IoT devices play an integral part of our digital life today, yet pose significant security risks. These risks allow attackers to carry out various cyberattacks, mainly distributed denial of service (DDoS) attacks. To ...
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Internet, one of the essential components of today's civilization, serves numerous purposes for individuals, businesses, and society. However, its extensive use has sparked concerns, especially regarding privacy a...
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ISBN:
(数字)9798331529833
ISBN:
(纸本)9798331529840
Internet, one of the essential components of today's civilization, serves numerous purposes for individuals, businesses, and society. However, its extensive use has sparked concerns, especially regarding privacy and cybersecurity. Furthermore, cyber dangers are becoming more dangerous, intense, and complicated. distributed Denial of Service (DDoS) attacks have evolved as a prevalent and substantial danger to cybersecurity that may disable the network infrastructures of targeted companies and providers. To guard from DDoS assaults, a many security measures are used, like firewalls and intrusion detection systems. Improving the protective capabilities of IDS frameworks using machine and deep learning, other associated technology, is a popular topic currently. Nevertheless, regardless of considerable improvements, identifying DDoS assaults using machine and deep learning, other associated techs remain a difficulty, particularly when dealing with new DDoS attack. Consequently, this review aims to comprehensively discuss about DDoS attacks by going through the contemporary efforts made in the literature to counter the danger due to the DDoS attacks. First, we investigate certain DDoS attack-related solutions suggested by today’s investigators. Finally, we delve deeper by identifying the domains wherein the DDoS attacks are prone to take place; common challenges in recognizing the DDoS attacks in the IoT circumstance; advantages of Software-Defined Networking (SDN); state-of-the-art practices in the academic community to counter DDoS attack attempts in any networks of IoT or SDN or web-connected devices.
The proceedings contain 37 papers. The special focus in this conference is on Data Science. The topics include: Trust as a Classification Tool: Analyzing Collaboration in Senate Floor Speeches on G...
ISBN:
(纸本)9783031858550
The proceedings contain 37 papers. The special focus in this conference is on Data Science. The topics include: Trust as a Classification Tool: Analyzing Collaboration in Senate Floor Speeches on Gun Legislation Post-Uvalde and Sandy Hook;an Application of Convolutional Neural networks to Chaotic systems;artificial Intelligence Data Reduction Algorithm for Streaming Readout in High Energy Physics Experiment;user Behavior Based Implicit Personality Detection in Recommendation systems;proactive Management of Delays in the French Railway Network: A Seasonal Machine Learning Based Approach;CNN to BiLSTM: Enhancing Setswana Named Entity Recognition;Assessing the Impact of Homelessness on COVID-19 Hospitalization Rates in Patients with Underlying Medical Conditions Through Explainable AI;leveraging Ensemble Learning Paradigms for B2B E-Commerce Fraud Detection;exploring Equity: Integrating Knowledge Graphs in Fairness Testing Methodologies;explainable Machine Learning Approach for Intelligent Edits of Medicaid Home Healthcare Services Claims;authAttLyzer-V2: Unveiling Code Authorship Attribution Using Enhanced Ensemble Learning Models and Generating Benchmark Dataset;Real-Time AI Voice Clone Detection: A Deep Learning Approach to Safeguard Authenticity;Enhancing security with Automated Boom Gate Access Through License Plate Recognition Utilising YOLOv8 Model;generating Culturally Appropriate Avatars;NLP-Guided Synthesis: Transitioning from Sequential Programs to distributed Programs;Generative AI Techniques for the Simulation of Groundwater Well Data at Hanford Site;Enhancing Financial Analysis with Generative AI: Utilizing Large Language Models for Efficient Data Extraction;Leveraging NLP and Large Language Models for Clinical Documentation Improvement: A Medical AI Chatbot Approach;Harnessing LLMs to Build an Autonomous Marketing Agent;Generative AI Use in One Health, One System as Healthcare is Global;dataDock: An Open Source Data Hub for Research;big Data Techniques i
The Internet of Things (IoT) is considered an evolving technology, consisting of different types of connected devices that have sensors, specialized hardware, and software. However, considerable challenges related to ...
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ISBN:
(数字)9798331506995
ISBN:
(纸本)9798331507008
The Internet of Things (IoT) is considered an evolving technology, consisting of different types of connected devices that have sensors, specialized hardware, and software. However, considerable challenges related to user data privacy, security, and device integrity are presented by this swift expansion, with digital identity being identified as a significant concern in the online landscape. Established by the World Wide Web Consortium (W3C) [2], Decentralized Identifiers (DIDs) represent a standardized format for defining identity. A peer-to-peer model for managing identity and credentials through self-sovereign identity is facilitated by DIDs, in conjunction with blockchain technology and public-key cryptography. The development of verifiable credentials is enabled by the combination of DIDs and blockchain technology, allowing for the verification of the identities of transacting parties through distributed identity registration and the identification of cryptographic keys necessary for validating electronic authentication during transactions. This integrated framework is regarded as both reliable and trusted. Device registration, verification, and credential revocation are enabled by it. In addition, security is ensured, the privacy of participating nodes is respected, and data integrity is upheld to address several existing challenges, such as data scalability and confidentiality. Trusted management and transaction of IoT data are ensured by the presented IoT data platform. Blockchain, decentralized identifiers, and public key cryptography are integrated by the authors to develop this platform. Self-sovereign identity is granted to each participating device, and dynamic changes in components like consensus algorithms and databases are supported by key features. Different IoT communication protocols are evaluated within a decentralized blockchain infrastructure for identity verification by the authors, focusing on interactions between IoT devices and networked se
An Intrusion Detection System (IDS) is a form of network security that monitors for malicious activity. In the cloud, an IDS might operate on individual hosts or over an entire network. DDoS attacks are so named becau...
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Traditional Intrusion Detection systems (IDS) frequently rely on anomaly and signature-based methods, which have limits in terms of accuracy, scalability, and flexibility. Anomaly-based systems generate a high number ...
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作者:
Mattam, ManjunathMSIT Division
International Institute of Information Technology Gachibowli Hyderabad Andhra Pradesh 500 032 India
This paper proposes a model (architecture and protocol) that will help in securing assignment submissions into learning management systems. A client server architecture that uses cryptography is proposed to transform ...
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Monitoring a large-scale wireless sensor networks (WSN) is very difficult, not only because it is large and complex, much of difficulty comes from the lack of visual analysis tools. This paper describes snds (Sensor N...
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Due to severe DRM failures and the urgent demand for a better solution to solve the existing DRM systems vulnerabilities, this paper discusses the current DRM status, stressing system security objectives and requireme...
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