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7th international Symposium on Cyber Security, Cryptology, and Machine Learning, CSCML 2023

7th International Symposium on Cyber Security, Cryptology, a...

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7th international Symposium on Cyber Security, Cryptology, and Machine Learning, CSCML 2023

ISBN: (纸本)9783031346705

the proceedings contain 36 papers. the special focus in this conference is on Cyber Security, Cryptology, and Machine Learning. the topics include: Using Machine Learning Models for Earthquake Magnitude Prediction in California, Japan, and Israel;a Bag of Tokens Neural Network to Predict Webpage Age;correlations Between (Nonlinear) Combiners of Input and Output of Random Functions and Permutations;PPAuth: A Privacy-Preserving Framework for Authentication of Digital Image;Robust Group Testing-Based Multiple-Access Protocol for Massive MIMO;the Use of Performance-Countersto Perform Side-Channel Attacks;HAMLET: A Transformer Based Approach for Money Laundering Detection;hollow-Pass: A Dual-View Pattern Password Against Shoulder-Surfing Attacks;Practical Improvements on BKZ Algorithm;pseudo-random Walk on Ideals: Practical Speed-Up in Relation Collection for Class Group Computation;enhancing Ransomware Classification with Multi-stage Feature Selection and Data Imbalance Correction;a Desynchronization-Based Countermeasure Against Side-Channel Analysis of Neural Networks;new Approach for Sine and Cosine in Secure Fixed-Point Arithmetic;How Hardened is Your Hardware? Guiding ChatGPT to Generate Secure Hardware Resistant to CWEs;evaluating the Robustness of Automotive Intrusion Detection systems Against Evasion Attacks;On Adaptively Secure Prefix Encryption Under LWE;SigML: Supervised Log Anomaly with Fully Homomorphic Encryption;HBSS: (Simple) Hash-Based Stateless Signatures – Hash All the Way to the Rescue!: (Preliminary Version);improving Performance in Space-Hard algorithms;A Survey of Security Challenges in Automatic Identification System (AIS) Protocol;Efficient Extended GCD and Class Groups from Secure Integer Arithmetic;A New Interpretation for the GHASH Authenticator of AES-GCM;Fast ORAM with Server-Aided Preprocessing and Pragmatic Privacy-Efficiency Trade-Off;Improving Physical Layer Security of Ground Stations Against GEO Satellite Spoofing Attacks;midgame Attac

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Detection of Pathological Markers in Colonoscopy Images using YOLOv7

Detection of Pathological Markers in Colonoscopy Images usin...

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international conference on ent computing and Control systems (ICICCS)

作者： Shruthy S Stancilas Rahul Krishnan Pathinarupothi Uma Gopalakrishnan Center for Wireless Networks and Applications (WNA) Amrita Vishwa Vidyapeetham Amritapuri India

Colonoscopy is a procedure for inspecting the colon of a patient. On colonoscopy images, anatomical landmarks, irritated and swollen tissue, ulcers, and polyps in the colorectal region can all be detected. these images are critical in identifying a variety of colorectal pathological disorders. the third leading cause of cancer-related death in both men and women is colorectal cancer. Many colorectal cancers can be avoided with routine screening. Polyp identification during colonoscopy may be prone to human error, such as missed polyps, which can lead to a missed diagnosis of colorectal cancer. In this study, we employ YOLOv7, enabling real-time and more accurate polyp detection that can be used in real-world colonoscopy. this will be useful for current physicians as well as training new clinicians. With an F1 score of 0.9304, the proposed model is capable of identifying polyps. Our approach outperforms existing methodologies by 7.5 percentage in terms of precision and 1.05 percentage in terms of F1 score.

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Using Opinionated-Objective Terms to Improve Lexicon-Based Sentiment Analysis 12th

Using Opinionated-Objective Terms to Improve Lexicon-Based S...

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12th international conference on Soft computing for Problem Solving, SocProS 2023

作者： Ogunleye, Bayode Brunsdon, Teresa Maswera, Tonderai Hirsch, Laurence Gaudoin, Jotham Department of Computing and Mathematics University of Brighton BrightonBN2 4GJ United Kingdom Department of Statistics University of Warwick CoventryCV4 7AL United Kingdom Department of Computing Sheffield Hallam University SheffieldS1 2NU United Kingdom

ISBN: (纸本)9789819732913

Sentiment analysis (SA) has received huge attention to understand customer perception, especially in the movie review (IMDB) domain. this is due to the availability of large, labelled dataset. this has enhanced the use and development of machine learning (ML) algorithms ranging from the traditional machine learning algorithms, deep learning algorithms to large language models. the ML models have shown great performances. However, the application of ML methods for SA is limited in service industry like banking, due to the unavailability of large training dataset. thus, we consider the use of lexicon-based sentiment analysis appropriate. We employ 346,000 Nigeria bank customers’ tweets to develop our corpus and thus, propose SentiLeye, a novel lexicon-based algorithm for sentiment analysis. Our algorithm incorporates corpus-based approach and external lexical resources for sentiment lexicon generation of Pidgin English language terms (a non-English under resourced language). Moreover, we demonstrate the use of verbs and adverbs that express opinion on service experience to improve the performance of lexicon-based sentiment analysis. Results show that SentiLeye outperforms popular off-the-shelf sentiment lexicons with macro F1-score of 76%. We conclude that results from domain specific algorithms such as SentiLeye evidence that general-purpose lexicons cannot replace them. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Sentiment analysis

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Study of Image Data Security with Cloud

Study of Image Data Security with Cloud

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international conference on Trends in Electronics and Informatics (ICEI)

作者： Pronika Chawla Harshita Parihar Ankit Mathur Department of Computer Science & Engineering Faculty of Engineering & Technology Manav Rachna International Institute of Research and Studies Faridabad India

the on-demand availableness of computer systems resources, especially storage of data (cloud storage) and rectifying power, with no direct ongoing administration by the user is what they call cloud computing. Large cloud functions are usually spread among several locations, each of which constitutes a data center. Customers may save money on capital expenses by using cloud computing, which frequently takes a “pay-as-you-go” approach. Coherence in cloud computing is achieved by sharing resources. In today's world of the Internet, demand for cloud services is increasing drastically leading to the production of new services day by day. As the services increase, the data gets primarily targeted by spiteful users who attempt to steal the data for their own atrocious and unethical activities. Users and trustworthy applications are considering more security and privacy and services get more in demand. Moreover, this study has reviewed several algorithms such as CPE-ABE (Ciphertext policy attribute-based encryption), ABE, KP-ABE (Key policy attribute-based encryption) CSP (Constraint satisfaction problem), PKG, AES (Advanced Encryption Standards), SHA-1 (Secure Hash Algorithm), Photo encryption, Photo decryption, PRE, IDEA (international Data Encryption algorithm) and LSBG (Least Significant Bit Grouping) for image data security. As already discussed, the increasing threats and frauds around the world, safe and secure applications and services should be created to resolve this problem so that people can store data on a platform that can be relied on. this research study has discussed about the concept of what are the paradigms required for securing and protecting the data and securing the image data at an encrypted level. this study has reviewed several existing research works, studied different algorithms which have been used in different research articles, and compared their strengths and drawbacks accordingly. Different research works have been summarized in a form of ta

关键词： Cloud computing Privacy Data centers Image resolution Production Market research Encryption

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Window Function Dependency on Male and Female Speech Signals for Pitch Extraction at Low SNRs 7th

Window Function Dependency on Male and Female Speech Signals...

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7th international conference on Soft computing: theories and Applications, SoCTA 2023

作者： Rahman, Md. Saifur Parvin, Nargis Rahman, Moinur Department of Information and Communication Technology Comilla University Cumilla Bangladesh Department of CSE Bangladesh Army International University of Science and Technology Cumilla Cumilla Cantonment Bangladesh

ISBN: (纸本)9789819720309

this research suggests an efficient idea that is better suited for speech processing applications for retrieving the accurate pitch from speech signals in noisy conditions. Almost every pitch detection method has windowing as a significant part of segmentation. this research considers using Hanning, Hamming, and rectangular windows’ function on male and female speech signals separately for pitch extraction. Also, analyze the windowing effect on the speech signal analytically to understand which window function is more suitable and effective for male and female speech signals specifically. For the validation of our idea, we have utilized the conventional autocorrelation function, cepstrum method and state-of-the-art method BaNa. this study puts out a potent idea that will work better for speech processing applications in noisy speech. From experimental results, the proposed idea represents which window function is more appropriate for male and female speech signals in noisy environments. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Extraction

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Qualitative Analysis on Implementation of Security Aspects for Web 3.0

Qualitative Analysis on Implementation of Security Aspects f...

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international conference on ent computing and Control systems (ICICCS)

作者： Siddhant Padave N.A. Natraj Giri. G Hallur Symbiosis Institute of Digital and Telecom Management Symbiosis International (Deemed University) Lavale Pune

Social Media Analytics and its real-time people sentiments play a pivotal role in shaping the use of emerging technologies. they will act as a critical use case with Web 3.0. Organizations have used this data to plan campaigns and design advertisements to entice their target audience & with web 3.0, social media platforms like Facebook, Instagram, and Twitter are integrated with evolving computing models, such as IoT. Consumers can thus expect additional interaction, integration, and seamless movement between physical spaces due to these platforms coming together in Web 3.0. However, ensuring data privacy across such systems could be challenging. this is where the emergence of blockchain technology could potentially improve and help evolve the online landscape. thus, the research aims to narrow down methods to enhance security protocols in web 3.0 by leveraging available technology. this article employs a bibliographical study based on an extensive literature study. the analysis has found numerous web 3.0 use cases and parallel security loopholes, thus offering scope for research. this article will have large-scale implications for achieving control over data leading to digital privacy.

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Techniques of Image Processing and Segmentation in Predicting Hydrocephalus using Magnetic Resonance Image

Techniques of Image Processing and Segmentation in Predictin...

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international conference on Advanced computing and Communication systems (ICACCS)

作者： S.V. Rajiga M. Gunasekaran Government Arts College (Autonomous) Salem -7. Government Arts College Dharmapuri

Children are most commonly affected by many neurological disorders now a days. One of the common disease is hydrocephalus occurring 1/1000 in infantile age group and also in adults as a result of congenital, acquired, tumors, spina bifida, bleeding or infection. Hydrocephalus may cause disability and even death when it is left untreated. Hydrocephalus occurs when, due to previous causes in the brain, excessive cerebrospinal fluid builds up in the brain. When diagnosing tumours and hydrocephalus, image processing plays a vital role. the gap between the visual representation of data captured by MRI and the information relevant to the individual is a major challenge in the medical field. the latest image processing and data mining technologies are used to classify images with high precision. this research paper suggest a definition of image processing and segmentation algorithms for the evaluation of hydrocephalus in children and the determination of its MRI volume. Earlier research work are intended for identifying Hydrocephalus from CT brain images. But in the proposed work MRI images are used for diagnosis. this paper presents techniques and algorithms of Image processing and Segmentation which will be very useful in diagnosing Hydrocephalus.

关键词： Neurological diseases Image segmentation Brain Visualization Pediatrics Magnetic resonance imaging Magnetic resonance

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Approaches for Advanced Spectrum Sensing in Cognitive Radio Networks

Approaches for Advanced Spectrum Sensing in Cognitive Radio ...

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international conference on ent computing and Control systems (ICICCS)

作者： Abhay Chaturvedi Kdv Prasad Sudhanshu Kumar Jha Ved Srinivas N Anil Kumar V Dankan Gowda Department of Electronics and Communication Engineering GLA University Mathura Uttar Pradesh India Symbiosis Institute of Business Management (SIBM) Symbiosis International (Deemed University) (SIU)Off Bangalore Highway Kothur Mandal Village Mahabubnagar Hyderabad Telangana India Department of Electronics and Communication University of Allahabad Prayagraj Uttar Pradesh India Public Policy Thiagarajar School of Management Madurai Tamilnadu India Department of Electronics and Instrumentation Engneering Mohan Babu University (Erst while Sree Vidyanikethan Engineering College) A.rangampet Andhra Pradesh India Department of Electronics and Communication Engineering BMS Institute of Technology and Management Bangalore Karnataka India

Intelligent learning and adaptation allow cognitive radios (CRs) to maximise available spectrum while maintaining stable connections. Cognitive radio technology may detect unused channels of radio frequency space via a process called “spectrum sensing," and then get rapid and easy access to such channels. An important aspect of CR technology is spectrum sensing, which allows CRs to detect gaps in the spectrum. It’s the practise of keeping tabs on a certain radio spectrum band on a regular and changing basis to see if there are any interference issues that might prevent its utilisation. Noise power and signal fading in a wireless channel have a significant impact on the efficiency of spectrum sensing techniques in noisy situations. Another difficulty for sensing algorithms involving a single secondary user is the dilemma of a hidden main user in shadowed areas. algorithms for cooperative spectrum sensing must take into account a number of aspects, including sensing time, speed, cooperation overheads, and decision fusion methods. In order to provide efficient and adaptable IoT networking, many wireless technologies have emerged in recent years. One of the primary technologies that provides opportunistic connection to a wide variety of interconnected IoT devices is cognitive radio (CR), which makes software-defined radio possible. An unmanaged and unregulated invasion of privacy through low-powered wireless sensors into the Internet of things (IoT). the output of such networks is dependent on the main consumer’s observed spectrum pattern because of the networks’ opportunistic nature.

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Maximum Power Point Tracking for Hybrid Wind and Solar Power Generation System Utilizing Particle Swarm Optimization Technique: A Mathematical Approach 7th

Maximum Power Point Tracking for Hybrid Wind and Solar Power...

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7th international conference on Intelligent computing and Optimization, ICO 2023

作者： Dinku, Tigilu Mitiku Manshahia, Mukhdeep Singh Yadav, Ramsagar Chaudhary, Mahendra Pal Department of Mathematics Bule Hora University Bule Hora Ethiopia Department of Mathematics Punjabi University Patiala Punjab Patiala India International Scientific Research and Welfare Organization New Delhi India

ISBN: (纸本)9783031733239

this research paper presents a mathematical framework for optimizing the maximum power point tracking (MPPT) in a hybrid wind and solar power generation system using the particle swarm optimization (PSO) technique. the inherent variability of renewable energy sources (RES), including wind and solar, over time has necessitated the development of hybrid renewable energy systems (HRES). To maximize the energy output from the hybrid system, an MPPT control algorithm is essential for accurately tracking the maximum power based on the fluctuations in wind speeds and solar irradiation. Several methods have been proposed for MPPT control, and this paper focuses on employing the PSO algorithm to achieve efficient power tracking. the proposed system architecture encompasses mathematical models of the wind turbine, photovoltaic (PV) system, and interfacing power electronic components. through simulation results, the effectiveness of the PSO-based MPPT controller is demonstrated. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Particle swarm optimization (PSO)

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Evaluating the Performance of a Biclustering Algorithm Applied to Collaborative Filtering - A Comparative Analysis

Evaluating the Performance of a Biclustering Algorithm Appli...

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international conference on Hybrid Intelligent systems (HIS)

作者： Pablo A. D. de Castro Fabricio O. de Franca Hamilton M. Ferreira Fernando J. Von Zuben Laboratory of Bioinformatics and Bio-Inspired Computing-LBIC School of Electrical and Computer Engineering-FEEC State University of Campinas-UNICAMP Sao Paulo Brazil

Collaborative filtering (CF) is a method to perform automated suggestions for a user based on the opinion of other users with similar interest. Most of the CF algorithms do not take into account the existent duality between users and items, considering only the similarities between users or only the similarities between items. the authors have proposed in a previous work a bio-inspired methodology for CF, namely BIC-aiNet, capable of clustering rows and columns of a data matrix simultaneously. the usefulness and performance of the methodology are reported in the literature. Now, the authors carry out more rigorous comparative experiments with BIC-aiNet and other techniques found in the literature, as well as evaluate the scalability of the algorithm in several datasets of different sizes. the results indicate that our proposal is able to provide useful recommendations for the users, outperforming other methodologies for CF.

关键词： Filtering algorithms Performance analysis Algorithm design and analysis Clustering algorithms Information filtering Information filters international collaboration Scalability Hybrid intelligent systems Laboratories

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