2023 International Conference on Computer Communication and Informatics (ICCCI)最新文献

{"title":"Cross Site Scripting (XSS) vulnerability detection using Machine Learning and Statistical Analysis","authors":"J. Harish Kumar, J. J Godwin Ponsam","doi":"10.1109/ICCCI56745.2023.10128470","DOIUrl":"https://doi.org/10.1109/ICCCI56745.2023.10128470","url":null,"abstract":"In our current technological development, usage of social networking, e-commerce, media, and management, web application plays a very indispensable role on the Internet. organizations use web applications to reach information to the public, e-commerce sites like Amazon and Flipkart use web applications to sell their products, and social networking sites like Facebook and Instagram use web applications. Many other services are provided on the web. Every mobile application will have its equivalent web application. Web Application Security plays a very vital role around the world. Cross Site Scripting (XSS) attacks are by far the most common and widely used method for stealing data from web applications. This paper discusses the XSS vulnerability detection using different deep learning and machine learning models. XSS attacks are a common type of web-based attack in which malicious code is injected into a website or web application, allowing attackers to steal sensitive information or perform other malicious actions. To ensure web-based systems’ security, XSS attack detection and prevention are essential. If the attacker successfully executes the XSS script, then the website will be compromised, and the attacker can steal sensitive data. The Open Web Application Security Project (OWASP) has listed XSS attacks as a top three risk to web applications. This research paper proposes a novel approach for detecting XSS attacks using different models. Deep learning algorithms such as Long Short Term Memory (LSTM), Convolution Neural Networks (CNN) and boosting algorithms such as AdaBoost and Gradient Boosting algorithms, and classification algorithms such as Logistic Regression (LR), Support Vector Machine (SVM), K-Nearest Neighbour (KNN), Random Forest (RF), Naive Bayes (NB), and Decision Tree (DT) algorithm for the detection of XSS attacks. To evaluate the effectiveness of our approach, we conducted experiments on a dataset of real-world XSS attacks and non-attack web requests. Our experiments showed that our machine-learning model was able to accurately identify XSS attacks with a high degree of accuracy, outperforming several baseline approaches. Overall, our research demonstrates the potential for using machine learning to detect XSS attacks effectively.","PeriodicalId":205683,"journal":{"name":"2023 International Conference on Computer Communication and Informatics (ICCCI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122746063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Machine Learning Approach For Predicting Crop Seasonal Yield and Cost For Smart Agriculture","authors":"M. Nandaraj, A. Roshan Raj, M. Uma Maheshwari, R. Sathiyaraj, K. Tejasvi","doi":"10.1109/ICCCI56745.2023.10128317","DOIUrl":"https://doi.org/10.1109/ICCCI56745.2023.10128317","url":null,"abstract":"In our economy, agriculture plays a key component. Current scenario has plunged the agricultural sector into extensive losses leading to a lot of food shortages and cases of farmer suicides. This can be solved through the implementation of advanced scientific methods like Machine learning, Deep Learning, and Internet of Things. The Proposed framework Smart Agriculture using Seasonal Yield and Cost Prediction (SYCP) uses Machine Learning to predict the ideal crop or set of crops to be grown based on a particular season. The Model also analyzes the current market trends and predicts the approximate price of the crop for that season and geographic region based on which the farmer can decide accordingly. Random forest has been found to be suitable for both crop and price prediction. The framework has been experimented with an agricultural dataset and the results were found to be more efficient than the existing methods. This would be an efficient solution, where it offers a seasonal yield along with price prediction to improve the economy of farmers and to push them to grow.","PeriodicalId":205683,"journal":{"name":"2023 International Conference on Computer Communication and Informatics (ICCCI)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122116720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reconfigurable Hardware Implementation of CNN Architecture using Zerobypass Multiplier","authors":"K. Sakthi, D. Abishek., M. Arun Kumar","doi":"10.1109/ICCCI56745.2023.10128256","DOIUrl":"https://doi.org/10.1109/ICCCI56745.2023.10128256","url":null,"abstract":"The current state-of-the-art in image recognition, segmentation, and localization algorithms has reached an extremely high level of accuracy thanks to the development of deep neural networks and their use in computer vision problems. Specifically, Convolutional Neural Networks (CNNs) have reached human-level performance in image classification and detection. CNN must be executed on a portable, low-cost, and low-power-consuming device for the object classification/detection use cases. However, real-time execution of CNN based applications is hindered by these devices’ limited computing resources and low on-board memory storage capability. In this dissertation, we introduce hardware-efficient algorithms for performing complex computations in CNN at low cost and with minimal power consumption. Additionally, we provide efficient VLSI architectures based on systolic arrays for creating high-performance devices for running CNN.The limitations of traditional CNN for detecting occluded objects are also outlined in this thesis. We propose an improved CNN with self-feedback layers and present an algorithm to increase the detection accuracy of the hidden objects. Improved accuracy in detecting hidden objects is found when the enhanced CNN is compared to the gold standard dataset. In addition, enhanced CNN requires a much larger number of computations to execute than regular CNN. We introduce a low-cost, low-power VLSI architecture design for efficient hardware execution of improved CNN.","PeriodicalId":205683,"journal":{"name":"2023 International Conference on Computer Communication and Informatics (ICCCI)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128404466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factors affecting gaming engines: Analytical Study","authors":"Mayank Tyagi, R. Agarwal, Amrita Rai","doi":"10.1109/ICCCI56745.2023.10128640","DOIUrl":"https://doi.org/10.1109/ICCCI56745.2023.10128640","url":null,"abstract":"The apparent evolution of machine learning in gaming is the application of machine learning techniques. One major use can be the creation of much more realistic, smarter and responsive characters in the games those which can learn new abilities from the various actions of the players and then use these actions to counter-perform the tactics and the strategies as well as also produce many unscripted responses when these actions are being observed by the in-game player actions. The methodology of analytics is providing a better understanding of the gaming industry data and how it is going to affect a lot of businesses in the future. Also, monetization models in gaming have been steadily shifting to lower outspoken pricing all the way down to free-to-play balanced with increased in-game purchases and microtransactions which give profit over time. still, this model of course requires both long-term player engagement and desirable in-game purchases. Machine learning can help in the design of these products and in deciding when and how to present them to the player.","PeriodicalId":205683,"journal":{"name":"2023 International Conference on Computer Communication and Informatics (ICCCI)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128250403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated Stock Price Prediction Using LSTM-ANN","authors":"P. Nagaraj, V. Muneeswaran, T. V. Dastagiri Reddy, B.Venu Gopal Reddy, T.Ganesh Reddy, P. Suresh","doi":"10.1109/ICCCI56745.2023.10128264","DOIUrl":"https://doi.org/10.1109/ICCCI56745.2023.10128264","url":null,"abstract":"It is well known that the stock market is erratic, dynamic, and nonlinear. Correct stock price forecasting is extraordinarily difficult due to more than one (Large and small) factor, such as politics, world economic circumstances, surprising actions, and business’s economic performance. But, there’s also this has the potential. There is a statistic toward discovering patterns. This gave an upward jab to the idea of Trading using pre-programmed, automated buying and selling methods known as algorithmic trading. In the generation of massive information, bottomless knowledge for expecting inventory market expenses and tendencies has become still more famous than before. We accumulated 10 years of records from Yahoo Finance and anticipate charge trends of inventory markets, a deep learning based model and comprehensive customization of characteristic engineering are presented. The planned answer stands complete as it consists of preparing the inventory for forecasting inventory market price trends, a market dataset, several function engineering methodologies, and a customized deep learning-based device combined. The model achieves a typically high-level of stock accuracy in market estimates. We also build a streamlet application for users to easily access that they can search a stock ticker and our model predicts the previous 100 days’ values and make a detailed overview of the 101st day.","PeriodicalId":205683,"journal":{"name":"2023 International Conference on Computer Communication and Informatics (ICCCI)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129014990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trustworthy Web Service-Business Activities (WSBA) using an Efficient Byzantine Fault Tolerance Algorithm","authors":"G. Muneeswari, Kanmani P, Vijay Kumar Burugari, Prabha Selvaraj","doi":"10.1109/ICCCI56745.2023.10128413","DOIUrl":"https://doi.org/10.1109/ICCCI56745.2023.10128413","url":null,"abstract":"In order to provide the services related to coordination, all the stipulated Business Activities (WS-BA) rely on the Byzantine Fault Tolerance (BFT) based lightweight mechanism for trustworthiness. The main objective of this paper is to provide security and less overhead to the initiator. The ultimate idea of the proposed work is to deploy a trustworthy third party services for the entire coupling and coordination services for the multiple business activities of an organization or enterprises. It can also be executed using the cloud services which will be much easy for large scale companies. In this paper we use BFT algorithm which handles lightweight ordering of sources and provides a standard way of communication between the client and the actual system coordinator. It also deals with Web Services-Business Activities-Initiator service which resolves some issues related with the security to the initiator, coordinator and participants. We also use timestamp or nonce to provide security to the coordinator and the initiator during the request and response between them.","PeriodicalId":205683,"journal":{"name":"2023 International Conference on Computer Communication and Informatics (ICCCI)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129359838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and Integration of dApp with blockchain smart contract Truffle Framework for user interactive applications","authors":"R. Dhanvardini, Pavletić-Peršić Martina, R. Vijay, Rengarajan Amirtharajan, Padmapriya Pravinkumar","doi":"10.1109/ICCCI56745.2023.10128406","DOIUrl":"https://doi.org/10.1109/ICCCI56745.2023.10128406","url":null,"abstract":"Websites and Web apps have become increasingly crucial over the past decade to daily life. Over the last ten years, websites have increased from three million to over 1.7 billion. Modern centralised digital marketplaces and enterprises provide consumers with an alternative method of selling and purchasing items conveniently. However, disadvantages among the marketplaces include the platform’s potential to arbitrarily block merchants, the fees associated with listing and selling products on the site, and the lack of user data privacy. In this, we propose and demonstrate a decentralised application that takes advantage of the Ethereum blockchain to address all these issues. The Truffle development framework was employed in the creation of the application. An Ethereum smart contract later migrated to the Ethereum network comprised the application’s features. The web3.js API (Application Program Interface) was used to send the user’s input to the Ethereum network after being received through a web interface. The users involved will be able to do transactions with the help of an interactive user interface. The interfacing is done using the Truffle framework, and the transactions are made through MetaMask, where ETH tokens are used. The dApp is created using JavaScript and React JS library. Thus, the integration of the blockchain and with front-end application by interfacing it with web 3.0 helps create a secured, immutable, trusted, and easy-to-use e-commerce website.","PeriodicalId":205683,"journal":{"name":"2023 International Conference on Computer Communication and Informatics (ICCCI)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129537765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Secure ReversibleImage Data Hiding (SRIDH) Using LSB Prediction Method","authors":"A. Kiran, C. Vimalarani, L. Ashwini, G. Gayithri, J. Supriya, T. Vinod","doi":"10.1109/ICCCI56745.2023.10128232","DOIUrl":"https://doi.org/10.1109/ICCCI56745.2023.10128232","url":null,"abstract":"Protecting sensitive data in public networks from prying eyes of unauthorised users has emerged as a critical concern in recent years. To safeguard the confidentiality of digital media, one of the most difficult methods to implement is data concealing. Techniques for the reversible concealment of data in digital photographs have been proposed by us. Textual information, such as that pertaining to weapon designs, map layouts, and satellite specifications, must be sent to and received by the majority of research and defence institutions. In order to complete this task, you will need a text file as well as an image file. In addition to the message, we will have a cover image file. After then, the number of pixels contained within the cover image will be taken into account. That is where each individual piece of the secret text will be embedded. This method will be repeated until the final snippet of the secret text is found. Following this procedure, the data will be masked by the image. After that, we will give this picture file to our client, who will be provided with a reverse process to use in order to extract the original text from the image. In the realm of cyber security, there are a plethora of innovative procedures and algorithms that can hide data. Each method has its own significance, and the least significant bit method is the one that was utilised for this method (LSB).","PeriodicalId":205683,"journal":{"name":"2023 International Conference on Computer Communication and Informatics (ICCCI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130143866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Implementation of Blockchain Technology in Combination with IPFS for Crime Evidence Management System","authors":"C. Shilpa, A. H. Shanthakumara","doi":"10.1109/ICCCI56745.2023.10128414","DOIUrl":"https://doi.org/10.1109/ICCCI56745.2023.10128414","url":null,"abstract":"Crime is an unlawful act and is punished by the authority, in order to prove crime, evidence is necessary. Evidence obtained from crime scene is crucial as it act as proof of crime, Digitalization of evidences is need of hour. During the entire process of investigation heterogenous format of data is generated and integrity of the sensitive data has to be maintained as sensitive data passes through the various levels of intermediaries forming Chain of Evidences (CoE). Evidence needs to be tramper proof and should be protected from any kind of alterations. In order to build strong system with immutability, integrity, and legitimacy features blockchain technology is more suitable. The digital evidence can be transferred in a transparent way between the parties involved without any central authority using blockchain technology. This paper focuses on how blockchain based solutions can help in building a strong secure system. The system is implemented using Ethereum platform to achieve integrity, immutability transparency as well as tampering can be identified by any one at any time.","PeriodicalId":205683,"journal":{"name":"2023 International Conference on Computer Communication and Informatics (ICCCI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130359752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hand Sign Classification Techniques Using Supervised And Unsupervised Learning Algorithms","authors":"J. L. V. S. Harshitha, N. Saranya, Yekkitilli Sruthi, S. Srithar, J. V. Chandra","doi":"10.1109/ICCCI56745.2023.10128426","DOIUrl":"https://doi.org/10.1109/ICCCI56745.2023.10128426","url":null,"abstract":"Gesture recognition is becoming a sore subject in computer vision captivating the idea of social interaction not only between humans but also create ergonomic systems that control devices ranging from time-of-flight cameras and controlling vehicles to virtual reality. Even though it is gaining ground recently, fast and robust recognition remains an unsolved problem. To our understanding, we are utilizing the Leap motion sensor captured near-infrared image dataset for gesture identification, which tides over word-level sign recognition encompassing a diverse set of hand gestures. We have suggested the approach of extracting the gesture from the image using PCA and image segmentation followed by the feature extraction stage. In this paper, we have analyzed and differentiated various methods of hand recognition counting Random forests, stochastic gradient descent, Naive Bayes, Decision tree, and Logistic regression algorithms and exploited our results","PeriodicalId":205683,"journal":{"name":"2023 International Conference on Computer Communication and Informatics (ICCCI)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130528993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}