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Securing Digital Governance: A Deep Learning and Blockchain Framework for Malware Detection in IoT networks

Securing Digital Governance: A Deep Learning and Blockchain ...

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Integrated Intelligence and Communication systems (ICIICS), international conference on

作者： Priyanka Pramod Pawar Deepak Kumar Mohan Kumar Meesala Piyush Kumar Pareek Santosh Reddy Addula Shwetha K S Department of Information Technology University of the Cumberlands Williamsburg KY USA Department of Artificial Intelligence & Machine Learning Nitte Meenakshi Institute of Technology Bengaluru India Department of Computer Science and Engineering Dayananda Sagar College of Engineering Bangalore India

ISBN: (数字)9798331504960

ISBN: (纸本)9798331504977

This research uses deep learning and blockchain frameworks to provide a safe platform that promotes digital governance data exchange and interoperability. Use the bonobo optimization algorithm to start a blockchain-based smart city data authentication approach. This paper presents a Blockchain-based malware detection method and framework that uses AI to account for multiple distributed conditions. An upgraded greedy search algorithm and the XGBoost decision tree construct a two-layer extreme gradient boosting (XGBoost) classification model that detects attacks. Three pre-existing XGBoost significance indices were split and merged based on the model's leaf nodes' tree traversal structural features. The augmented greedy search technique retrieved and imported spectral band variables into the XGBoost model's second layer. Bat method was used to optimize XGBoost modeling parameters. The deployed model increased power consumption per device by 13.5%, while Raspberry Pi devices used 0.2 GB and NVIDIA Jetson devices used 0.42 GB. ML models had 93% f1-scores and 95% detection accuracy on both datasets. Our technology detects malware and attacks in Smart Environments efficiently and accurately, as shown by the models.

关键词： Deep learning Data privacy Power demand Smart cities Malware Blockchains Classification algorithms Internet of Things security Interoperability

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Owl: Differential-Based Side-Channel Leakage Detection for CUDA Applications

Owl: Differential-Based Side-Channel Leakage Detection for C...

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international conference on Dependable systems and networks (DSN)

作者： Yu Zhao Wenjie Xue Weijie Chen Weizhong Qiang Deqing Zou Hai Jin National Engineering Research Center for Big Data Technology and System Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China Jinyinhu Laboratory Wuhan China National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9798350341058

ISBN: (纸本)9798350341065

Over the past decade, various methods for detecting side-channel leakage have been proposed and proven to be effective against CPU side-channel attacks. These methods are valuable in assisting developers to identify and patch side-channel vulnerabilities. Nevertheless, recent research has revealed the feasibility of exploiting side-channel vulnerabilities to steal sensitive information from GPU applications, which are beyond the reach of previous side-channel detection methods. Therefore, in this paper, we conduct an in-depth examination of various GPU features and present Owl, a novel side-channel detection tool targeting CUDA applications on NVIDIA GPUs. Owl is designed to detect and locate side-channel leakage in various types of CUDA applications. When tracking the execution of CUDA applications, we design a hierarchical tracing scheme and extend the A-DCFG (Attributed Dynamic Control Flow Graph) to address the massively parallel execution in CUDA, ensuring Owl's detection scalability. After completing the initial assessment and filtering, we conduct statistical tests on the differences in program traces to determine whether they are indeed caused by input variations, subsequently facilitating the positioning of side-channel leaks. We evaluate Owl's capability to detect side-channel leaks by testing it on Libgpucrypto, PyTorch, and nvJPEG. Meanwhile, we verify that our solution effectively handles a large number of threads. Owl has successfully identified hundreds of leaks within these applications. To the best of our knowledge, we are the first to implement side-channel leakage detection for general CUDA applications.

关键词： Target tracking Statistical analysis Filtering Scalability Graphics processing units Side-channel attacks Feature extraction

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REPLACE: Real-time security Assurance in Vehicular Platoons Against V2V Attacks

REPLACE: Real-time Security Assurance in Vehicular Platoons ...

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IEEE Intelligent Transportation systems conference (ITSC)

作者： Boddupalli, Srivalli Hegde, Ashwini Ray, Sandip Univ Florida Dept Elect & Comp Engn Gainesville FL 32611 USA

ISBN: (纸本)9781728191423

Connected Autonomous Vehicular (CAV) platoon refers to a group of vehicles that coordinate their movements and operate as a single unit. The vehicle at the head acts as the leader of the platoon and determines the course of the vehicles following it. The follower vehicles utilize Vehicle-to-Vehicle (V2V) communication and automated driving support systems to automatically maintain a small fixed distance between each other. Reliance on V2V communication exposes platoons to several possible malicious attacks which can compromise the safety, stability, and efficiency of the vehicles. We present a novel distributed resiliency architecture, REPLACE for CAV platoon vehicles to defend against adversaries corrupting V2V communication reporting preceding vehicle position. REPLACE is unique in that it can provide real-time defense against a spectrum of communication attacks. REPLACE provides systematic augmentation of a platoon controller architecture with real-time detection and mitigation functionality using machine learning. Unlike computationally intensive cryptographic solutions REPLACE accounts for the limited computation capabilities provided by automotive platforms as well as the real-time requirements of the application. Furthermore, unlike control-theoretic approaches, the same framework works against the broad spectrum of attacks. We also develop a systematic approach for evaluation of resiliency of CAV applications against V2V attacks. We perform extensive experimental evaluation to demonstrate the efficacy of REPLACE.

关键词： Systematics Vehicular ad hoc networks computer architecture Machine learning Real-time systems Magnetic heads Safety

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A Powered-Up Classification of Disabling distributed Network Cloud-Based Attacks Using MLPNN-BP and MLPNN-LM 1

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3rd international conference on Machine Intelligence and Smart systems, MISS 2023

作者： Singh, Dhiraj Mishra, Rahul Centre for Interdisciplinary Research in Business and Technology Chitkara University Punjab Rajpura140401 India

ISBN: (数字)9783031317231

ISBN: (纸本)9783031317224

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 because they involve multiple computers working together to disable a service so that it can be taken offline entirely. By diminishing victim resources, the assaults prevent legitimate users from accessing the targeted services. In a classification problem, the classes are already defined and do not overlap before the method is applied, making classification itself a very straightforward problem to solve. Back Propagation (BP), Multi-Layer Perceptron Neural Network (MLP-NN), Levenberg-Marquardt (LM) method, MLPNN-BP, MLPNN-LM, and Radial Basis Function (RBF) were all proposed in this paper (RBF). It is possible that the BP algorithm can be employed successfully for training Neural networks (NN). After the learning phase, the MLP-NN is able to generalise to completely new data. During the training phase, the weights are optimised to minimise the occurrence of any specified error functions. The weight configuration used as a starting point by the LM algorithm is used by all MLP-NNs in this combination method. After the LM training is complete, MLP-NN will use the validation data's MSE to compute. RBF was developed to address the interpolation issue with multiple variables. This is an example of a local approximation of a NN, and it has a high approximation power, a high classification accuracy, and a fast learning rate. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Radial basis function networks

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Exploring Quantum Computing Use Cases for Critical National Infrastructures 23

Exploring Quantum Computing Use Cases for Critical National ...

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Proceedings of the 7th international conference on Future networks and distributed systems

作者： Maryah Alghamdi Sara Alghamdi College of Computer Science and Engineering King Fahd University of Petroleum and Minerals Saudi Arabia and Information Technology Engineering Department Aramco Saudi Arabia College of Computer Science and Engineering King Fahd University of Petroleum and Minerals Saudi Arabia and Cyberani Saudi Arabia

ISBN: (纸本)9798400709036

Quantum computing is one of the evolving fields within computer science. It leverages benefits from physics, mathematics, and quantum principles in order to develop a computer with capabilities not ever witnessed before. Such a computer is based on complex physics and is able to store and process data in units of "qubits" that enable electronics or photons to be available in more than one state simultaneously. A distinguishing characteristic of a quantum computer is its ability to perform certain calculations and solve or simulate complex problems exponentially faster than classical computers. From a governmental perspective, such a technology is a double-edged sword. A quantum computer that is able to break public-key cryptography may pose threats due to its potential to leak confidential and sensitive government information. On the other hand, quantum cryptography and quantum key distribution can lead to a secured communication where exchanged data are secured against cyber-attacks. Despite the absence of a fully realized quantum computer model, governments worldwide recognize the substantial potential of quantum technology to drive economic development and safeguard critical national security data, they have actively positioned themselves in the race to advance quantum technology. This survey reviews the research and development of several branches of quantum computing used for critical national infrastructures. It aims to map potential use cases of quantum computing with critical national infrastructure applications. The survey is divided into two main sections, namely, quantum communication and cryptography, and quantum networks, where each of these is further reviewed from different angles. This includes opportunities and challenges quantum computing can pose for governmental communications. Also, it reviews the advancement of quantum satellites and quantum drones for establishing a reliable quantum network. In addition, it touches on the use of quantum techno

关键词： National infrastructure Quantum Internet Quantum communication Quantum computing Quantum cryptography Quantum cybersecurity Quantum drone Quantum key distribution Quantum navigation Quantum satellite Space

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Break-Glass Conceptual Model for distributed EHR management system based on Blockchain, IPFS and ABAC 12

Break-Glass Conceptual Model for Distributed EHR management ...

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12th international conference on Emerging Ubiquitous systems and Pervasive networks, EUSPN 2021 / 11th international conference on Current and Future Trends of Information and Communication Technologies in Healthcare, ICTH 2021

作者： Saberi, Mohammad Ali Adda, Mehdi McHeick, Hamid Department of Computer Science Mathematics University of Quebec at Chicoutimi ChicoutimiG7H 2B1 Canada Department. of Computer Science Mathematics University of Quebec at Rimouski RimouskiG5L 3A1 Canada

The recently proposed Blockchain-based healthcare system proposes an interesting vision for the level of data integrity and security. This research aims to propose a conceptual model of a break-glass conceptual for Blockchain-based healthcare systems. In case of emergency, it provides access to the whole patient's medical records for healthcare professionals as quickly as possible regarding patients' privacy and data security. The proposed conceptual model was designed based on blockchain technology, IPFS (InterPlanetary File System), and ABAC (Attribute-Based Access control) as a novel design in this domain. In current healthcare systems, regulatory and non-integrated offline data sources make it near impossible for timely access to patients' EHRs and EMRs, even in case of emergencies for healthcare professionals. Our conceptual model could be a satisfactory alternative not only for patients but also for governing organizations to handle this situation clearly by regarding patients' privacy. Additionally, it can work in an untrusted environment, and it doesn't require bypassing the access control system to make the patients' data available. In case of emergencies, healthcare professionals receive medical records access near just in time with regard to all the rights of security and privacy based on the attribute which were set by the patients in the past. This novel conceptual model has been designed by coupling Blockchain technology with IPFS, and the attribute base control system (ABAC). © 2021 Elsevier B.V.. All rights reserved.

关键词： Access control

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VLDB workshops: international Workshop on Polystore systems for Heterogeneous Data in Multiple Databases with Privacy and security Assurances, Poly 2021 and 7th international Workshop on Data Management and Analytics for Medicine and Healthcare, DMAH 2021

VLDB workshops: International Workshop on Polystore Systems ...

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VLDB workshops: international Workshop on Polystore systems for Heterogeneous Data in Multiple Databases with Privacy and security Assurances, Poly 2021 and 7th international Workshop on Data Management and Analytics for Medicine and Healthcare, DMAH 2021

ISBN: (纸本)9783030936624

The proceedings contain 13 papers. The special focus in this conference is on Polystore systems for Heterogeneous Data in Multiple Databases with Privacy and security Assurances. The topics include: Administrative Health Data Representation for Mortality and High Utilization Prediction;Generating Longitudinal Synthetic EHR Data with Recurrent Autoencoders and Generative Adversarial networks;TRACE: Early Detection of Chronic Kidney Disease Onset with Transformer-Enhanced Feature Embedding;a Formal Category Theoretical Framework for Multi-model Data Transformations;towards Generic Fine-Grained Transaction Isolation in Polystores;Data Governance in a Database Operating System (DBOS);ACID-V: Towards a New Class of DBMSs for Data Sharing;Polystore systems and DBMSs: Love Marriage or Marriage of Convenience?;WIP: Pods: Privacy Compliant Scalable Decentralized Data Services;privacy-Preserving distributed Support Vector Machines;benchmarking Multi-instance Learning for Multivariate Time Series Analysis.

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Optimized Data Storage Algorithm of IoT Based on Cloud Computing in distributed System

Optimized Data Storage Algorithm of IoT Based on Cloud Compu...

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Emerging Trends in Industry 4.0 (ETI 4.0)

作者： K.Jaya Deepthi T.Suresh Balakrishnan Prabhakar Krishnan U.Samson Ebenezar Nageshwari Department of AIML Mohan Babu University Tirupati-2 AP India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai India IEEE Research Scientist Center for Cyber security Systems and Networks Amrita Vishwa Vidyapeetham Amritapuri-campus India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical SciencesSaveetha University Chennai Tamil Nadu India Department of Computer Science and Engineering CARE College of Engineering Trichy Tamil Nadu

ISBN: (数字)9798350373783

ISBN: (纸本)9798350373790

IoT and cloud technology are vital for large systems. An improved data storage technique for IoT applications and cloud distribution is described in this research. Scalability, reliability, latency, and resource usage are internal and external to the algorithm. The approach above scales well with work portion or dataset size. The first experiment shows the algorithm scaling perfectly even as IoT devices generate additional data. Experiment 2 proves linear scalability works for 100,000 IoT devices, while Experiment 3 efficiently organizes 1 million data points. It proved the algorithm by tolerating manufactured faults. To ensure data service availability, Experiment 1 tests the system’s operational dependability on node failures and network disturbances. With 0.1% downtime even under challenging conditions, experiment 2 showed the algorithm’s incredible robustness in real-world applications. To improve data organization, this experiment exhibits data consistency when nodes fail. Lower and constant time improves operation safety and reliability. Algorithm 1 shows how the algorithm can quickly answer data queries and keep up with the massive amount of data transfers, supporting low-latency IoT applications. Average data retrieval latency of experiment 2 is 10 ms, which is real-time for vital information. Trial 3 processes data online with a latency <20 ms, providing fast insights for speedy response and decision-making. The adaptive distributed workload uses little resources, making the approach efficient. Exp1 uses distributed nodes to share data and processing, improving task efficiency. In experiment 2, 60% of the CPU, 70% of the Memory tool, and 80% of the Storage system are used, demonstrating platform resource efficiency. Trial 3 provides optimal resource allocation with less than 5% waste, making it an effective system that passes all performance benchmarks.

关键词： Cloud computing Scalability Decision making Memory distributed databases Robustness Real-time systems

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security and Privacy Enabled Framework for Online Social networks using Blockchain

Security and Privacy Enabled Framework for Online Social Net...

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Electronics and Sustainable Communication systems (ICESC), 2020 international conference on

作者： Arvind Kumar Tushar Vyas Saleem Ahmed Nitin Girdharwal E. Vijayakumar Arivanantham Thangavelu MRIIRS Faridabad Haryana India Department of CSE JECRC University Jaipur Rajasthan India Oryx Universal College Doha Qatar Prestige Institute of Management & Research (PIMR) Indore Madhya Pradesh India KIT- Kalaignar Karunanidhi Institute of Technology Coimbatore Tamilnadu India Computer Engineering Dr. D. Y. Patil College of Engineering and Innovation Varale Talegaon Pune Maharashtra India

Users may easily deal with data overload concerns while navigating Online Social networks (OSN) through suggestion engines. In addition, it increases a number of privacy-related issues, particularly for users who would rather remain anonymous on OSNs. Furthermore, certain vendors of services sell consumer data to other organizations without the consumer’s awareness as a result of the exploitation of online consumer data, which undermines user confidence in the vendors of services. Such issues demand a solution that gives consumers of technology the independence and authority they sorely need over their data. As blockchain technology develops, numerous research organizations are working with distributed techniques to find a solution to the privacy invasion and hacking problem that OSN users face. A blockchain-based hybrid framework for confidentiality maintenance is proposed, to overcome these restrictions. To guarantee the confidentiality and anonymity of user data, two smart contracts, SCSGI and SCSTI are created. While the SCSTI retains information, the SCSGI controls transfer of user information. To identify rebellious nodes, a Graph Attention Network (GAT) was incorporated into the blockchain-enabled platform. The research and trial findings reveal that the suggested approach exemplifies efficacy and confidentiality of consumers in the system.

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Optimizing Energy Management and Load Balancing Through AI-Driven Quantum Approximate Optimization

Optimizing Energy Management and Load Balancing Through AI-D...

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Mobile networks and Wireless Communications (ICMNWC), IEEE international conference on

作者： Manjunath Kamath K Manasa M Anitha B. S Mahadevi Falguni Tlajiya Sangramjit Chavan Department of Cyber Security NMAM Institute of Technology NITTE (Deemed to be University) Karkala India Department of Artificial Intelligence and Machine Learning Brindavan College of Engineering Bengaluru India Department of Computer Science Sarada Vilas College Mysuru India Department of Electrical Engineering Parul institute of Engineering and Technology Parul University Gujarat India Symbiosis Law School (SLS) Symbiosis International (Deemed University) (SIU) Pune India

ISBN: (数字)9798331528348

ISBN: (纸本)9798331528355

The integration of Quantum Approximate Optimization Algorithm (QAOA) and Quantum Annealing (QA) offers a promising approach to addressing energy management and load balancing challenges in modern power systems. This study explores the application of these quantum computing techniques, coupled with Artificial Intelligence (AI), to optimize energy distribution across smart grids. The proposed hybrid model leverages the problem-solving capabilities of QAOA for discrete optimization and the real-time adaptability of QA for minimizing energy consumption and operational costs. AI techniques are employed to predict energy demand, balance loads, and ensure efficient resource allocation. Simulations were conducted on a smart grid scenario involving renewable energy sources, varying demand, and distributed energy generation. The results demonstrate that the hybrid model achieved a 25% improvement in load balancing efficiency and a 30% reduction in energy wastage compared to traditional optimization methods. Additionally, the model reduced peak energy demand by 20%, contributing to overall grid stability. The quantum-enhanced approach also decreased computational complexity by 40%, enabling faster decision-making in dynamic environments. These findings highlight the potential of combining quantum algorithms with AI for sustainable and efficient energy management.

关键词： Data centers Renewable energy sources Quantum algorithm Computational modeling Power system stability Load management Quantum annealing Artificial intelligence Optimization Load modeling

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