-distance protocol to find the path of photon transfer. The entangled photon that is used in communication is done through normal fibre optic cable. The presence of an eavesdropper can be measured with the help of an error correction protocol and a public key is sent through the normal communication channel. This pattern is checked throughout the communication path and malicious nodes that change its pattern will be eliminated from the network. This multiple encoding enhances the security level and reduces the end decryption time effectiveness. Quantum repeaters are used in the QKD protocol to extend the transmission distance by implementing quantum correlations. Unlike the conventional QR, our proposed structure performs one-way communication by encoding and decoding the data within a single node. The reader can decode the information from the actual sender and the writer transforms this decoded data to another node of quantum repeaters. The qubits that are decoded will be in a bell state, and qubits transfer the data in the form of polarization.Moreover, the shortest path algorithm-based photon transfer is done in this approach which increased the execution period of the proposed approach and also turned into the enhanced cost-effective technique. The obtained key error rate of the proposed system is compared with the conventional BB84 protocol and the comparison result proved an increase of 30% in error reduction and reduced energy consumption.

Library repositories are essential for providing secure and seamless digital access to academic and research materials. However, challenges related to data security, scalability, and efficient repository exchange persist, particularly with the rise of cyber threats and increasing remote access demands. This paper proposes a secure and scalable framework for optimizing library repository exchanges using Virtual Private Network (VPN) technology. The framework integrates advanced encryption mechanisms, multi-factor authentication (MFA), AI-driven anomaly detection, and load balancing techniques to ensure confidential, high-performance, and uninterrupted access to digital resources. A comparative analysis of VPN-based solutions versus traditional repository exchange methods demonstrates that VPN-based architectures significantly enhance security, ensure data integrity, and improve accessibility across distributed library networks. The study highlights the role of AI-powered threat detection in mitigating unauthorized access while maintaining scalability through dynamic resource allocation. By implementing this structured approach, academic institutions can fortify their digital repositories against evolving cybersecurity threats while ensuring efficient, scalable, and user-friendly remote access to library resources.

Tokamak is a nuclear fusion reactor; inside, the two lighter nuclei known as deuterium and tritium are first ionized together to form plasma, which is heated up to 150 million degrees Celsius, and then they are confined by the torus-shaped magnetic field. During this process, it releases a massive amount of energy, making fusion a feasible option for a long-term and renewable source of energy. On the other hand, plasma leads to disruptions as a consequence of the sudden implosion of the system, which halts the fusion process. Disruptions can irrevocably harm current fusion devices and are predicted to have a more catastrophic impact on feature devices such as ITER since they cause a rapid loss of confinement. To control, and prevent disruptions, or at least lessen their negative impact by mitigating them, various traditional and data-driven models obtained with machine learning and deep learning techniques have been used, an overview of some of which is presented in this article. These models are commonly used to forecast their occurrence and give sufficient time to take some counteractive measures.

The information technology has grown so rapidly that it has led to the development of compact size and inexpensive sensor nodes. Several sensor nodes together form a WSN. Though the WSN is compact in size, they can be equipped with radio transceivers, sensors, microprocessors which are embedded and sensors. One of the major critical issues with WSN is energy efficiency. With WSN, various energy-efficient techniques are being employed. Among clustering techniques, LEACH, HEED, EAMMH, TEEN, SEP, DEEC, K-means clustering algorithm are some of the most popular energy-efficient techniques which are employed. These are hierarchical based protocol which saves energy by balancing the energy expense. Detailed review and analysis of these protocols are presented, and midpoint location algorithm is proposed in this paper. The methodology used for reduction in dead nodes while transmitting the data is also discussed. In the proposed work, path construction phase (PCP) and alternative path construction phase (APCP) are created in order to reduce dead nodes. During the processes of data transmission if a node is found out that it will fail and APCP is applied, the cluster head is changed while applying the APCP. The cluster head is chosen based on midpoint location and highest node energy. The cluster head becomes permanent if the node has midpoint location and the highest energy. If the node does not have midpoint location and highest energy, it becomes a temporary cluster head. The proposed techniques are compared with EAMMH protocol and LEACH protocol using MATLAB. When compared with EAMMH, the dead nodes were reduced with subsequent rounds.

In recent days, cloud computing is a universal computing and conventional paradigm, in which the resources are provided over the Internet based on requirements. With the huge growth of cloud storage and processing, security in Cloud has become the most captivating research domains. Though there are many methods for enhancing security and data confidentiality over cloud, security is the major threat among data owners and users in data storages and data sharing between two parties in Cloud. In data sharing, for assuring security, the data are secured with key and the key is required to be encrypted to keep that not accessible for attacks. With that concern, this work develops a Quantum Cryptography based Cloud Security Model (QC-CSM) that uses Quantum Key Distribution Protocol (QKDP) for sharing the secret key between parties. For ensuring the data owner about the security of their share data over Cloud, Attribute Based Encryption (ABE) is used. Further, the data can be accessed by an authenticated user, who is having the access for decryption through the key from a secure quantum channel. The results show that the proposed model outperforms the existing works by providing a more secure environment and confidential data sharing between entities in minimal time in the Cloud framework.

Introduction: Nearly 10% of children and adolescents suffer from functional somatic symptoms (FSS) which are persistent, bothersome bodily symptoms not having demonstrable organic pathology. Associations have been reported between children’s FSS, anxiety, depression, and certain parental factors. Aims: (i) compare the anxiety and depression levels between children with FSS and children not having FSS, (ii) identify the child and parent-related risk factors of FSS. Methods:  Case-control design was used for this cross-sectional study. Cases constituted a hospital sample of 60 children, aged 9-15 years, who presented with FSS. Age, gender and class-matched 60 school children, who did not disclose any FSS while screening with Children’s Somatic Symptoms Inventory-24 constituted the control group. Both the groups were administered with Revised Children’s Anxiety and Depression Scale, Illness Behaviour Encouragement Scale, and Lum Emotional Availability of Parents (Child report). Results: Cases scored significantly higher than the control children on anxiety, depression (p<0.001), and parental illness behaviour encouragement (p<0.001), but reported low emotional availability of both parents (p<0.01). Significantly large number of children in the FSS group showed anxiety disorder (p<0.05), separation anxiety disorder (p<0.001) generalized anxiety disorder (p<0.01), and major depressive disorder (p<0.01). The stepwise multiple logistic regression analysis revealed over all anxiety, separation anxiety, generalized anxiety and high parental illness encouragement as the risk factors of FSS. Conversely, higher perception of maternal emotional availability significantly reduced its risk. Conclusion: Children with FSS must be screened for anxiety and depressive disorders as well as parental reinforcing responses and emotional availability before initiating treatment.

The information technology has grown so rapidly that it has led to the development of compact size and inexpensive sensor nodes. Several sensor nodes together form a WSN. Though the WSN is compact in size, they can be equipped with radio transceivers, sensors, microprocessors which are embedded and sensors. One of the major critical issues with WSN is energy efficiency. With WSN, various energy-efficient techniques are being employed. Among clustering techniques, LEACH, HEED, EAMMH, TEEN, SEP, DEEC, K-means clustering algorithm are some of the most popular energy-efficient techniques which are employed. These are hierarchical based protocol which saves energy by balancing the energy expense. Detailed review and analysis of these protocols are presented, and midpoint location algorithm is proposed in this paper. The methodology used for reduction in dead nodes while transmitting the data is also discussed. In the proposed work, path construction phase (PCP) and alternative path construction phase (APCP) are created in order to reduce dead nodes. During the processes of data transmission if a node is found out that it will fail and APCP is applied, the cluster head is changed while applying the APCP. The cluster head is chosen based on midpoint location and highest node energy. The cluster head becomes permanent if the node has midpoint location and the highest energy. If the node does not have midpoint location and highest energy, it becomes a temporary cluster head. The proposed techniques are compared with EAMMH protocol and LEACH protocol using MATLAB. When compared with EAMMH, the dead nodes were reduced with subsequent rounds.