Abstract Rice is one of the significant crops, and the early identification and prevention of its diseases are essential to ensure adequate and healthy availability to the world's growing population. The use of image processing is an encouraging method for automatic rice leaf disease identification and detection. In particular, the recent advancements indicate the effectiveness of convolutional neural network (CNN) based deep learning approaches. In this direction, the present work proposes a novel stacked parallel convolution layers‐based network (SPnet) with the squeeze‐and‐excitation (SE) architecture, named (SE_SPnet), for classifying diseased rice leaf images. The stacked parallel network block comprises four parallel convolution layers with different kernel sizes for abstractions of the global and local features. The SE block extracts feature information automatically while removing invalid ones. We compare the SE_SPnet model with state‐of‐the‐art CNN models such as VGG16, DenseNet121, and InceptionV3 based on computational effort, accuracy, sensitivity, specificity, precision, recall, and F1‐score. The experimental results show that the SE_SPnet outperforms standard CNN models for the considered rice leaf disease image datasets. In particular, the SE_SPnet achieves the highest accuracy (99.2%), sensitivity (98.2%), specificity (98.5%), precision (98.4%), recall (98.2%), and F1‐score (98.5%) while using stochastic gradient descent (with momentum) optimizer with a 0.01 learning rate. Furthermore, the SE_SPnet also exhibits to outperform when compared with some of the most recent and relevant existing works.

Several recent works talk about the potential use of network slice brokering mechanism to facilitate the resource allocation of network slicing in next generation networks. This involves network tenants on the one hand and resource/infrastructure providers on the other hand. However, the potential downside of deploying Network Slice Broker (NSB) is that it can be victimized by DoS (Denial of Service) attack. Thus, the aim of this work is three fold. First, to present the possible ways in which DoS/DDoS attacks can be mounted on NSB and their adverse effects. Second, to propose and implement initial blockchain-based solution named as Security Service Blockchain (SSB) to prevent DoS attacks on NSB. Third, to enumerate the challenges and future research directions to effectively utilize blockchain for mitigating DoS/DDoS attacks on NSB. To evaluate the performance the proposed SSB framework is implemented using Hyperledger Fabric. The results manifest that the latency impact of the legitimate slice creation over scaled up malicious traffic remains minimal with the use of SSB framework. The integration of SSB with NSB results in gaining several fold reduction in latency under DoS attack scenario.

Virtual Private LAN services (VPLS) is a Layer 2 Virtual Private Network (L2VPN) service that has gained immense popularity due to a number of its features, such as protocol independence, multipoint-to-multipoint mesh connectivity, robust security, low operational cost (in terms of optimal resource utilization), and high scalability. In addition to the traditional VPLS architectures, novel VPLS solutions have been designed leveraging new emerging paradigms, such as Software Defined Networking (SDN) and Network Function Virtualization (NFV), to keep up with the increasing demand. These emerging solutions help in enhancing scalability, strengthening security, and optimizing resource utilization. This paper aims to conduct an in-depth survey of various VPLS architectures and highlight different characteristics through insightful comparisons. Moreover, the article discusses numerous technical aspects such as security, scalability, compatibility, tunnel management, operational issues, and complexity, along with the lessons learned. Finally, the paper outlines future research directions related to VPLS. To the best of our knowledge, this paper is the first to furnish a detailed survey of VPLS.

Sharing of students’ credentials is a necessary and integral process of an education ecosystem that comprises various stakeholders like students, schools, companies, professors and the governmental authorities. As of today, all these stakeholders have to put-in an enormous amount of efforts to ensure the authenticity and privacy of students’ credentials. Despite these efforts, the process of sharing students’ credentials is complex, error-prone and not completely secure. Our aim is to leverage blockchain technology to mitigate the existing security-related issues concerning the sharing of students’ credentials. Thus, the paper proposes a tamper-proof, immutable, authentic, non-repudiable, privacy protected and easy to share blockchain-based architecture for secured sharing of students’ credentials. To increase the scalability, the proposed system uses a secure off-chain storage mechanism. The performance and viability of the proposed architecture is analyzed by using an Ethereum based prototypical implementation. The test results imply that requests can be executed within few seconds (without block-time) and the system has stability to process up to 1000 simultaneous requests.

Robotics is the multi-disciplinary domain that is booming in today’s world, and expanding its roots deep into various fields of research, manufacturing industries, healthcare, and even in our day-to-day lives. Nevertheless, as with any other evolving technology, robotics face numerous challenges. In this context, lately, blockchain technology has been identified as a promising technology to resolve many of these issues such as identification of malicious/rogue nodes, malfunctioning/faults in automated processes, non-compliance to the agreed norms and privacy rules, security attacks on robotic systems, and non-transparency in performance monitoring and audits. In particular, blockchain with its features like decentrality, immutability, provenance, low operational cost, tight access control, and trustworthy operations, can offer significant improvements to new applications and use cases driven by robotics. Thus, the paper begins with exploring the key requirements and technical challenges encountered by robots in general. Next, it provides detailed overview of blockchain technology in a tutorial style. Then, the role of blockchain for different uses cases of robotics are surveyed. Furthermore, various technical challenges that need to be mitigated to harness full potential of blockchain for robotics are highlighted. Finally, the future research directions are presented that can pave the way ahead for advancements and profitable integration of blockchain in the realm of robotics.

The paper aims to resolve security issues revolving around the sharing of students' credentials by leveraging the blockchain technology. It proposes a novel blockchain-based architecture followed by its implementation as a decentralized application (DApp). Further, the cost & the performance analysis are carried out based on the experiments conducted.