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Mobile Computing and Sustainable Informatics (ICMCSI), International Conference on

作者： C. Sathiyapriyan B. Manikandan S. Gokul Rewin Satheesh S. Nivetha S. Leelavathy Department of Computer Science and Engineering Cyber Security Aarupadai Veedu Institute of Technology Chennai Department of Computer Science and Engineering Aarupadai Veedu Institute of Technology Chennai Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai

Ensuring the security of web applications is paramount in safeguarding sensitive data and maintaining user trust. This study presents a comprehensive overview of strategies for building and maintaining secure web applications, acknowledging their inherent limitations and outlining potential areas for future work. The strategies discussed encompass fundamental aspects of web application security, including input validation and sanitization, robust authentication and authorization mechanisms, secure communication through HTTPS, timely security patching, implementation of security headers, monitoring and logging, client-side security measures, and vigilance in handling third-party components.. This research employed algorithms include Routing Algorithms, Middleware Execution Order Algorithms, Eloquent ORM Algorithms, Encryption and Hashing Algorithms, Session Handling Algorithms, Queue Management Algorithms, and Dependency Injection Algorithms.

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Asymmetric Channel Reuse Model for Wi-Fi 6

Asymmetric Channel Reuse Model for Wi-Fi 6

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International Conference on Emerging Technologies, ICET

作者： Aitizaz Uddin Syed Safdar Nawaz Khan Marwat Cyber Security Operations Ministry of Justice Doha Qatar Department of Computer Systems Engineering Faculty of Electrical and Computer Engineering University of Engineering and Technology Peshawar Pakistan

ISBN: (数字)9798350379587

ISBN: (纸本)9798350379594

Channel reuse is an effective technique to reutilize the limited resource of the frequency radio spectrum to fulfill the ever-increasing demands of wireless communication. Implementing the channel reuse in Wi-Fi 6 by embedding the new enhancements of Channel Bonding, Beamforming, and utilizing reclaimed channels of the 5 GHz spectrum creates an asymmetric behavior. In this paper, we propose and investigate the Asymmetric Channel Reuse Model (ACRM) for 160 MHz communication in the presence and absence of Terminal Doppler Weather Radar (TDWR) channels at 5 GHz spectrum. In both conditions, we observe significant improvement in throughput and SINR compared to known symmetric channel reuse models.

关键词： Wireless communication Meteorological radar Array signal processing IEEE 802.11ax Standard Interference Throughput Doppler radar Bonding Signal to noise ratio Meteorology

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A System security Strategy Implementation for Secured Data Communication System 5

A System Security Strategy Implementation for Secured Data C...

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5th IEEE International Conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Madhumala, V.S. Tripathi, Pradeep Kumar Rana, Priya Sharma, Nitin Kumar Yamsani, Nagendar Shashikant Cyber Security Department Vignana Bharathi Institute of Technology Hyderabad India Ajay Kumar Garg Engineering College Department of Information Technology Ghaziabad India Raj Kumar Goel Institute of Technology Department of Information Technology Ghaziabad India Nitra Technical Campus Department of Cse Ghaziabad India Sr University School of Computer Science and Artificial Intelligence Warangal India Babu Banarasi das University School of Engineering Electrical Engineering Department Lucknow India

ISBN: (纸本)9798350383522

The digital age is one of omnipresent digital information and network access. As such, it is essential for any enterprise to make the security of their office networks a top priority. However, due to the rapid spread of sophisticated malware using increasingly varied technological hazardous methods and the looming possibility of data breaches, confidentiality and security of sensitive information in office settings is difficult in many cases. That's why it has become increasingly important for organizations to implement robust, proactive, and cost-effective network security solutions. This revolutionary project was through the capability of ESP8266 Wi-Fi boards, called Innovative Workplace Network security Approaches for Malware The process of detection, security Mitigation, and Data Protection It is IDS that meets the tailored need of office network scenarios. The Major themes in intrusion detection systems are malware detection, threat reduction, and data protection all in the manner of the IDS methodology applied in this project. Nowadays referred to as the heart of modern enterprises, the office network is a larger world where every kind of device and person connects with digital resources. To protect this complex ecosystem from cyber threats, we need to be on our guard every minute and respond quickly to any irregularity found in real-time. Our research offers a new answer because using ESP8266-based IDS can enhance the network security posture of office networks;only network security measures alone may not be sufficient in light of the steadily shifting threat landscape. In this system, both the focus and aim is the ESP8266-based Intrusion Detection System This system also provides a fine demonstration of its efficacy in shoring up office network security. To do this, we are combining the development of cutting-edge hardware with clever software design and careful threat data management. Consequently, our project represents a significant step forward in the st

关键词： Network security

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Real-time consumer aware and alert system based on smart water tank

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Materials Today: Proceedings 2022年 63卷 790-797页

作者： Khan, Fazal Qudus Ahmad, Ibrar Fawzi Khairullah, Enas Bajaber, Osama Ullah, Anayat Jan, Sadeeq KPK Shangla Pakistan Department of Information Technology Faculty of Computing and Information Technology King AbdulAziz University Jeddah Saudi Arabia National Center for Cyber Security Department of CS&IT University of Engineering & Technology Peshawar Pakistan

As population is growing water scarcity is becoming a raising issue year after year. The reasons may vary but there are two main factors which could be considered as key reasons of water shortages. Fresh water sources in Saudi Arabia are very limited and water desalination plants can't cover the high demand. omeowners should pay higher attention to their faucet's leakages, not only to reduce water wastage but leakages could also impact their own water expenses in addition to our environment and economy. This project presents two tiers (homeowner / national water company) water shortage solution, we can't control the sources in our technical field, but we can improve water distribution system and develop a water monitoring system for clients. Our prototype consists of two parts. A web site to display statistical information and illustrations of different types of estimates and calculations, for national water employees to make water distribution decision more efficient besides clients to monitor their consumption rate and notice alerts of any leakages. The second part of our project focuses on hardware which well be sensing the water level and consumption then send the readings to the server to be presented on the website. It has an ultrasonic sensor installed in water container to detect water level, also there are three faucets each one is connected to a flow meter sensor to detect amount of dispensed water. All sensors are connected to a microcontroller where we embedded functions contains algorithms to calculate consumption rate, leaks detection and tank level to be sent through the Ethernet shield to the website. Finally, our monitoring approach is inexpensive and will reduce shortages by guiding the water pumping only to most needed districts;also, it will take care of water wastage issue approximately around 40% water can be stored using this developed technology. © 2022

关键词： Real time systems

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The Role of Smart Contracts in Revolutionizing Supply Chain Finance with Blockchain 2

The Role of Smart Contracts in Revolutionizing Supply Chain ...

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2nd IEEE International Conference on IoT, Communication and Automation technology, ICICAT 2024

作者： Kumar, Rakesh Surekha, N. Rao, Cherukupalli Mallikarjuna Al-Fatlawy, Ramy Riad Bhuvaneshwari, P. Raja, Lakshmi GLA University Department of Computer Engineering & Applications Mathura India CMR College of Engineering & Technology Department of CSE India GRIET Bachupally Department of CSE Telangana Hyderabad India The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq New Prince Shri Bhavani College of Engineering and Technology Department of CSE Tamil Nadu Chennai600073 India Karpagam Academy of Higher Education Department of Cyber Security Coimbatore641021 India

ISBN: (纸本)9798350368109

Focusing on revolution of Supply Chain Finance (SCF) through the help of smart contracts and blockchain technology, this work aims to identify the potential of this field. Global supply chain finance management using smart contracts can help in improving efficiency, transparency and security of the key process, thus minimizing transaction time and cost. I choose both qualitative and quantitative data collection methods as a research approach to elicit information about the benefits and difficulties of blockchain implementation in SCF. The results also highlighted that considerable performances such as speed, cost, and accuracy of the transactions are enhanced when undertaken through smart contracts and the impact of applying smart contract in supply chain. The results have highlighted the need for additional research in terms of scalability and the regulation of polycentric platforms. © 2024 IEEE.

关键词： Smart contract

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Neural Network-Based Multi-class Model for Abnormal Heartbeat Audio Signal Detection

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SN computer Science 2025年第1期6卷 1-16页

作者： Kashyap, Pavan P. Madihalli, Revanasiddappa B N, Kavitha S, Santosh Kumar N, Ravi Kumar B Rohith, S. Department of CSE (Cyber Security) Sri Venkateshwara College of Engineering Bengaluru 562157 India Department of Civil Engineering Sri Venkateshwara College of Engineering Bengaluru 562157 India Department of Mathematics Sri Venkateshwar College of Engineering Bengaluru 562157 India Department of CSE (Data Science) Sri Venkateshwara College of Engineering Bengaluru 562157 India Department of CSE BMS Institute of Technology & Management Yelahanka Bengaluru 560119 India Department of Electronics and Communication Engineering Nagarjuna College of Engineering and Technology Bengaluru 562164 India

Detection of abnormal heartbeats, or arrhythmias, is crucial for early diagnosis and management of cardiac diseases. Traditional methods, such as manual auscultation and basic signal processing techniques, often fall short in accuracy and depend heavily on the expertise of the practitioner. In this paper, we introduce a novel neural network-based multi-class model designed to enhance the detection of abnormal heartbeat audio signals. The model leverages convolutional neural networks (CNNs) to automatically extract intricate features from heartbeat audio signals, thus eliminating the need for manual feature engineering. The proposed system preprocesses the raw audio signals by employing noise reduction techniques, normalization, and segmentation into short, manageable frames. These frames are then processed by several convolutional layers, which learn hierarchical representations of the audio features. The extracted features are subsequently classified into multiple classes using fully connected layers, employing a softmax function to ensure proper probability distribution over the classes. The performance of the proposed model is rigorously evaluated using a comprehensive dataset containing various types of abnormal heartbeats. The dataset is split into training, validation, and test sets to ensure unbiased performance evaluation. The model is trained using cross-entropy loss and optimized with the Adam optimizer, incorporating early stopping and regularization techniques to prevent overfitting. Our experimental results demonstrate that the proposed model significantly outperforms traditional methods, achieving a classification accuracy of 95.2%, precision of 94.8%, recall of 95.1%, and an F1-score of 94.9%. The study highlights the potential of deep learning approaches, specifically CNNs, in capturing the nuanced patterns in heartbeat audio signals, making it a valuable tool for clinicians. By enabling early and accurate detection of arrhythmias, the model can aid

关键词： Abnormal heartbeat detection Audio signal processing Deep learning Multi-class classification Neural networks

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AntiMal: an Approach of Malware Detection Employing Swin Transformer 13

AntiMal: an Approach of Malware Detection Employing Swin Tra...

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13th International Conference on Communication and Network security, ICCNS 2023

作者： Lyu, Chenxi Yao, Yinan Guo, Xiaodong Huang, Zihong Dong, Chen Zhang, Yuanyuan Chen, Zhenyi College of Computer and Data Science Fuzhou University Fuzhou China College of Computer and Cyber Security Fujian Normal University Fuzhou China Department of Computer Science and Engineering University of South Florida FL United States

ISBN: (纸本)9798400707964

In the present era, the menace of malicious software is growing continuously, posing a significant challenge in the realm of cybersecurity. Currently, traditional machine learning algorithms have been widely applied to the analysis of malicious software and are considered effective methods. However, these approaches often require extensive feature engineering, feature learning, and feature representation, which can be time-consuming and resource-intensive. In this paper, a method for the identification of malicious software, named "AntiMal,"is proposed. This method utilizes the Swin Transformer as the backbone network and combines it with image features for static analysis. It leverages the dataset provided by Microsoft for the Kaggle Microsoft Malware Classification Challenge. Initially, it converts the binary data of malicious code into grayscale images, treating every 8 bits as a pixel. Subsequently, it employs PyTorch to build and train the Swin Transformer, classifying the images in the validation set. The results demonstrate that this approach excels in the problem of malicious software classification, achieving an impressive accuracy of up to 95%, showcasing remarkable precision and generalization capabilities. Furthermore, it exhibits significant advantages when dealing with large datasets, requiring fewer computational resources, thus offering exceptional computational efficiency. © 2023 ACM.

关键词： Malware

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AI-Based Intelligent Model to Predict Epidemics Using Machine Learning Technique

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Intelligent Automation & Soft Computing 2023年第4期36卷 1095-1104页

作者： Liaqat Ali Saif E.A.Alnawayseh Mohammed Salahat Taher M.Ghazal Mohsen A.A.Tomh Beenu Mago College of Engineering and Technology University of Science and Technology of FujairahFujairahUAE Electrical Engineering Department Faculty of EngineeringMutah UniversityJordan School of Information Technology Skyline University CollegeUniversity City Sharjah1797UAE Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan Malaysia43600Malaysia Faculty of Computer Science NCBA&ELahore54660Pakistan School of Information Technology Skyline University CollegeUniversity City Sharjah1797SharjahUAE

The immediate international spread of severe acute respiratory syn-drome revealed the potential threat of infectious diseases in a closely integrated and interdependent *** an outbreak occurs,each country must have a well-coordinated and preventative plan to address the *** and Communication Technologies have provided innovative approaches to dealing with numerous facets of daily *** intelligent devices and applica-tions have become a vital part of our everyday lives,smart gadgets have also led to several physical and psychological health problems in modern ***,we used an artiﬁcial intelligence AI-based system for disease prediction using an Artiﬁcial Neural Network(ANN).The ANN improved the regularization of the classiﬁcation model,hence increasing its *** unconstrained opti-mization model reduced the classiﬁer’s cost function to obtain the lowest possible *** verify the performance of the intelligent system,we compared the out-comes of the suggested scheme with the results of previously proposed *** proposed intelligent system achieved an accuracy of 0.89,and the miss rate 0.11 was higher than in previously proposed models.

关键词： Intelligent model epidemics artiﬁcial intelligence machine learning techniques

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Strengthening KMS security with Advanced Cryptography, Machine Learning, Deep Learning, and IoT Technologies

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SN computer Science 2023年第5期4卷 1-13页

作者： Ogala, Justin Onyarin Ahmad, Shahnawaz Shakeel, Iman Ahmad, Javed Mehfuz, Shabana Department of Cyber Security University of Delta Agbor Nigeria Department of Computer Science & Engineering Mewat Engineering College (WAQF) Mewat Haryana Nuh 122107 India Department of Electrical Engineering Jamia Millia Islamia (A Central University) New Delhi 110025 India Department of Computer Science School of Engineering Sciences & Technology (SEST) Jamia Hamdard (Deemed to be University) Hamdard Nagar New Delhi 110062 India

This paper presents an innovative approach to strengthening Key Management Systems (KMS) against the escalating landscape of cyber threats by integrating advanced cryptographic technologies, machine learning, deep learning, and the Internet of Things (IoT). As digital reliance and cyber-attacks surge, strengthening KMS security becomes paramount. Our research provides a comprehensive overview of the state-of-the-art in cloud data security, identifying key vulnerabilities in existing KMS. The paper also outlines a distinctive framework based on the combined application of advanced cryptography, machine learning, deep learning, and IoT, which represents a novel approach in the quest for robust KMS security. Our experimental results substantiate the efficacy of this unique blend of technologies, providing solid empirical evidence that such a fusion can successfully strengthen KMS against potential threats. As technologies and threat landscapes continue to evolve, our framework can serve as a benchmark for future research and practical implementations. It highlights the potential of integrated technological solutions to counter complex cybersecurity issues. Moreover, the approach we've developed can be adapted and expanded to cater to the specific needs of different sectors, such as finance, healthcare, and e-commerce, which are particularly vulnerable to cyber threats. The novelty of our work lies in the amalgamation of the four technologies and the creation of an empirically backed, robust framework, marking a significant stride in KMS security. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Cloud computing Cryptographic technologies DL IoT KMS ML

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On Multi-Key FuncCPA Secure Encryption Schemes 1

On Multi-Key FuncCPA Secure Encryption Schemes

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1st International Conference on Cryptography and Information security, VCRIS 2024

作者： Nakajima, Eri Hara, Keisuke Yamashita, Kyosuke Osaka University Department of Information and Computer Sciences Osaka Japan National Institute of Advanced Industrial Science and Technology Cyber Physical Security Research Center Tokyo Japan Yokohama National University Kanagawa Japan

ISBN: (纸本)9798331529949

The notion of funcCPA security for homomorphic encryption schemes was introduced by Akavia et al. (TCC 2022). Whereas it aims to capture the bootstrapping technique in homomorphic encryption schemes, Dodis et al. (TCC 2023) pointed out that funcCPA security can also be applied to non-homomorphic public-key encryption schemes (PKE). As an example, they presented a use case for privacy-preserving outsourced computation without homomorphic computation. It should be noted that prior work on funcCPA security, including the use case presented by Dodis et al., considered only the single-key setting. However, in recent years, multi-party collaboration in outsourced computation has garnered significant attention, making it desirable for funcCPA security to support the multi-key setting. Therefore, in this work, we introduce a new notion of security called Multi-Key funcCPA (MKfunc) to address this need, and show that if a PKE scheme is KDM-secure, then it is also MKfuncCPA secure. Furthermore, we show that similar discussions can be applied to symmetric-key encryption. © 2024 IEEE.

关键词： Encryption algorithms

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