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Story Telling with Basic and Advanced Data Visualizations of Blockchain Technologies 2

Story Telling with Basic and Advanced Data Visualizations of...

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2nd international conference on Augmented Intelligence and Sustainable systems, ICAISS 2023

作者： Kurada, Ramachandra Rao Pavan Kanadam, Karteeka Ramu, Y. Silpa, N. Rao, V.V.R. Maheswara Pattem, Sunil Shri Vishnu Engineering College for Women Department of Cse Bhimavaram India Chandramoulipuram Chowdavaram Department of Computer Applications R.V.R. & J.C.College of Engineering Guntur India

ISBN: (纸本)9798350325799

The reinforced significance of blockchain technology is due to its foul-proof security of decentralized self-triggering applications. The major concern is towards maintaining transaction record keeping as unhampered in the peer-to-peer infrastructure and finally moldings them into digital assets. Blockchain concept is in the form of a distributed peer-to-peer network and is first applied in the design of Bitcoin cryptocurrency. After it was established as a successful model, all the business sectors started the working framework for their customized applications. Universally, the suite of blockchain is still in an embryonic stage and is evolving as a potentially transformative force. Hence to revamp the existing paradigms, the first part of the paper is articulated by stating a concise view towards the architectural importance of blockchain technology. The work also attempts to oversight the potential case studies implemented in the public sector. The second part patches the approachable technical underpinnings that can be transparently applied over with cryptocurrencies such as Bitcoin and Ethereum etc in the form of data visualizations. These visualizations attempt to highlight and demystify compliances in the blockchain datasets and help decision makers to improve their business values timely via this trusted medium. © 2023 IEEE.

关键词： Peer to peer networks

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Evaluation of Human Immune-Based IDPS Under DoS/DDoS Attacks 1st

Evaluation of Human Immune-Based IDPS Under DoS/DDoS Attack...

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1st international conference on Advances in Computing Research, ACR’23

作者： Aliyu, Farouq Sheltami, Tarek Abu-Amara, Marwan Deriche, Mohamed Mahmoud, Ashraf King Fahd University of Petroleum and Minerals Dhahran31261 Saudi Arabia Interdisciplinary Research Center of Smart Mobility and Logistics King Fahd University of Petroleum and Minerals Dhahran31261 Saudi Arabia Ajman University Ajman United Arab Emirates

ISBN: (纸本)9783031337420

Typical intrusion detection and prevention systems (IDPS) require a lot of computing resources such as;CPU time, memory, and energy. However, some resources are not in abundance in fog computing (FC). FC is a computer networking paradigm where computing devices provide services to the user in place of the server. In our previous research, we proposed an IDPS that mimics the human immune behavior by using layers of defense that interact with one another to detect attacks aimed at the fog layer. This paper investigates how the proposed system adapts to denial of service (DoS) and distributed denial of service (DDoS) attacks. The results show that the system has an accuracy of 91.46%. More importantly, the system can recover from both with the help of its intrusion prevention mechanism. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Network security

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Implementation of Deep Learning Techniques for Secure IoT networks 1

Implementation of Deep Learning Techniques for Secure IoT Ne...

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1st international conference on Futuristic Technologies, INCOFT 2022

作者： Mahajan, Rohini Singh, Dushyant Chandigarh Engineering College Department of Computer Science & Engineering Jhanjeri India Vivekananda Global University Department of Computer Science Engineering Jaipur India

ISBN: (纸本)9781665450461

The medical industry, the military, and the power grid are just a few examples of businesses that may benefit greatly from using IoT solutions. The safety of an Internet of Things network is less important than the safety of the underlying computer and communications systems. However, IoT networks are vulnerable to a variety of threats because of the scarcity of available resources and computational power. Protecting the Internet of Things (IoT) network from malicious assaults necessitates the creation and use of effective security measures, such as an intrusion detection system. In this paper, we provide a unique method for categorising the data flowing through an Internet of Things (IoT) network by using Deep Neural networks (DNNs) educated on deep learning data to spot outliers. We create standard features from field-collected packet-level data using a recently released IoT dataset. To classify potential threats to Internet of Things (IoT) devices, such as denial-of-service (DoS), distributed denial-of-service (DDoS), reconnaissance, and information theft, we create a feed-forward neural networks model. On the sanitised dataset, the tested approach exhibits high classification accuracy. © 2022 IEEE.

关键词： Internet of things

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Effective security Mechanisms against distributed Denial of Services

Effective Security Mechanisms against Distributed Denial of ...

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international conference on Information systems and computer networks (ISCON)

作者： Kashish Gaur Kaamya Gaur Tanya Sachdeva Manoj Diwakar Prabhishek Singh Neeraj Kumar Pandey Graphic Era Deemed to be University Dehradun India School of Computer Science Engineering and Technology Bennett University Greater Noida India School of Computing DIT University Dehradun

In general, the popularity of DDoS attacks being used as a weapon to harm the opposite party, is on the rise. Hence, is the need for the security from such disruptive attacks. There have been several attempts at detecting, preventing and mitigating the DDoS attacks with several model proposals being put forward. In this paper, we have reviewed some research papers along with the models and mechanisms proposed in them. As the conclusion, we have picked out the mechanism which we found to be the most effective against the DDoS attacks.

关键词： Industries Weapons Denial-of-service attack Information filters Virtual machining computer networks security

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Blockchain-Enhanced Access Control for IoT systems in Smart Cities

Blockchain-Enhanced Access Control for IoT Systems in Smart ...

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distributed systems, computer networks and Cybersecurity (ICDSCNC), international conference on

作者： Santhosh Kumar Kuchoor Sanjeev Kukreti R.S.S. Raju Battula Suruchi Singh Ashutosh Panchbhai Natrayan L Palo Alto Networks San Francisco Bay Area California USA Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun India Department of Computer Applications Aditya University Surampalem India Department of Computer Science and Engineering Chhatrapati Shahu Ji Maharaj University Kanpur India Department of Law Symbiosis Law School Symbiosis International (Deemed University) Pune India Department of Mechanical Engineering Saveetha School of Engineering SIMATS Kuthambakkam India

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

With the exponential growth of smart gadgets and the technologies that connect them, the Internet of Things (IoT) has emerged as the most promising new technology of the last decade. This is true from both a business and academic standpoint. Deployment in smart-home and smart-city initiatives throughout the globe has increased IoT's popularity. Regrettably, the processing power, storage capacity, and bandwidth of IoT network devices are severely constrained. So, compared to other endpoint devices like PCs, tablets, and smartphones, they are more susceptible to assaults. The development of a safe and reliable model for commonly used operations is booming, including data collection, processing, storage, and communication. It isn't easy to build such a model since there are so many obstacles to overcome. New cybersecurity risks emerge on a regular basis, while old ones remain dormant and ready to be exploited. Sadly, these cyber dangers also serve to safeguard the IoT. Due to recent developments, research into cyberphysical systems, the internet of things (IoT), and blockchain is more important than ever. In Internet of Things (IoT) systems, where security breaches compromise the centralised system's ability to function, blockchain technology has shown remarkable promise. distributed ledgers powered by blockchain technology may enhance the security of the Internet of Things (IoT) and its user access management systems, making them more reliable. Following the safe vehicle authorization, the suggested model presents the idea of a branching blockchain that considers the most recently utilized block. This allows low-powered devices to also benefit from the blockchain's security. The needs of the IoV at the physical layer are beyond the capabilities of present-day mining technology. The suggested architecture has many important aspects, such as a decentralized ledger system, load balancing, scalability, and a lightweight blockchain for the physical layer and above. The com

关键词： Authorization Costs Social networking (online) distributed ledger Authentication Physical layer Blockchains Internet of Things security Reliability

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Energy Efficient and Secure Scheme Based Compressive Sensing Method for Internet of Vehicles 22nd

Energy Efficient and Secure Scheme Based Compressive Sensin...

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22nd international conference on Next Generation Teletraffic and Wired/Wireless Advanced networks and systems, NEW2AN 2022

作者： Aziz, Ahmed Ibrahim, Maha Tashkent State University of Economics Tashkent Uzbekistan Computer Science Department Faculty of Computers and Artificial Intelligence Benha University Benha Egypt

ISBN: (纸本)9783031302572

The Compressive Sensing (CS) technique based solutions are increasingly finding application in the field of IoV and WSNs motivated by the benefits of concurrent implementation of lightweight encryption and compression, which offers security and enhancement of WSN lifetime. The CS based solutions still face certain major challenging issues concerned with Key Distribution and Chosen Plain-Text Attacks (CPA). We introduce in this paper, a lightweight framework by instigating a scheme that generates and exchanges the key between the WSN nodes and the BS with the objective of enhancing security and efficiency. It enhances the security by resisting the Chosen Plaintext Attack using the newly introduced algorithm, "Data Compression with Encryption", which allows the WSN nodes to use a secret value for generating secret compressed samples. Furthermore Mobile distributed Clustering Algorithm (MDCA) which is based on the use of predicted combined criteria metric is proposed for node clustering. The simulation results using experimentally collected data from real sensors placed at Intel Berkeley Research Lab show that the introduced scheme decrypts data with a small error in case of real user with correct seed, however, the decryption of the same data by an adversary produces the resultant data with considerably larger error. Moreover, the proposed framework succeeds to prolong the WSN lifetime when compared to other encryption algorithms. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Compressed sensing

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Comparative Analysis of 5G security Mechanisms

Comparative Analysis of 5G Security Mechanisms

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international conference on Information systems and computer networks (ISCON)

作者： Tanya Sachdeva Siddhant Kumar Manoj Diwakar Prabhishek Singh Neeraj Kumar Pandey Savita Choudhary Graphic Era Deemed to be University Dehradun India School of Computer Science Engineering and Technology Bennett University Greater Noida India School of Computing DIT University Dehradun Sir M. Visvesvaraya Institute of Technology Bengaluru

As networks continue to expand, they become increasingly heterogeneous, accommodating a diverse range of devices, from sensors and IoT to clients and servers. This ecosystem is highly distributed, with network facilities supporting many broadband devices, as well as device mobility and dynamic variations in networks, which makes them vulnerable to security attacks. In light of this, this paper reviews previous research on securing 5G networks and identifies the most effective methods. By analyzing various approaches, we determine which method is the most appropriate and provides the highest accuracy for securing our 5G networks. This review paper provides a valuable resource for those seeking to optimize the security of their 5G networks in the face of evolving security threats.

关键词： Wireless communication Wireless sensor networks Privacy Protocols 5G mobile communication security Communication system security

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Unveiling the Landscape of Network Architectures: A Deep Dive and Multi-Criteria Analysis of SDN and Traditional networks

Unveiling the Landscape of Network Architectures: A Deep Div...

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Circuit, systems and Communication (ICCSC), international conference on

作者： Ahmed Belkhadim Abderrahim Maizate Abdelaziz Ettaoufik Zouhair Ibn Batouta RITM – ESTC/CED ENSEM Hassan II University Casablanca Morocco LTIM FS Ben M’SIK Hassan II University Casablanca Morocco LTI FS Ben M’SIK Hassan II University Casablanca Morocco

ISBN: (数字)9798350365306

ISBN: (纸本)9798350365313

The advancement of computer networks has resulted in the emergence of various networking architectures, including Software-Defined Networking (SDN) and traditional networks. While traditional networks use a distributed approach, SDN uses a central system that makes network management and control more efficient. This paper aims to compare SDN and Traditional networks in detail, looking at how they’re built, how well they perform, and how they’re managed. We also look at the pros and cons of each architecture, summarized in a SWOT analysis. Additionally, the paper uses a Multi-Criteria Analysis to further compare SDN and Traditional networks on important factors like control, scalability, flexibility, and security. Overall, this paper provides useful insights into the differences between SDN and Traditional networks, emphasizing the benefits of choosing SDN and paving the way for solving problems with SDN in the future.

关键词： Scalability computer architecture Quality of service Network architecture Routing protocols security Task analysis

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Comparison Of Emotion Through Text Analysis Using Various Deep Learning Models

Comparison Of Emotion Through Text Analysis Using Various De...

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Blockchain and distributed systems security (ICBDS), IEEE international conference on

作者： Harshita Sanjay Trimukhe Rutuja Anil Pagare Shreya Sandeep Salunke Afeefa Rafeeque Rasheed Noor Salman Baig Computer Engineering Department MMANTC Malegaon Malegaon India

ISBN: (数字)9798350354348

ISBN: (纸本)9798350354355

In this study, we investigate the efficacy of Convolutional Neural networks (CNN), Recurrent Neural networks (RNN), Long Short-Term Memory networks (LSTM), and Bidirectional LSTMs (BiLSTM) for emotion classification tasks, which are crucial in natural language processing for applications ranging from sentiment analysis to mental health monitoring. After preprocessing textual data and encoding it into numerical representations suitable for deep learning models, we train multiple architectures with varied configurations and hyperparameters. Evaluation based on accuracy, precision, recall, and F1-score reveals distinct strengths and weaknesses of each model. CNNs excel in capturing local features, RNNs adeptly model sequential dependencies, LSTM networks overcome vanishing gradient issues for long-range dependencies, and BiLSTMs outperform by incorporating bidirectional information flow, enhancing contextual understanding. Our findings offer valuable insights into selecting appropriate deep learning models for emotion analysis, advancing the state-of-the-art in these fields, and guiding practitioners in their applications.

关键词： Deep learning Emotion recognition Analytical models Sentiment analysis Accuracy Text analysis Bidirectional long short term memory Numerical models Convolutional neural networks security

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Maize Crop Yield Prediction Using Machine Learning Regression Approach 5th

Maize Crop Yield Prediction Using Machine Learning Regressio...

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5th international conference on Advances in distributed Computing and Machine Learning, ICADCML 2024

作者： Bedane, Tarikwa Tesfa Kebede, Kidistie Bizuneh Mohapatra, Sudhir Kumar Das, Tapan Kumar Tripathy, Asis Kumar Department of Software Engineering Addis Ababa Science and Technology University Addis Ababa Ethiopia Agricultural Transformation Institute Addis Ababa Ethiopia Faculty of Emerging Technologies Sri Sri University Cuttack India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9789819735228

Given maize’s significant role as a staple crop, it becomes imperative to carry out precise crop yield prediction to ensure food security. This research employs machine learning algorithms to analyze historical data related to maize crop yields, with the aim of developing a predictive model. The outcome of this study can serve as a valuable tool for pre-harvest planning and measuring crop production per unit of land area. The dataset utilized in this research spans from 2010 to 2021 and was sourced from Ethiopia’s Central Statistical Agency. Three machine learning regression algorithms—Logistic Regression, XGBoost, and Random Forest—were employed to design the predictive model. After data preparation and preprocessing, a total of 436,358 records were used for model development. The models were further trained with reduced features using principal component analysis (PCA). The experimental results demonstrate that the Random Forest algorithm, trained with a reduced number of features through PCA, yielded superior performance, with a lower error rate and a high R2 score of 0.98. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Machine learning

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