作者:
Nirmala, P.
Saveetha School of Engineering Department of Electronics and Communication Engineering Chennai India
In the absence of a permanent infrastructure, the networks are utilized for temporary events, military operations, and disaster recovery. A Blockchain-Enabled intelligent Vehicle Communication systems: Trust Bit Rewar...
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ISBN:
(纸本)9798331509675
In the absence of a permanent infrastructure, the networks are utilized for temporary events, military operations, and disaster recovery. A Blockchain-Enabled intelligent Vehicle Communication systems: Trust Bit Rewards and Clustering for Autonomous Vehicles (BIVC-CA), an algorithm designed to ensure secure communication between devices and optimize efficient routing in intelligent vehicle systems, is also used to provide quick emergency response. Using blockchain, each vehicle is given its own Bit Trust ID to track its past data and calculate its trust levels. This system ensures transparency and trust between vehicles through cryptographic processes such as key generation, secure message encryption, and message verification, which improve overall communication security. It also includes an Emergency Vehicle Communication System (EUC) that uses OBU devices and sensors to detect collisions and send GSM-based rescue messages, greatly improving road safety and the efficiency of emergency operations. The road-based clustering model optimizes route selection considering traffic conditions and distances and organizes vehicles into clusters to ensure effective communication and coordination. Using the path distance algorithm, clustering is achieved by computing the similarity of routes and grouping accordingly for efficient route management with minimal network congestion. In addition, the model introduces a comprehensive network architecture that integrates vehicle cloud technology and blockchain technology, enabling intelligent vehicles to make quick decisions based on real-time data. With these integrated components, the BIVC-CA model provides a reliable framework for secure data transmission, intelligent routing, and rapid emergency response. This framework will ultimately improve the efficiency of intelligent vehicle systems and contribute to the development of advanced vehicle networks and smarter transportation solutions. We calculated the results with routing expe
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The project Multimodal Maestro believes in a groundbreaking system of human-computer interaction (HCI) for the benefit of common users and people with disabilities. It provides two visual input methods which includes ...
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The field of Artificial Intelligence (AI) has been witnessing a huge demand in the field of research, tools development, and applications of deployment. There are multiple software companies which are shifting their f...
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The rapid advancements in edge computing have opened new avenues for optimizing real-time controlsystems in maritime environments. Traditional centralized systems face challenges such as high latency, limited scalabi...
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Transmission control Protocol (TCP) is a fundamental protocol in the Internet Protocol Suite, responsible for establishing reliable data transmission between devices in network communication. This study models TCP con...
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Software's pervasive impact and increasing reliance in the era of digital transformation raise concerns about vulnerabilities, emphasizing the need for software security. Fuzzy testing is a dynamic analysis softwa...
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ISBN:
(纸本)9783031820724;9783031820731
Software's pervasive impact and increasing reliance in the era of digital transformation raise concerns about vulnerabilities, emphasizing the need for software security. Fuzzy testing is a dynamic analysis software testing technique that consists of feeding faulty input data to a System Under Test (SUT) and observing its behavior. Specifically regarding black-box RESTful API testing, recent literature has attempted to automate this technique using heuristics to perform the input search and using the HTTP response status codes for classification. However, most approaches do not keep track of code coverage, which is important to validate the solution. This work introduces a black-box RESTful API fuzzy testing tool that employs Reinforcement Learning (RL) for vulnerability detection. The fuzzer operates via the OpenAPI Specification (OAS) file and a scenarios file, which includes information to communicate with the SUT and the sequences of functionalities to test, respectively. To evaluate its effectiveness, the tool was tested on the Petstore API. The tool found a total of six unique vulnerabilities and achieved 55% code coverage.
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Industrial automation has become a cornerstone of modern manufacturing, enhancing efficiency, reliability, and scalability. The integration of intelligentcontrol algorithms, such as fuzzy logic, neural networks, gene...
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