Syed Anas Ansar, Archita Singh, Shruti Aggrawal, A. Yadav, Prabhash Chandra Pathak, R. Khan
{"title":"Modernizing CPS with Blockchain: Applications, Challenges & Future Directions","authors":"Syed Anas Ansar, Archita Singh, Shruti Aggrawal, A. Yadav, Prabhash Chandra Pathak, R. Khan","doi":"10.1109/ICPS55917.2022.00031","DOIUrl":"https://doi.org/10.1109/ICPS55917.2022.00031","url":null,"abstract":"The necessity for ameliorating management and secure process is imperiously required in this tech-driven world with the digitized working environment. The increased usage of the internet and the burgeoning connectivity through IoT have provided a significant opportunity for Cyber-Physical Systems (CPS) to preponderate. These are advanced computerized devices that function together to perform specific tasks, respond to human stimuli, and control the physical segments. While this technology is already used in automatic pilot avionics, robotics systems, medical monitoring, industrial control systems, etc. yet the advancement of these systems must comprehend incontrovertible focus on making them efficient and secure. To improve the resilience, dependability, and security of these systems, researchers can incorporate Blockchain technology which has an inbuilt blend of consensual algorithms, secure protocols, and distributed data storage, with the CPS. Moreover, with the advancement of IoT in the upgraded version of CPS, such as autonomous driving, there’s a major need to manage big data with low latency and high accuracy. Therefore, deep learning can be applied for systematic analysis of big data, which supports vivid analytic ability. While these emerging technologies set some security standards and enable users to authenticate their digital information, these technologies have the potential to significantly influence the current trend in the field of CyberPhysical Systems. This article focuses on a comprehensive analysis of Blockchain applications synthesized with CPS. Furthermore, this article briefly presented the BCPS (Blockchain-enabled CPS) framework for addressing issues in the Industry 4.0 manufacturing system while adopting Blockchain (BC) in CPS.","PeriodicalId":263404,"journal":{"name":"2022 Second International Conference on Interdisciplinary Cyber Physical Systems (ICPS)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132019559","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":"Transmission Modeling and Attack Simulation of Bluetooth Low Energy","authors":"Midhun Raj, K. Achuthan","doi":"10.1109/ICPS55917.2022.00025","DOIUrl":"https://doi.org/10.1109/ICPS55917.2022.00025","url":null,"abstract":"Bluetooth low energy Attacks are common because of the widespread use of BLE devices in low power networks. Simulators and emulators are the traditional methods for testing and finding vulnerabilities in real-world technologies. The existing BLE Emulators are working based on packet transmission and performs BLE controller level attacks rather than the physical properties of the signal. This work helps simulate jamming attacks by using the BLE library that has been made as part of this work using the OpenModelica tool. A mathematical model is created using OpenModelica for testing BLE attacks. The BLE library can be used to simulate jamming and interference-related attacks by using the electromagnetic(EM) property of the wave. The effect of attack on transmission can be seen as graphical plots of power and EM fields based on the attack type..","PeriodicalId":263404,"journal":{"name":"2022 Second International Conference on Interdisciplinary Cyber Physical Systems (ICPS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123292047","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 Ensemble-based Machine Learning Model for Accurate Predictions using Multiple Categorical Datasets","authors":"Rajni Bhalla, Amit Sharma, Amandeep, J. Gupta","doi":"10.1109/ICPS55917.2022.00008","DOIUrl":"https://doi.org/10.1109/ICPS55917.2022.00008","url":null,"abstract":"In the consumer sector, electronic reviews are more common and comprehensive. Manufacturers, retailers, and customers are all aware of it. All require this knowledge to benefit from considering and guiding the massive and energetic data spaces that follow. Many social media outlets give polarized feedback. A fundamental problem with the internet's destructive content is that it makes it impossible for people to read important information. We'll look at all of the traditional machine learning approaches to catch the true sentiment. The accuracy using decision tree, naïve bayes and KNN applied on nursery dataset. All these three techniques achieved precisons of 72 to 90%. Decision tree performed well and accurate result as compared to knn and naïve bayes.The decision tree faced overfitting issues and KNN faced issues in deciding the value of K. On a large dataset, complexity increase when we apply a decision tree. Zero probability issues are a major challenge in naïve Bayes. To solve all those issues, an ensemble machine learning model (NKD) for accurate predictions is proposed to check the performance of the model. The proposed methodology applied on nursery dataset and IRIS dataset. The accuracy achieved using iris dataset is 100%.","PeriodicalId":263404,"journal":{"name":"2022 Second International Conference on Interdisciplinary Cyber Physical Systems (ICPS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116304262","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 Residual Network Model (ResNet152) for Bronchitis Detection using X-ray Images","authors":"S. Kaur, T. Adilakshmi, T. Jalaja","doi":"10.1109/ICPS55917.2022.00012","DOIUrl":"https://doi.org/10.1109/ICPS55917.2022.00012","url":null,"abstract":"Every year 5 Lakhs of people affects from bronchitis and it rate crores of rupees to the public treasury for the industry of health care. It also affects cancer causing agents like diseases which can also lead to death of a human being. Thus diagnosing at the early stage becomes successful detection, prevention and survival of that diseased patient. The work at present where doctors predict by observing the symptoms or observing the x rays of the patients then the doctor used to percept about the disease. The purpose of the model is to build a model used to classify whether the patient is suffering from bronchitis or normal lung by x-ray images. A pre-trained Residual network model (ResNet152) is used for predicting early bronchitis and classifying the images by labeling them.","PeriodicalId":263404,"journal":{"name":"2022 Second International Conference on Interdisciplinary Cyber Physical Systems (ICPS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116490605","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}
Syed Anas Ansar, K. Jaiswal, S. Aggarwal, S. Shukla, Jaya Yadav, Nupur Soni
{"title":"Smart Home Personal Assistants: Fueled by Natural Language Processor and Blockchain Technology","authors":"Syed Anas Ansar, K. Jaiswal, S. Aggarwal, S. Shukla, Jaya Yadav, Nupur Soni","doi":"10.1109/ICPS55917.2022.00029","DOIUrl":"https://doi.org/10.1109/ICPS55917.2022.00029","url":null,"abstract":"With the ever-increasing cost of livelihood, technological intervention is necessary to keep costs under control. Hence, smart home technology can be considered as a well-established and entrenched region of interest. In the current scenario, research subsidizes present-time houses, enabling the user to design and manage a smart home to conserve energy while allowing for more autonomous applications. A voice-activated home automation system integrates the Internet of Things, Artificial Intelligence, Blockchain, and Natural Language Processing to deliver a cost-effective and efficient method of interacting with household equipment. The primary objective of this paper is to assess SPAs using blockchain technology and a natural language processor (NLP), as well as the design of a SPA based on the internet of things. Applicable cyber threats and countermeasures are also addressed in this article. Using Yule's coefficient of association, a case study was undertaken to evaluate the association between privacy and security threats posed by this modern technology. The findings show that privacy and security are positively related.","PeriodicalId":263404,"journal":{"name":"2022 Second International Conference on Interdisciplinary Cyber Physical Systems (ICPS)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130268409","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}
K. R, Amala Rosy Mishma J, Charulatha J, Roshini N B
{"title":"LiveFit : A Smart Fitness App","authors":"K. R, Amala Rosy Mishma J, Charulatha J, Roshini N B","doi":"10.1109/ICPS55917.2022.00038","DOIUrl":"https://doi.org/10.1109/ICPS55917.2022.00038","url":null,"abstract":"\"More than 50 million people are facing health problems due to lack in care of food intake and diet plan\", according to the reports recorded by World Health Care in 2019. Improper diet leads to chronic diseases such as Obesity, Cancer, Diabetes, Cardiovascular disease, etc. With the evolution of Mobile Technology, it is possible to develop mobile applications which helps in monitoring the intake of foods as well as in monitoring the physical activities. The main aim of this application is to promote a healthy lifestyle by creating awareness to the users about their physical fitness. The application facilitates the users to achieve their weight goals and maintain fitness. In order to assist this, the application provides many features. Some of the major features of this application are Daily Calorie tracking, Body Mass Index (BMI) calculation, Steps Counting, Chat with Advisor. This application provides a User-friendly Interface where users can keep track of their daily food intake and maintain a healthy diet.","PeriodicalId":263404,"journal":{"name":"2022 Second International Conference on Interdisciplinary Cyber Physical Systems (ICPS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124199189","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":"Performance Analysis of DDoS Mitigation in Heterogeneous Environments","authors":"A. Verma, R. Saha","doi":"10.1109/ICPS55917.2022.00047","DOIUrl":"https://doi.org/10.1109/ICPS55917.2022.00047","url":null,"abstract":"Computer and Vehicular networks, both are prone to multiple information security breaches because of many reasons like lack of standard protocols for secure communication and authentication. Distributed Denial of Service (DDoS) is a threat that disrupts the communication in networks. Detection and prevention of DDoS attacks with accuracy is a necessity to make networks safe.In this paper, we have experimented two machine learning-based techniques one each for attack detection and attack prevention. These detection & prevention techniques are implemented in different environments including vehicular network environments and computer network environments. Three different datasets connected to heterogeneous environments are adopted for experimentation. The first dataset is the NSL-KDD dataset based on the traffic of the computer network. The second dataset is based on a simulation-based vehicular environment, and the third CIC-DDoS 2019 dataset is a computer network-based dataset. These datasets contain different number of attributes and instances of network traffic. For the purpose of attack detection AdaBoostM1 classification algorithm is used in WEKA and for attack prevention Logit Model is used in STATA. Results show that an accuracy of more than 99.9% is obtained from the simulation-based vehicular dataset. This is the highest accuracy rate among the three datasets and it is obtained within a very short period of time i.e., 0.5 seconds. In the same way, we use a Logit regression-based model to classify packets. This model shows an accuracy of 100%.","PeriodicalId":263404,"journal":{"name":"2022 Second International Conference on Interdisciplinary Cyber Physical Systems (ICPS)","volume":"97 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113989726","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 Technique to Detect Music Emotions Based on Machine Learning Classifiers","authors":"Devi Unni, Aminta Melta D’Cunha, Deepa G","doi":"10.1109/ICPS55917.2022.00033","DOIUrl":"https://doi.org/10.1109/ICPS55917.2022.00033","url":null,"abstract":"Music has the power to evoke emotional responses and is a vital component of human life. Emotion Recognition of Music is useful for music comprehension, retrieval, and other music-related tasks. It is also important to be able to detect a person's emotional state through their voice. In this research, we suggested a technique for recognising song emotion that might also be used to recognise speech emotion. Various musical features are retrieved and throughout the process, data is fed into machine learning classification algorithms: Random Forest, SVM, Decision Tree, and Naive Bayes. When compared to other algorithms, the audio is analysed for emotional content and identifies six emotions (angry, calm, fearful, happy, neutral, and sad), with Random Forest having the best accuracy and performance. By increasing the number of features extracted and reducing noise, this method can be utilised to detect speech emotion in the future.","PeriodicalId":263404,"journal":{"name":"2022 Second International Conference on Interdisciplinary Cyber Physical Systems (ICPS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134273655","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}
K. K., Meghana B, S. K., Jyothi Priyanka D, D. Sree Lakshmi
{"title":"Credit Card Fraud Identification Using Logistic Regression and Local Outlier Factor","authors":"K. K., Meghana B, S. K., Jyothi Priyanka D, D. Sree Lakshmi","doi":"10.1109/icps55917.2022.00026","DOIUrl":"https://doi.org/10.1109/icps55917.2022.00026","url":null,"abstract":"Credit cards are a crucial financial tool that enables its users to make purchases and pay at a later date. Issued by financial customs, credit cards give users a pre-agreed credit limit that they can use for their purchases. MasterCard extortion is a type of data fraud where crooks make buys utilising a Visa account which doesn't have a place with them. The two primary tactics for reducing frauds and losses caused by fraudulent conduct are fraud detection systems and fraud prevention. Fraud detection is tracking the behaviours of large groups of people in order to estimate, perceive, or identify obnoxious activity, such as fraud, intrusion, or defaulting. The Local Outlier Factor is a technique for detecting aberrant data points by comparing a data point's local variability to that of its neighbours. Under the Supervised Learning approach, one of the most prominent Machine Learning algorithms is logistic regression","PeriodicalId":263404,"journal":{"name":"2022 Second International Conference on Interdisciplinary Cyber Physical Systems (ICPS)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131456946","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}
Gyanesh Samanta, Rishal Ramesh, Rushil Saxena, Devdarshan K Sardar, Sidhant Chourasiya, Fancy C
{"title":"DNAIoT - Dynamic Network Architecture for IoT","authors":"Gyanesh Samanta, Rishal Ramesh, Rushil Saxena, Devdarshan K Sardar, Sidhant Chourasiya, Fancy C","doi":"10.1109/icps55917.2022.00027","DOIUrl":"https://doi.org/10.1109/icps55917.2022.00027","url":null,"abstract":"Cyber-physical systems consist of various domains such as sensing, computation, controlling and networking in infrastructure, often connected by the internet. Controlling each device with separate controllers or switches seems tedious and troublesome. In today’s world, smart devices or an intelligent hub allow us to connect a limited number of devices, usually around 30-40. In this paper, we propose a way in which you can connect to over 200 IoT devices seamlessly without affecting the bandwidth to a single point. In a connected network system, you can increase the number of devices linearly. It is a unique system that is different from the existing systems based on WiFi and Bluetooth. We have used WiFi as the first communication link, and for controlling the IoT devices, we are using the Arduino Uno WiFi REV2 microcontroller equipped with Zigbee [2] communication. The Arduino Uno WiFi REV2 works as a bridge between WiFi and Zigbee [2] communication. This is a simple IoT-based work that connects multiple devices at once and provides a stable, reliable and fast connection, communication, and control between the devices As per our methodology we can connect more than 2000 devices over a range of 1000 meters.","PeriodicalId":263404,"journal":{"name":"2022 Second International Conference on Interdisciplinary Cyber Physical Systems (ICPS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130343648","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}