2021 3rd International Conference on Advancements in Computing (ICAC)最新文献_第2页

A Sensitive Data Leakage Detection and Privacy Policy Analyzing Application for Android Systems (PriVot) Android系统敏感数据泄露检测及隐私策略分析应用(PriVot)

2021 3rd International Conference on Advancements in Computing (ICAC) Pub Date : 2021-12-09 DOI: 10.1109/ICAC54203.2021.9671075

H. Atapattu, W. Fernando, J. P. A. K. Somasiri, P. M. K. Lokuge, A. Senarathne, Muditha Tissera

{"title":"A Sensitive Data Leakage Detection and Privacy Policy Analyzing Application for Android Systems (PriVot)","authors":"H. Atapattu, W. Fernando, J. P. A. K. Somasiri, P. M. K. Lokuge, A. Senarathne, Muditha Tissera","doi":"10.1109/ICAC54203.2021.9671075","DOIUrl":"https://doi.org/10.1109/ICAC54203.2021.9671075","url":null,"abstract":"Mobile applications can have access to various sensitive information to accomplish the business requirements as well as user requirements. Due to the sensitivity of this information, app developers are bound by the regulations to provide a privacy policy that describes their data collection practices. However, there were many incidents where the privacy policies were inconsistent with the actual data practices. Additionally, the privacy policies are often too long and difficult to grasp just by reading them due to their complex language. To address this hurdle, we propose a mobile application “PriVot”. PriVot has a privacy policy analyzer built with a hierarchical classifier using convolutional neural networks to provide a detailed and unambiguous summary indicating the data that is being collected by each app and their purpose for being collected Furthermore, it monitors the network traffic of the device with the aid of a Transport Layer Security(TLS) proxy, a Forwarder, and a Traffic Analyzer that operates on-device without requiring root privileges to identify potential data leakages and privacy policy violations. We present “PriVot” which achieved a 67.4% accuracy on privacy policy analysis and a 72.5% throughput at a low latency overhead with the network traffic monitoring.","PeriodicalId":227059,"journal":{"name":"2021 3rd International Conference on Advancements in Computing (ICAC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128378383","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}

引用次数: 1

AI Based Monitoring System for Social Engineering 基于人工智能的社会工程监控系统

2021 3rd International Conference on Advancements in Computing (ICAC) Pub Date : 2021-12-09 DOI: 10.1109/ICAC54203.2021.9671218

K. Yapa, S. Udara, U. P. B. Wijayawardane, K. N. P. Kularatne, N. M. P. P. Navaratne, W. G. V. U. Dharmaphriya

{"title":"AI Based Monitoring System for Social Engineering","authors":"K. Yapa, S. Udara, U. P. B. Wijayawardane, K. N. P. Kularatne, N. M. P. P. Navaratne, W. G. V. U. Dharmaphriya","doi":"10.1109/ICAC54203.2021.9671218","DOIUrl":"https://doi.org/10.1109/ICAC54203.2021.9671218","url":null,"abstract":"Social media is one of the most predominantly used online platforms by individuals across the world. However, very few of these social media users are educated about the adverse effects of obliviously using social media. Therefore, this research project, is to develop an advisory system for the benefit of the general public who are victimized by the adverse impacts of their ignorant and oblivious behavior on social media. The system was implemented using a decision tree model with the use of customized datasets; and for the proceeding operational implementations, Python programming language, Pandas, Natural Language Processing and TensorFlow were used. This advisory system can monitor user behaviors and generate customized awareness reports for the users based on category and level of their behaviors on social media. Furthermore, the system is also capable of generating graph reports of the use behavior fluctuations for the reference of the user. With the help of these customized awareness reports and the graph reports, the users can identify their potential vulnerabilities and improve their social media habits.","PeriodicalId":227059,"journal":{"name":"2021 3rd International Conference on Advancements in Computing (ICAC)","volume":"473 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129253082","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}

引用次数: 1

Standalone Application and Chromium Browser Extension-based System for Online Examination Cheating Detection 基于独立应用和chrome浏览器扩展的在线考试作弊检测系统

2021 3rd International Conference on Advancements in Computing (ICAC) Pub Date : 2021-12-09 DOI: 10.1109/ICAC54203.2021.9671103

Samadhi Kariyawasam, A. Lakshan, Anuranaga Liyanage, Kaveesha Gimhana, Vijani S. Piyawardana, Y. Mallawarachchi

{"title":"Standalone Application and Chromium Browser Extension-based System for Online Examination Cheating Detection","authors":"Samadhi Kariyawasam, A. Lakshan, Anuranaga Liyanage, Kaveesha Gimhana, Vijani S. Piyawardana, Y. Mallawarachchi","doi":"10.1109/ICAC54203.2021.9671103","DOIUrl":"https://doi.org/10.1109/ICAC54203.2021.9671103","url":null,"abstract":"Educational organizations and institutes that provide services to the public use e-learning frequently than before. The incapacity to evaluate the knowledge acquired is a flaw in education. Due to the current situation, traditional evaluation and examinations are not possible. In a developing country like Sri Lanka, the conduct of online examinations has not been efficient, resulting in cheating at examinations due to vulnerabilities resulting from organizational policies and the difficulty to track down candidates who are prone to cheating, therefore use of facial features for candidate verification and to monitor the background interactions the use of audio and video is taken into consideration with the aid of two cameras; the system mounted camera and a wearable camera containing a microphone allowing audio detection. In this research, we suggest using the training data set generated from individuals to undertake a training approach to improve the robustness for background interactions through audio and video to detect the level of cheating of candidates.","PeriodicalId":227059,"journal":{"name":"2021 3rd International Conference on Advancements in Computing (ICAC)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116258739","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}

引用次数: 1

Non-Communicable Diseases Detection System 非传染性疾病检测系统

2021 3rd International Conference on Advancements in Computing (ICAC) Pub Date : 2021-12-09 DOI: 10.1109/ICAC54203.2021.9671162

H. Thudawehewa, U.C.B. Pathmakulasooriya, W.P.S. Jayawardhana, C. G. Wellehewa, Chamari Silva, Pasangi Rathnayake

{"title":"Non-Communicable Diseases Detection System","authors":"H. Thudawehewa, U.C.B. Pathmakulasooriya, W.P.S. Jayawardhana, C. G. Wellehewa, Chamari Silva, Pasangi Rathnayake","doi":"10.1109/ICAC54203.2021.9671162","DOIUrl":"https://doi.org/10.1109/ICAC54203.2021.9671162","url":null,"abstract":"This research paper presents a Non-communicable Diseases Detection System which is a centralized medical system designed for general public usage. The system aims to provide help for people with non-communicable diseases. In a pandemic situation like this where people find it difficult to reach medical facilities and staff, the system is more advantageous. The system covers areas related to the medical report analysis, BMI value prediction, and breast cancer analysis related to non-communicable diseases. Presently health reports are taken for every disease. BMI is a factor essential to everyone to lead a healthy life. The majority of women suffer from breast cancer. As per the findings of the report, the report analysis predicts possible diseases that can occur in the person concerned. In BMI prediction, particularly the possible BMI value and weight value for the next month is predicted. In Mammogram detection, it gives the current status of the breast. The report analysis model has 90.6% accuracy while the BMI prediction model has 99.7% accuracy. The mammogram detection model proved that it has 96.5% accuracy. All the aforesaid procedures were carried out by analyzing related data systematically. Machine learning, Deep learning, and Image processing techniques were used to develop this system. The main purpose of this system is to make the persons aware of their current health status and to prevent them from having non-communicable diseases.","PeriodicalId":227059,"journal":{"name":"2021 3rd International Conference on Advancements in Computing (ICAC)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121043371","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}

引用次数: 0

ASD Screening for Toddlers via Physical Interpretation through Advanced AI 通过先进的人工智能进行肢体翻译的幼儿自闭症筛查

2021 3rd International Conference on Advancements in Computing (ICAC) Pub Date : 2021-12-09 DOI: 10.1109/ICAC54203.2021.9671177

Dinushe Jayasekera, Hasini Alwis, H.M.N.S. Dissanayaka, Rashmika Mudalinayake, Vijani S. Piyawardana, K. Pulasinghe

{"title":"ASD Screening for Toddlers via Physical Interpretation through Advanced AI","authors":"Dinushe Jayasekera, Hasini Alwis, H.M.N.S. Dissanayaka, Rashmika Mudalinayake, Vijani S. Piyawardana, K. Pulasinghe","doi":"10.1109/ICAC54203.2021.9671177","DOIUrl":"https://doi.org/10.1109/ICAC54203.2021.9671177","url":null,"abstract":"Autism Spectrum Disorders (ASD) are generally causing challenges for significant communication, social interaction, and behavioral patterns to elderly people and children. Providing early treatments can make a huge advancement in the lives of children. Meanwhile, there is a limited number of systems to screen and identify ASD children. This research project is about developing a set of tools bonding together to one system called \"AI - Bot Simon\" to screen kids with ASD by filling the gap. In the system development process mainly, Audio, Facial expressions, Gestures, and the Gates of a targeted group of children are considered for screening. Since the target group is 6 months to 4 years, they are in early language development age. On the technical side of view Machine Learning (ML) and Deep Learning (DL) with Neural Networks (NN) are used for advanced screening and monitoring for automation of the process. In the last step of the development, all the outputs or information gathered from each tool or model, processed, analyzed, and provided to the users of the system by an Artificial Intelligence (AI) bot implemented with a web application and a mobile application whether children are suffering from ASD or not.","PeriodicalId":227059,"journal":{"name":"2021 3rd International Conference on Advancements in Computing (ICAC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132801609","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}

引用次数: 0

Smart Monitoring and Disease Detection for Robotic Harvesting of Tomatoes 番茄机器人收获的智能监测和病害检测

2021 3rd International Conference on Advancements in Computing (ICAC) Pub Date : 2021-12-09 DOI: 10.1109/ICAC54203.2021.9670888

Imesh Pasindu, Sumeera Viraj, Ravindu Dilshan, Akshith Kalhara, Oshada Senaweera, R. de Silva, C. Jayawardena

引用次数: 0

Cricket Shot Image Classification Using Random Forest 基于随机森林的板球镜头图像分类

2021 3rd International Conference on Advancements in Computing (ICAC) Pub Date : 2021-12-09 DOI: 10.1109/ICAC54203.2021.9671109

Mithelan Devanandan, Vithurson Rasaratnam, Manoj Karthik Anbalagan, Narthanan Asokan, R. Panchendrarajan, Janani Tharmaseelan

{"title":"Cricket Shot Image Classification Using Random Forest","authors":"Mithelan Devanandan, Vithurson Rasaratnam, Manoj Karthik Anbalagan, Narthanan Asokan, R. Panchendrarajan, Janani Tharmaseelan","doi":"10.1109/ICAC54203.2021.9671109","DOIUrl":"https://doi.org/10.1109/ICAC54203.2021.9671109","url":null,"abstract":"Cricket is one of the top 10 most played sport across the world regardless of age and gender. However, learning cricket has been quite challenging as the majority of the cricket-playing individuals are unable to afford quality infrastructure. While this has opened up many research opportunities to provide solutions to automatically learn cricket, very little work has been done in this era. In this paper, we focus on the batting skills of cricket players. We develop a Random Forest model to classify the cricket shot images using human body keypoints extracted with MediaPipe. Experiment results show the proposed model achieves an F1-score of 87% and outperforms the existing solution in a 5% margin. Further, we propose a similarity estimation approach to compare the user’s cricket image with popular international cricket players’ cricket shot images of the same type and retrieve the most similar one. The mobile application we developed based on our solution will enable cricket-playing individuals to analyze, improve and track their batting performances without the need of having a coach.","PeriodicalId":227059,"journal":{"name":"2021 3rd International Conference on Advancements in Computing (ICAC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133375407","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}

引用次数: 6

Price Optimisation and Management 价格优化与管理

2021 3rd International Conference on Advancements in Computing (ICAC) Pub Date : 2021-12-09 DOI: 10.1109/ICAC54203.2021.9671224

M.T.M Shafkhan, P.R.S.S Jayasundara, K. Kariyapperuma, H.P.S Lakruwan, L. Rupasinghe

{"title":"Price Optimisation and Management","authors":"M.T.M Shafkhan, P.R.S.S Jayasundara, K. Kariyapperuma, H.P.S Lakruwan, L. Rupasinghe","doi":"10.1109/ICAC54203.2021.9671224","DOIUrl":"https://doi.org/10.1109/ICAC54203.2021.9671224","url":null,"abstract":"One of the most crucial decisions a company makes is its pricing strategy. When it comes to pricing, a company must consider the present, as well as the future and the past pricing. It enables a company to make sound judgments. In the process of marketing products, price is the only factor that creates income; everything else is a cost. Guessing at product pricing is a little like throwing darts blindfolded; some will hit something, but it probably will not be the dartboard. Large-scale enterprises throughout the world still depend on Excel sheets with numerous manpower or expensive pricing solutions. Expensive pricing systems are difficult to implement for Medium and Large Sized Enterprises in countries like Sri Lanka. Our goal in this research is to propose an affordable, efficient, easy-to-use and secure solution which can be implemented in Medium and Large Sized Enterprises in Sri Lanka. Manufacturing cost, shipping cost, competitor analysis, customer behaviour are taken as the root factors when deciding the price. The proposed solution includes Machine Learning components which is fed with historical data of these four factors to predict the manufacturing cost, shipping cost, competitor price and customer behavioural factors on a given date and as well as an optimisation component which enables the opportunities to minimise the cost and maximise the profit. The four Machine Learning components are implemented using LSTM, ARIMA, Facebook Prophet and a clustering model. The optimisation model is implemented using linear programming optimise these four components. A user-friendly web application is implemented using MEAN stack with micro service architecture to access this.","PeriodicalId":227059,"journal":{"name":"2021 3rd International Conference on Advancements in Computing (ICAC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124819759","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}

引用次数: 0

Use of Natural Language Processing and Deep Learning towards Guiding Healthy Cholesterol Free Life

2021 3rd International Conference on Advancements in Computing (ICAC) Pub Date : 2021-12-09 DOI: 10.1109/ICAC54203.2021.9671230

Dilith Sasanka, H. Malshani, U.I Wickramaratne, Yashmitha Kavindi, Muditha Tissera, Buddhima Attanayaka

引用次数: 0

Automated Crop Harvesting, Growth Monitoring and Disease Detection System for Vertical Farming Greenhouse 垂直温室作物自动收获、生长监测和病害检测系统

2021 3rd International Conference on Advancements in Computing (ICAC) Pub Date : 2021-12-09 DOI: 10.1109/ICAC54203.2021.9671074

Charith Jayasekara, Sajani Banneka, Gihan Pasindu, Yukthi Udawaththa, Sasini Wellalage, Pradeep K.W. Abeygunawardhane

引用次数: 2