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2022 IEEE Asia-Pacific Conference on computer science and Data engineering, CSDE 2022

作者： Nahar, Mahbubun Kamal, A.H.M. Jatiya Kabi Kazi Nazrul Islam University Dept. of Computer Science and Engineering Trishal Bangladesh

ISBN: (纸本)9781665453059

While hiding data in DNA sequence, the steganograpy schemes try to increase the embedding payload, enhance the security of implanted data, protect the stego expansion and preserve the biological characteristics of DNA sequence. In this research, we have proposed a new data hiding method where the scheme implants secrets in DNA sequence using a classical Toffoli quantum gate mechanism. The proposed scheme implants 4-bits of information per nucleotide. Experimental results demonstrate that the proposed scheme achieves massive improvement over the others which is 4 to 12-times higher than the competing schemes. © 2022 IEEE.

关键词： Steganography

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RAPUF: A Novel Integration of Reversible Logic and Arbiter Physical Unclonable Functions for Enhancing IoT Security

RAPUF: A Novel Integration of Reversible Logic and Arbiter P...

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Artificial Intelligence, computer, Data sciences and Applications (ACDSA), International Conference on

作者： Dominick Rizk Frederic Rizk Patrick Rizk Rodrigue Rizk Dept. of Electrical Engineering and Computer Science The Catholic University of America Washington DC USA The Center for Advanced Computer Studies University of Louisiana at Lafayette Lafayette LA USA Dept. of Mechanical Engineering University of Quebec at Trois-Rivières Drummondville Canada Dept. of Computer Science University of South Dakota Vermillion SD USA

The Internet of Things (IoT) devices’ proliferation underscores the critical importance of fortifying nanoscale circuit security against evolving cyber threats. This paper introduces an unprecedented paradigm to enhance IoT security through the synergistic integration of reversible logic gates and Arbiter Physical Unclonable Functions (APUFs). Reversible logic, known for its theoretical efficiency and energy conservation, is coupled with APUFs, leveraging their unique ability to exploit nanoscale manufacturing variations for robust hardware security. The novel integration is specifically tailored to address the distinctive security challenges prevalent in IoT ecosystems. The proposed methodology encompasses designing and implementing a secure nanoscale circuit system, tailored to the resource constraints of IoT devices. Through an exhaustive literature review, we establish the significance of reversible logic and APUFs in the broader context of nanoscale circuit design and IoT security. The experimental results demonstrate not only the feasibility of the integrated approach but also its effectiveness in fortifying IoT devices against unauthorized access and data breaches. This research contributes a fresh perspective to the field of IoT security, presenting a novel solution that combines energy-efficient reversible logic with the intrinsic security features of APUFs. The outcomes of this work hold promise for advancing the security paradigm of IoT devices ensuring their resilience against emerging threats in the ever-evolving landscape of cybersecurity and contributing significantly to the evolving field of quantum-enhanced IoT security.

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Trust management based multidimensional secure cluster with RSA cryptography algorithm in WSN for secure data transmission

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Measurement: Sensors 2023年 29卷

作者： Anitha, S. Saravanan, S. Chandrasekar, A. Dept. of Computer Science and Engineering Annamalai University Annamalainagar 608002 India Dept. of Computer Science and Engineering St.Joseph's College of Engineering Chennai India

WSNs are now widely used for information gathering and transmission using WSN. Due to its low cost and simple communication, this type of network is widely used in many applications. Although hierarchical routing protocols may handle a variety of applications, choosing a Cluster Head (CH) and balancing network overload are difficult problems. This recommended strategy provides LEACH Protocol based on Novel Trust Management with Cryptographic RSA algorithm (NTM-LEACH-RSA) to extend the lifetime of network and to consume less energy. Here the proposed methodology includes two aspects for improving Security in WSN. Using the suggested NTM-LEACH technique, cluster formation and cluster head election are carried out in the first phase. Here, the threshold function value, the distance and density between nearby nodes, and the trust value are used to elect the cluster head. Based on the energy domain and the distance domain, the threshold function value is estimated in this case. The RSA cryptography technique is employed in the second phase to protect data transmission and guarantee data integrity. By using simulation tools, the proposed NTM-LEACH-RSA methodology's performance analysis is estimated. In comparison to other algorithms currently in use, it also offers higher performance results. © 2023

关键词： Data transfer

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Modeling Data Flows of a System for Analyzing Messages in Social Networks

Modeling Data Flows of a System for Analyzing Messages in So...

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2022 International Conference "Quality Management, Transport and Information Security, Information Technologies", IT and QM and IS 2022

作者： Bekeneva, Yana A. Lopushansliy, Alexandr M. Kulikov, Alexandr I. Saint Petersburg Electrotechnical University Leti Dept. of Computer Science and Engineering St-Petersburg Russia

ISBN: (数字)9781665488709

ISBN: (纸本)9781665488709

There is a problem associated with an overabundance of information: users write hundreds of posts every day, leave thousands of comments, which makes it difficult to search, structure and analyze useful data. Especially in the case of creating a distributed network, it is also important to calculate the load on the network so that it works smoothly and as quickly as *** paper describes the creation of a system for modeling data flows of a message analysis system in social networks with the ability to change the composition and structure of a distributed network to estimate the amount of transmitted traffic with a different number of processing points for incoming data. © 2022 IEEE.

关键词： Data transfer

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Skin Cancer Detection Using CNN and Ensemble Learning 1

Skin Cancer Detection Using CNN and Ensemble Learning

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1st IEEE International Conference on Advances in Signal Processing, Power, Communication, and Computing, ASPCC 2024

作者： Samantaray, Ruturaj Afrin, Karishma Behera, Bichitrananda Bag, Kirtimayee Tata Consultancy Services Limited Tcs BaNCS Bangalore560066 India C. V. Raman Global University Dept. of Computer Science and Engineering Bhubaneswar752054 India

ISBN: (纸本)9798350355093

The global prevalence of skin cancer has seen a concerning increase over recent decades, now accounting for one in every three cancer cases worldwide. The unchecked growth of aberrant cells in the skin can lead to skin cancer, a potentially fatal illness. There are different types of skin cancer, namely, DF (Dermatofibroma), AKIEC (Actinic Keratoses and Intraepithelial Carcinoma), Mel (Melanoma), BCC (Basal Cell Carcinoma), VASC (Vascular Lesions), BKL (Benign Keratosislike Lesions), and NV (Melanocytic Nevi). Skin cancer can spread to nearby tissues in our body if it is not caught early. Presently, diagnosing skin cancer is a time-consuming and financially burdensome process for both patients and healthcare systems. Moreover, diagnosing skin cancer heavily relies on human cell detection. Skin cancers can be dangerous if they are not treated before they have a chance to spread. However, existing technology lacks the ability to detect skin cancer accurately. Traditional machine learning algorithms display limitations when classifying different classes of skin cancer. In this research, we have proposed skin cancer detection with classification using CNN and ensemble learning. CNN, known as the Convolutional Neural Network, represents a specialized architecture within deep learning algorithms primarily tailored for image recognition and feature extraction. It comprises convolutional, pooling, and fully connected layers in its mathematical structure. In this work, CNN (Convolutional Neural Network) is employed for image feature extraction, followed by utilizing three distinct classifier algorithms, namely, SVM (Support Vector Machine), KNN (K-Nearest Neighbour), and DT (Decision Tree), integrated through an ensemble approach utilizing a voting system. Despite utilizing multiple classifiers, the model exhibits impressive performance, achieving a classification accuracy of 98%. Notably, our research leverages the HAM10000 dataset for this study. © 2024 IEEE.

关键词： Convolutional neural networks

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Visualization Tool for NYC Open Data - A Time Lapse Analysis

Visualization Tool for NYC Open Data - A Time Lapse Analysis

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Conference on Technologies for Sustainability (Sustech)

作者： Alan Yuan Guang Wei Too Yihan Xu Ziqian Dong Huanying Gu Roberto Rojas-Cessa Dept. of Computer Science New York Institute of Technology New York City NY USA Dept. of Electrical and Computer Engineering New York Institute of Technology New York City NY USA Dept. Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

ISBN: (数字)9798331504311

ISBN: (纸本)9798331504328

In this paper, we present a web-based tool that maps and visualizes datasets from New York City (NYC) Open Data, specifically on building energy efficiency and fallen trees reported to NYC311, as heatmap or pin map to show building energy efficiency and weather event impact at a neighborhood level over time. To evaluate its effectiveness in addressing climate-related urban challenges, we applied the tool to two case studies from NYC Open Data: the ENERGY STAR Score and Fallen Trees datasets. We demonstrate the heat map function for the ENERGY STAR Score dataset and the use of a combination of heat and pin map functions of the Fallen Trees dataset to highlight spatial and temporal patterns. The interactive visualization tool effectively provides data distribution and trend analysis based on postal codes while also allowing for precise, location-specific insights using longitude and latitude. Beyond its applications in data visualization, the tool can facilitate decision-making in the design of future urban environments.

关键词： Heating systems Visualization Urban areas Buildings Stars Energy efficiency Pins Heat maps Sustainable development Open data

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An Overview of Protocols-Based Security Threats and Countermeasures in WLAN 4

An Overview of Protocols-Based Security Threats and Counterm...

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4th International Conference for Emerging Technology, INCET 2023

作者： Ojha, Nitish Kumar Baray, Elyas Indian Institute of Information Technology Dept. of Information Technology Allahabad211012 India Sharda University Knowledge Park - III Dept. of Computer Science and Engineering Greater Noida201310 India

ISBN: (纸本)9798350335750

WLAN security protocols are the most important section for wireless networks which controls all the security-related issues by securing the network with some pre-defined rules made by wireless-protected access organizations, further which makes it the main target of hacking and threats by interested parties and to be safe from such threats. There should be countermeasures for such threats where there will be a solution for any threat encountered and to mention. WIFI or wireless local area Network is a cost-effective easy deployment Network that makes users take advantage of vast data shared on the internet and by the network without the need for any cable for connections. Here in this overview paper by reviewing many researchers' techniques and works on the WLAN security topic, there are shared threats to WLAN and the ways of taking precautions against those threats as countermeasures and for which the tables are used. For comparison of techniques used by authors and some famous and highly dangerous threats are also defined further. WPA3's new security protocol is also defined with its newly found vulnerabilities and countermeasures except there is a conclusion on the downgrade attack problem with WPA3. Further, there are also countermeasures for that as well, nowadays people think the network is secured with standards defined by the IEEE organization but some know this is not the case so it makes it a more important area for research. © 2023 IEEE.

关键词： Wireless local area networks (WLAN)

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Financial Viability of PV Grid for an Intelligent System of Residential Buildings in sub-urban Areas of Punjab, Pakistan

Financial Viability of PV Grid for an Intelligent System of ...

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Power Electronics and Control (SEPOC), Seminar on

作者： Moazzam Shehzad Nasir Jamal Hafiz Abdul Muqeet Noman Sohaib Qureshi Dept. of Electrical Engineering Lincoln University College Petaling Jaya Malaysia Dept. of Electrical Engineering Punjab Tianjin University of Technology Lahore Pakistan Dept. of Computer Science University of Engineering and Technology (RCET Campus) Lahore Pakistan

ISBN: (数字)9798350379419

ISBN: (纸本)9798350379426

With fuel prices rising and environmental concerns intensifying, the financial burden on consumers and businesses has shown an upward trajectory, prompting a search for sustainable alternatives sources. This study investigates the financial feasibility of installing a grid-tied solar photovoltaic (PV) system in residential buildings in suburban areas of Punjab, Pakistan. The research uses a complete intelligent financial model to assess the feasibility of a grid-connected solar PV system, incorporating parameters such as solar irradiance levels, system size, capital costs, operating expenses, energy rates, its incentives, and payback periods in a systematic computational optimization methodology. The shift to solar photovoltaic systems provides an affordable way to lower energy bills that can also lessen the dependency on fossil fuels. Additionally, solar PV systems help significantly to reduce greenhouse gas emissions and environmental damages by utilizing the clean energy of the sun. This is in line with worldwide efforts to battle climate change and protect the planet from environmental concerns. This research uses RET Screen software to evaluate the financial feasibility with GHG reduction analysis as well. The study’s findings are useful for homeowners, policymakers, and stakeholders interested in encouraging renewable energy adoption and sustainable development in Punjab, Pakistan’s suburban region.

关键词： Climate change Meters Computational modeling Optimization methods Fuels Pricing Power grids Photovoltaic systems Financial management Energy management Buildings Solar power generation Economics

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Machine Learning Techniques for Identifying Child Abusive Texts in Online Platforms

Machine Learning Techniques for Identifying Child Abusive Te...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Tanjim Mahmud Tahmina Akter Mohammad Kamal Uddin Mohammad Tarek Aziz Mohammad Shahadat Hossain Karl Andersson Department of Computer Science and Engineering Rangamati Science and Technology University Rangamati Bangladesh Dept. of Computer Science and Engineering Port City International University Chittagong Bangladesh Department of Computer Science and Engineering Chittagong University of Engineering & Technology Chittagong Bangladesh Dept. of Computer Science and Engineering University of Chittagong Chittagong Bangladesh Cybersecurity Laboratory Luleå University of Technology Luleå Sweden

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

This study addresses the critical issue of child abuse in digital communications by developing advanced machine learning and deep learning models for detecting child abusive texts in the Bengali language on online platforms. The primary goal of this research is to contribute to child abuse prevention by creating an effective tool for accurately identifying abusive content. Utilizing a combination of natural language processing (NLP) techniques and deep learning algorithms, this model distinguishes between abusive and non-abusive text. The dataset, comprising manually collected and labeled comments and posts from social media sites, is categorized into Positive, Neutral, and Negative classes. For model development, a variety of machine learning algorithms including RF, DT, and SVM, alongside deep learning approaches such as LSTM and CNN, were tested. The performance of the proposed model was assessed using precision, recall, and F1 score metrics. The findings reveal that the model performs with high accuracy in classifying abusive text in Bengali, offering significant potential as a tool for effective child abuse identification and prevention.

关键词： Deep learning Support vector machines Radio frequency Measurement Machine learning algorithms Social networking (online) Prevention and mitigation Computational modeling Natural language processing Long short term memory

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Impact Analysis of Contributing Factors of NYC Flash Floods with Interpre table Machine Learning

Impact Analysis of Contributing Factors of NYC Flash Floods ...

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Conference on Technologies for Sustainability (Sustech)

作者： Yihan Xu Alan Yuan Guang Wei Too Yordan Nikolov Ziqian Dong Roberto Rojas-Cessa Dept. of Electrical and Computer Engineering New York Institute of Technology New York City NY USA Dept. of Computer Science New York Institute of Technology New York City NY USA Dept. of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

ISBN: (数字)9798331504311

ISBN: (纸本)9798331504328

In this paper, we analyze multi-modal data including environmental, geographic, infrastructure, demographic, and socioeconomic data from New York City (NYC), to examine their impact on flood risk. We applied XGBoost machine learning model combined with SHapley Additive exPlanations (SHAP) function to analyze and interpret the contributions of these factors to flood risks. We tested the model with a window of 1 to 7 days to determine optimum time scales to capture the essential information in the time series and factors’ dependencies over various time periods. Our findings reveal that although environmental and geographic factors have a strong correlation with flood risk, socioeconomic factors, such as median age, median house value, population density, and race also play an important role in such risks. Low-income household areas have higher flood risks, which happen to also be minority communities, making them more vulnerable to flooding than higher-income communities. Furthermore, population density and level of education may also have impact on flood risks. These insights can be used to facilitate planning and preparing future flood prevention and mitigation strategies.

关键词： Analytical models Temperature dependence Prevention and mitigation Education Urban areas Time series analysis Machine learning Floods Socioeconomics Population density

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