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Fortifying IoT networks: A Blockchain-Based Communication security Paradigm

Fortifying IoT Networks: A Blockchain-Based Communication Se...

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international conference on Computational Intelligence and Communication networks (CICN)

作者： Kiran B V Samay Deepak Shetty Vinith Vijay Shetty Prakhyat Prakash Shetty ShivaKumar V Computer Science and Engineering Alvas Institute of Engineering and Technology Mangalore India

ISBN: (数字)9798331505264

ISBN: (纸本)9798331505271

Blockchain technology has taken a long way since its introduction together with Bitcoin in 2008. Today, this technology is being applied beyond just cryptocurrencies into, among others, the Internet of Things (IoT) and security. IoT, articulated through devices across networks, has opportunities but also poses some challenges, especially on achieving secure communication across a huge network of thousands of devices. Situations such as this need scalable models to manage the IoT network, which is complex when thousands are present because such management approaches have limitations arising from problems of synchronization. Blockchain technology is therefore decentralized and utilizes cryptography. As such, blockchains have been perceived as a promising solution for the secure communication and synchronization of IoT systems. In this review, we discuss the integration of blockchain technology in enhanced IoT security with respect to safe communication protocols like Ethereum-based smart contracts and RSA public key cryptography that can be used for the management of keys. The blockchain's distributed ledger provides strong security and counters threats like Denial of Service attacks while ensuring data can be transmitted securely. Furthermore, it notes that blockchain for IoT forensics: how critical data integrity, immutability, and scalability are, especially when dealing with forensic analyses and legal procedures. Hybrid frameworks, in which blockchain is integrated with intrusion detection systems and inter-blockchain communication models, have demonstrated significantly better defense against security threats in IoT environments and can be used as a basis to establish secure IoT networks. This paper represents a comprehensive review of blockchain-based solutions for communication within the context of IoT: effectiveness against these limitations of traditional systems and future research directions.

关键词： Performance evaluation Reviews Smart cities Scalability Smart contracts Intrusion detection Public key cryptography Blockchains Internet of Things Synchronization

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Optimized Bidirectional Long Short-Term Memory Model for distributed Denial of Service Attack Detection in Wireless Sensor networks

Optimized Bidirectional Long Short-Term Memory Model for Dis...

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Smart Technologies and systems for Next Generation Computing (ICSTSN), international conference on

作者： K Poongodi S Mithuna S Rajkumar Computer Science and Engineering K. S. Rangasamy College of Technology India

ISBN: (数字)9798350391565

ISBN: (纸本)9798350391572

The rapid expansion of Wireless Sensor networks (WSNs) has made them a critical component in various applications, from environmental monitoring to military surveillance. However, their inherent vulnerabilities make them prime targets for distributed Denial of Service (DDoS) attacks, that have the potential to significantly impair data integrity and network performance. This paper presents an advanced approach for DDoS detection in WSNs using an optimized Bidirectional Long Short-Term Memory (Bi-LSTM) network. The proposed method leverages the strengths of Bi-LSTM in capturing temporal dependencies and patterns within network traffic data, providing a robust mechanism for identifying anomalous activities indicative of DDoS attacks. To enhance the detection accuracy and efficiency, introduce a novel optimization technique that fine-tunes the BiLSTM parameters, balancing the trade-offs between detection performance and computational overhead. Extensive simulations demonstrate that our optimized Bi-LSTM model significantly outperforms traditional machine learning approaches and standard LSTM configurations. The results underline the potential of this approach in fortifying WSNs against sophisticated DDoS threats, ensuring reliable and secure network operations.

关键词： Wireless communication Wireless sensor networks Computational modeling Surveillance Telecommunication traffic Denial-of-service attack security

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Research on Non-IID Cervical Cell Image Classification Algorithm Based on Federated Learning 10

Research on Non-IID Cervical Cell Image Classification Algor...

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10th international conference on Information systems and Computing Technology, ISCTech 2022

作者： He, Huizhen Feng, Kaiping School of Computer Science Guangdong University of Technology Guangzhou China School of Art and Design Guangdong University of Technology Guangzhou China

ISBN: (纸本)9798350332933

Aiming at the performance degradation of existing federated learning algorithms in non-IID image classification tasks, a method of improving SRGAN and dynamically balancing the distribution of client data sets is proposed to enhance the data of non-IID images, and for depth The learning method ignores the privacy and security issues of cervical cell classification, and proposes a method combining federated learning, attention mechanism and convolutional neural network to improve the performance of non-IID cervical cell classification. The experimental results show that the proposed algorithm is 1.77% better than the original convolutional neural network on the liquid-based Pap smear cervical image dataset that is artificially divided into non-independent and identical distribution, and the correct rate can reach 91.75%,which better improves the performance of the non IID distributed images on the federal learning algorithm. © 2022 IEEE.

关键词： Convolutional neural networks

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Unifying RNN and KNN for Enhancing Mirai Attack Detection in IoT networks

Unifying RNN and KNN for Enhancing Mirai Attack Detection in...

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Information Technology, Electronics and Intelligent Communication systems (ICITEICS), IEEE international conference on

作者： Ankita Kumari Deepali Gupta Mudita Uppal Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (数字)9798350382693

ISBN: (纸本)9798350382709

Malicious software gets into Internet of Things (IoT) devices by using exploits and default passwords, which leads to Mirai attacks on IoT networks. These viruses can turn devices into botnets, which raises the risk of major security holes. Massive distributed Denial-of-Service (DDoS) attacks are then possible, which threatens the security of networks and stops internet services. In This research paper suggests a way to better find Mirai threats in IoT networks by mixing the K-Nearest Neighbors (KNN) and Recurrent Neural Network (RNN) methods. In the proposed model takes the best parts of both RNN and KNN systems and puts them together. The RNN architecture is best at finding time relationships in data about network traffic, while the KNN architecture is best at finding trends. When the authors combined the results of both models into our combined approach, it makes identification more accurate than other methods that are already out there. Empirical studies using a variety of datasets clearly demonstrate that our method regularly and accurately finds Mirai attacks. The Recurrent Neural Network and K-Nearest Neighbors method works better together to protect against new Mirai cyber risks in IoT settings. The integrated RNN and KNN provide the good accuracy with 82% of mirai attack detection. This new development makes a big difference in the field of defense.

关键词： Recurrent neural networks Accuracy Web and internet services computer architecture Telecommunication traffic Passwords Nearest neighbor methods

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Entropy-Based Attack Detection and Filtering for Enhanced Message Reception in CAN networks

Entropy-Based Attack Detection and Filtering for Enhanced Me...

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Electrical, computer and Energy Technologies (ICECET), international conference on

作者： Harish Madimangalam Ramesh Anup Kumar Yi Huang Md Tanzil Hoque Chowdhury Jayanta K. Debnath Bin Xie Department of CSE University of Louisville Louisville Kentucky USA Infobeyond Technology LLC Louisville Kentucky USA

ISBN: (数字)9798350395914

ISBN: (纸本)9798350395921

Advancements in automotive technology have been prominent in enabling communication with both internal and external networks (cellular, Bluetooth, satellite navigation, etc.) in vehicles, making it easier and more relevant. The Controller Area Network (CAN) serves as a critical infrastructure for enabling seamless communication among Electric Control Units (ECUs). However, the absence of efficient built-in security measures to mitigate attacks, especially in network attacks, is still something that needs to be addressed. In this paper, we discuss in detail how an intruder designs attack models that make CAN ECUs vulner-able, and we have developed a mechanism to detect distributed Denial Of Service (DDOS), MASQUERADE, and FUZZY attack scenarios by monitoring behavioral changes that occur when an attack is targeted at the victim ECU s. Additionally, we propose a countermeasure to tackle these attacks, which may happen either due to malicious message injection or through firmware overrides in the CAN controller. We showcase our experimental results and assert that the proposed system will be able to restore the victim node to a healthy state even after these three attack methodologies are implemented.

关键词： Wireless communication Satellites Prevention and mitigation Refining Satellite navigation systems security computer crime Monitoring Resilience Microprogramming

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distributed Blockchain-SDN Models for Robust Data security in Cloud-Integrated IoT networks

Distributed Blockchain-SDN Models for Robust Data Security i...

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Automation, Computing and Renewable systems (ICACRS), international conference on

作者： Koya Haritha Sai Srinivas Vellela Roja D Lakshma Reddy Vuyyuru Nallapu Malathi Lavanya Dalavai Dept. of CSE-Data Science Chalapathi Institute of Technology Guntur AP India Dept. of CSE KoneruLakshmaiah Education Foundation Vaddeswaram AP India Dept. of CSE-DS KKR & KSR Institute of Technology and Sciences Guntur AP India

ISBN: (数字)9798331532420

ISBN: (纸本)9798331532437

Blockchain and SDN are combined in the "DistB-SD Cloud" architecture to secure and execute cloud-integrated IoT data. Cloud Computing Management and Services, distributed Secure Blockchain Methodology, SDN Environment, and Data Extraction comprise the architecture. SDN-enabled devices safely gather and process sensor data in the data plane, while OpenFlow and OpenStack handle network component communication in the control plane. The application layer improves network administration with dynamic configuration and data analytics. distributed nodes and hash chains ensure system integrity in blockchain-based access control and ledger maintenance. Blockchain and SDN improve security, privacy, and scalability by resisting attacks. The architecture outperforms OpenFlow-based SDN models in throughput and bandwidth, proving its stability under different network conditions. The study shows that the suggested "DistB-SD Cloud" achieves increased throughput (22.1 KB/s) and bandwidth (1.9 GB/s) when nodes and packet arrival rates increase, making it a feasible solution for safe and scalable cloud computing in IoT-based systems.

关键词： Cloud computing Renewable energy sources Computational modeling Scalability Process control computer architecture Bandwidth Throughput Stability analysis Blockchains

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An Application for Privacy-Preserving Contact Tracing and Public Risk Assessment Using Blockchain for Covid-19 Pandemic 7th

An Application for Privacy-Preserving Contact Tracing and Pu...

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7th international conference on Information and Communication Technology for Competitive Strategies, ICTCS 2022

作者： Shreya, K.R. Nagamani, D.R. Department of Computer Science and Engineering Bangalore Institute of Technology Karnataka Bangalore India

ISBN: (纸本)9789811993039

Many nations are debating on the ways to revert to the new regular state of living as the count of reported infections and victims of the novel COVID-19 outbreak drops with each day gradually. One option examined is the use of contact tracking to bring the spreading of the illness reducing and preventing another round of transmission. Contact tracing still has security and privacy difficulties, regardless of the fact that there are multiple solutions, which makes widespread usage challenging. On the basis of that, a unique approach for contact traceability is introduced, utilizing Blockchain like its foundation. User confidentiality may be protected as well as a comprehensive view of the public for all verified instances can be made available to individuals and governmental entities through connecting distributed ledger alongside contacts tracking apps. By calculating the danger of COVID-19 exposure to the wider populace and disclosing it in a ledger, it also explores how open places may assist in contact tracking. With the use of an Android app, the system can detect the position, and this position is kept on the ledger. These places can efficiently notify possible contamination concerns whilst still ensuring the data's confidentiality and reliability. Finally, findings were made when numeric figures are presented in various settings. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： COVID-19

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Research on computer Network Big Data security Defense System Based on Support Vector Machine and Deep Learning

Research on Computer Network Big Data Security Defense Syste...

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Electronics, Energy systems and Power Engineering (EESPE), IEEE international conference on

作者： Yi Wang Jikui Wang Gansu Province Natural Resources Information Center Lanzhou Gansu China Lanzhou University of Finance and Economics Lanzhou Gansu China

ISBN: (数字)9798350389579

ISBN: (纸本)9798350389586

Due to the swift progress of big data technology, traditional network security systems that are in use can hardly deal with complex and diverse network attacks. In the current paper, a network security system that is based on big data technology is proposed. By the means of limited mathematical computations, for example, genetic algorithm (GA), support vector machine (SVM) and deep learning (DL) a superior and smarter defense system is created. Above all, the system carries out extensive data collection, that is traffic data, user behavior and system log in real time, with the help of numerous distributed data processing technologies such as Hadoop and Spark. The genetic algorithm was then employed to create the features required for the intrusion detection system to optimize the feature set of the detection systems which in the turn manifolds the detection efficiency. Next, to classify the network traffic, the support vector machine is utilized, and after that, optimization of the hyperplane separation is performed to enhance the accuracy of the anomaly detection. Lastly, the deep learning technology was used to significantly analyze the network traffic and it automatically produced higher levels of features and thereby enabling the machine to extract complex attack behaviors. The experiment result shows that the detection accuracy of our proposed system is 95. 4%, 92.1% and 89.7% when it comes to DDoS, SQL injection and XSS attacks, respectively, while the response time is much better than that of traditional defense systems. This paper's analysis supplies conceptual underpinning and practical protection for the issue of safety within the network of big data, and also has a significant practical impact.

关键词： Support vector machines Deep learning Accuracy Intrusion detection Big Data Network security Feature extraction computer networks Time factors Genetic algorithms

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The Internet of Trust: Securing and Transparent Supply Chains with Blockchain and IoT

The Internet of Trust: Securing and Transparent Supply Chain...

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international Symposium on Advanced networks and Telecommunication systems (ANTS)

作者： Gaurav Singal Riti Kushwaha Ashish Sharma Tulika Tewari SMIEEE Computer Science and Engineering Netaji Subhash University of Technology Delhi India School of Computer Science and Technology Bennett University Greater Noida India Computer Science and Engineering Manipal University Jaipur India Computer Science and Engineering Netaji Subhash University of Technology Delhi India

ISBN: (数字)9798350391725

ISBN: (纸本)9798350391732

In an era where digital commerce continues to burgeon, the conventional supply chain confronts challenges of inefficiency, fraud, and a dearth of transparency. Blockchain, renowned for its decentralized and immutable ledger, emerges as a compelling solution to transform the e-commerce supply chain landscape. In conventional supply chain practices marked by centralized databases and manual record-keeping, inefficiencies and a dearth of transparency are widespread. Challenges stemming from cumbersome paperwork, delayed information flow, and vulnerability to errors hindered effective coordination, traceability, and overall operational efficiency. Blockchain and IoT can elevate e-commerce supply chains by ensuring transparent, secure, and automated data-sharing, fostering efficiency and trust throughout the entire process. We have presented an Ethereum-based blockchain and Internet of Things e-commerce platform in this paper. We describe in detail how to put in place a system that stores a product’s journey’s details on an immutable distributed ledger. This allows for secure tracing of a product’s origin. The prototype of the system is deployed and tested on Hardhat testing framework. Traditional databases and cloud storages have been replaced by blockchain and IPFS. IPFS is used as the decentralized and distributed storage layer, facilitating the secure and efficient storage of credentials. Furthermore, the results of our experiments and security and scalability analyses demonstrate the viability of our suggested model.

关键词： Databases Supply chains Transforms Blockchains Telecommunications Electronic commerce Internet of Things security Secure storage Testing

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Cryptographic Ledger for Cyber security in Smart Grid

Cryptographic Ledger for Cyber Security in Smart Grid

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international conference on Edge Computing and Applications (ICECAA)

作者： Elanchezhiyan E K. Kalaiselvi D. Banumathy Department of Networking and Communications Faculty of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Tamilnadu Department of Computer Science and Engineering Paavai Engineering College Namakkal Tamilnadu

In addition to the physical security of energy networks, cyber security is essential to protecting these systems as well. Cyber threats can stem from malicious hackers who have infiltrated the networks to gain unauthorized access to sensitive data, or from vulnerabilities within the systems themselves. It is increasingly important that smart grid companies invest in cyber security solutions, such as strong passwords, two-factor authentication, encryption, and regular software updates, to counteract these threats. Additionally, it is beneficial for organizations to create incident response plans that are tailored to their specific needs, and which define the chain of command and actions to take in the case of an incident. To details the usage of smart grids in various domains and places in an effective way and explains the efficient way of consuming power for smart ventilators by monitoring and providing cyber security against cyber-attacks. The distributed power from various regions is collected from the less predominant places and supplied to the smart ventilators through smart inverters.

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