Pub Date : 2023-06-06DOI: 10.1109/MECO58584.2023.10155102
U. Reinsalu, T. Robal
This paper presents the design of a system that allows for remote, contactless calling of a smart elevator using a energy-efficient embedded system running on a battery. The main objective of this research was to create a low-power touchless service button, which can only be accessed by users in the immediate proximity of the elevator. The system uses a dynamic QR-code to make robust remote calls via a web-page opened on the user's phone, without the need for any authorization method. This is achieve by the use of Time-based One-time Password (TOTP) algorithm to generate periodically changing single-use passwords. The touch-free button system design uses an eInk display, a microcontroller, and RTC module for maximum energy savings. We show the potential of the proposed touch-free system design for various application areas.
{"title":"A Touch-Free Service Button for Smart Elevator Operation with Dynamic QR-code Generation","authors":"U. Reinsalu, T. Robal","doi":"10.1109/MECO58584.2023.10155102","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10155102","url":null,"abstract":"This paper presents the design of a system that allows for remote, contactless calling of a smart elevator using a energy-efficient embedded system running on a battery. The main objective of this research was to create a low-power touchless service button, which can only be accessed by users in the immediate proximity of the elevator. The system uses a dynamic QR-code to make robust remote calls via a web-page opened on the user's phone, without the need for any authorization method. This is achieve by the use of Time-based One-time Password (TOTP) algorithm to generate periodically changing single-use passwords. The touch-free button system design uses an eInk display, a microcontroller, and RTC module for maximum energy savings. We show the potential of the proposed touch-free system design for various application areas.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125164486","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}
Pub Date : 2023-06-06DOI: 10.1109/MECO58584.2023.10155079
Anxhela Gjecka, M. Fetaji
In recent times, machine learning has provided increasingly satisfying results in the field of medicine, providing results with very high accuracy while helping to reduce costs and diagnose the disease in real time. To achieve this, it is necessary to develop different deep machine learning techniques. Some of these are metaheuristic techniques that offer practical solutions for different types of chronic diseases. These types of algorithms have received the most attention in solving optimization problems. Therefore, this paper presents a wide review of the literature for solving the problems of feature selection using metaheuristic algorithms and selecting those that have had the highest performance compared to the results given by other algorithms. In this paper, a study of 71 articles from a research database was carried out, from which metaheuristic algorithms were analyzed and evidenced on the optimization and selection of features for the prediction of chronic diseases using numerical, binary, or even imaging data. The efficiency of the algorithms is measured based on the accuracy results, error rate, F-means, or other parameters or graphical representations found in this study. This work will help researchers to improve any of the methods, hybridize them, or even build applications for predicting diseases in the future. Gaps in this field have also been identified, and future studies should be conducted.
{"title":"Literature Review On Metaheuristics Techniques In The Health Care Industry","authors":"Anxhela Gjecka, M. Fetaji","doi":"10.1109/MECO58584.2023.10155079","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10155079","url":null,"abstract":"In recent times, machine learning has provided increasingly satisfying results in the field of medicine, providing results with very high accuracy while helping to reduce costs and diagnose the disease in real time. To achieve this, it is necessary to develop different deep machine learning techniques. Some of these are metaheuristic techniques that offer practical solutions for different types of chronic diseases. These types of algorithms have received the most attention in solving optimization problems. Therefore, this paper presents a wide review of the literature for solving the problems of feature selection using metaheuristic algorithms and selecting those that have had the highest performance compared to the results given by other algorithms. In this paper, a study of 71 articles from a research database was carried out, from which metaheuristic algorithms were analyzed and evidenced on the optimization and selection of features for the prediction of chronic diseases using numerical, binary, or even imaging data. The efficiency of the algorithms is measured based on the accuracy results, error rate, F-means, or other parameters or graphical representations found in this study. This work will help researchers to improve any of the methods, hybridize them, or even build applications for predicting diseases in the future. Gaps in this field have also been identified, and future studies should be conducted.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125452649","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}
Pub Date : 2023-06-06DOI: 10.1109/MECO58584.2023.10155096
Nikola Pop Tomov, V. Kokalanov, S. Koceski
In recent years, the use of deep learning techniques has gained widespread popularity in the field of computer vision, especially for tasks such as object detection and recognition. In this research paper, we present a deep learning-based approach for the real-time estimation of human body measurements using device cameras, intending to enhance the online shopping experience and reduce concerns related to size selection. The proposed method based on convolutional neural networks (CNNs) is evaluated and the results are presented.
{"title":"Deep Learning-Based Real-Time Body Measurements Using Device Camera","authors":"Nikola Pop Tomov, V. Kokalanov, S. Koceski","doi":"10.1109/MECO58584.2023.10155096","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10155096","url":null,"abstract":"In recent years, the use of deep learning techniques has gained widespread popularity in the field of computer vision, especially for tasks such as object detection and recognition. In this research paper, we present a deep learning-based approach for the real-time estimation of human body measurements using device cameras, intending to enhance the online shopping experience and reduce concerns related to size selection. The proposed method based on convolutional neural networks (CNNs) is evaluated and the results are presented.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131250401","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}
Pub Date : 2023-06-06DOI: 10.1109/MECO58584.2023.10155032
G. Laštovička-Medin, Dejan Karadžić
The purpose of this paper is to describe and study the capacity, potential and limitations of using thermal imaging camera to indicate the effects and track the changes caused by the physical exercises performed in the way that the certain part of body and muscles are stimulated. The methodology described here can be used as a reliable tool to prevent sport injuries and to track their recovery or showing quality of sportsmen training.
{"title":"Thermography: Features and utilization of thermal infrared camera and its application on human body in sports medicine","authors":"G. Laštovička-Medin, Dejan Karadžić","doi":"10.1109/MECO58584.2023.10155032","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10155032","url":null,"abstract":"The purpose of this paper is to describe and study the capacity, potential and limitations of using thermal imaging camera to indicate the effects and track the changes caused by the physical exercises performed in the way that the certain part of body and muscles are stimulated. The methodology described here can be used as a reliable tool to prevent sport injuries and to track their recovery or showing quality of sportsmen training.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125725568","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}
Pub Date : 2023-06-06DOI: 10.1109/MECO58584.2023.10154918
Amogh Jalan, Aniket Gupta, P. Meel
In today's world, it is pivotal to have to spot fake information as soon as it appears. Due to the vast and quick dissemination of news on the Internet, this is particularly crucial. Equally important is the capacity to determine if an article of news is accurate or false based on its headline. In this paper, we create a multi-lingual dataset and compare various algorithms on it. The outcome will be contrasted with the identification based on the entire text. The purpose of this is to put forth a technique for predicting fake news that strikes a balance between the quantity and quality of data analysis. A large number of studies on automatic fake news identification rely solely on English-language information, with only a few studies evaluating other language groups or contrasting several language features. This research examines textual characteristics that are not restricted to a specific language in the context of describing textual data for news discovery, as the widespread dissemination of false information is a prevalent global problem. To investigate text complexity, stylometric, and psychological aspects, the vocabulary of news articles published in English(American) and Hindi was examined. The traits that were retrieved help in the identification of real and fraudulent news. To create the detection model, we analyzed the performance of four ML algorithms: Multinomial Naive Bayes, Logistic Regression, Bernoulli Naive Bayes, and Bidirectional LSTM. With Logistic Regression and Bernoulli Naive Bayes an average accuracy of 86% was achieved, the results demonstrate that our suggested language-unrelated showcases are effective in classifying untrue and real news between two separate languages.
{"title":"Comparing Results of Multiple Machine Learning Algorithms on a bilingual dataset for the Detection of Fraudulent News","authors":"Amogh Jalan, Aniket Gupta, P. Meel","doi":"10.1109/MECO58584.2023.10154918","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10154918","url":null,"abstract":"In today's world, it is pivotal to have to spot fake information as soon as it appears. Due to the vast and quick dissemination of news on the Internet, this is particularly crucial. Equally important is the capacity to determine if an article of news is accurate or false based on its headline. In this paper, we create a multi-lingual dataset and compare various algorithms on it. The outcome will be contrasted with the identification based on the entire text. The purpose of this is to put forth a technique for predicting fake news that strikes a balance between the quantity and quality of data analysis. A large number of studies on automatic fake news identification rely solely on English-language information, with only a few studies evaluating other language groups or contrasting several language features. This research examines textual characteristics that are not restricted to a specific language in the context of describing textual data for news discovery, as the widespread dissemination of false information is a prevalent global problem. To investigate text complexity, stylometric, and psychological aspects, the vocabulary of news articles published in English(American) and Hindi was examined. The traits that were retrieved help in the identification of real and fraudulent news. To create the detection model, we analyzed the performance of four ML algorithms: Multinomial Naive Bayes, Logistic Regression, Bernoulli Naive Bayes, and Bidirectional LSTM. With Logistic Regression and Bernoulli Naive Bayes an average accuracy of 86% was achieved, the results demonstrate that our suggested language-unrelated showcases are effective in classifying untrue and real news between two separate languages.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117250907","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}
Pub Date : 2023-06-06DOI: 10.1109/MECO58584.2023.10154987
Alexandros Spournias, Evanthia Faliagka, Theodoros Skandamis, Christos D. Antonopoulos, N. Voros, G. Keramidas
This paper presents a system for detecting gestures and controlling devices in Ambient Assisted Living (AAL) environments using machine learning and Bluetooth Low Energy (BLE) technology. The system consists of two main components: a device equipped with a set of sensors to detect hand gestures via IMU sensor and a BLE-enabled hub that receives the gesture data and controls the lighting of the house. The hub uses machine learning algorithms to recognize hand gestures and transmit the corresponding commands to the devices. The hub, in turn, uses wifi to communicate with the devices and execute the appropriate actions based on the received commands. The proposed system's performance evaluation was carried out through a series of experiments in a AAL environment. The results demonstrate that the system is capable of accurately detecting hand gestures and controlling various devices such as lights, where the model's performance yields successful predictions with an accuracy rate of 90%. The proposed system provides a user-friendly and intuitive way for elderly or people with disabilities to control their environment without the need for complex interfaces or physical buttons. Furthermore, the system can be easily extended to support more gestures and devices, making it a flexible and scalable solution for AAL environments.
{"title":"Gestures detection and device control in AAL environments using machine learning and BLEs","authors":"Alexandros Spournias, Evanthia Faliagka, Theodoros Skandamis, Christos D. Antonopoulos, N. Voros, G. Keramidas","doi":"10.1109/MECO58584.2023.10154987","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10154987","url":null,"abstract":"This paper presents a system for detecting gestures and controlling devices in Ambient Assisted Living (AAL) environments using machine learning and Bluetooth Low Energy (BLE) technology. The system consists of two main components: a device equipped with a set of sensors to detect hand gestures via IMU sensor and a BLE-enabled hub that receives the gesture data and controls the lighting of the house. The hub uses machine learning algorithms to recognize hand gestures and transmit the corresponding commands to the devices. The hub, in turn, uses wifi to communicate with the devices and execute the appropriate actions based on the received commands. The proposed system's performance evaluation was carried out through a series of experiments in a AAL environment. The results demonstrate that the system is capable of accurately detecting hand gestures and controlling various devices such as lights, where the model's performance yields successful predictions with an accuracy rate of 90%. The proposed system provides a user-friendly and intuitive way for elderly or people with disabilities to control their environment without the need for complex interfaces or physical buttons. Furthermore, the system can be easily extended to support more gestures and devices, making it a flexible and scalable solution for AAL environments.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131806567","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}
Pub Date : 2023-06-06DOI: 10.1109/MECO58584.2023.10155059
M. A. Hail
The development of mobile applications for IoT systems has become increasingly important due to their ability to provide remote control, monitoring, and efficient analysis of device data for effective device management and decision-making. In recent years, the research on Named Data Networking (NDN) for IoT systems has focused on addressing challenges such as device heterogeneity, network scalability, data privacy, and efficient communication protocols for IoT-NDN devices. This paper presents the design of an app called “NDN4IoT” that enables remote management, control, and observation of IoT devices that utilize NDN technology. The app is integrated with the FIWARE IoT platform, which allows for the retrieval and storage of log information from the IoT-NDN devices. This log information can be used for critical data analysis and decision-making purposes before device failure. The proposed app design provides a user-friendly interface that enables efficient management and monitoring of the IoT-NDN devices remotely. This solution addresses the challenges of managing and controlling IoT devices, specifically those utilizing NDN technology, and enables efficient use of log data for analysis and decision-making purposes.
{"title":"Efficient Management, Control and Analysis of IoT-NDN Devices through “NDN4IoT” App Integrated with FIWARE","authors":"M. A. Hail","doi":"10.1109/MECO58584.2023.10155059","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10155059","url":null,"abstract":"The development of mobile applications for IoT systems has become increasingly important due to their ability to provide remote control, monitoring, and efficient analysis of device data for effective device management and decision-making. In recent years, the research on Named Data Networking (NDN) for IoT systems has focused on addressing challenges such as device heterogeneity, network scalability, data privacy, and efficient communication protocols for IoT-NDN devices. This paper presents the design of an app called “NDN4IoT” that enables remote management, control, and observation of IoT devices that utilize NDN technology. The app is integrated with the FIWARE IoT platform, which allows for the retrieval and storage of log information from the IoT-NDN devices. This log information can be used for critical data analysis and decision-making purposes before device failure. The proposed app design provides a user-friendly interface that enables efficient management and monitoring of the IoT-NDN devices remotely. This solution addresses the challenges of managing and controlling IoT devices, specifically those utilizing NDN technology, and enables efficient use of log data for analysis and decision-making purposes.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133895475","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}
Pub Date : 2023-06-06DOI: 10.1109/MECO58584.2023.10155043
Matthias Dziubany, A. Schmeink, Guido Dartmann
Time windows have great importance in the design of cyber physical systems (CPS) for transportation. In contrast to most transportation systems, where the time flexibility of customers is inadequately represented by fixed pick-up or delivery time windows, this paper assigns optimized pick-up or delivery time windows (appointments) with certain length inside exogenous flexibility time windows. The concept of appointments in flexibility time windows enables customers to report their true time flexibility, while keeping the pick-up or delivery time window short. By integrating the customers time flexibility substantially in the optimization of the transportation system, it well-deserved the description of cyber physical social system (CPSS). Simulations on the cordeau dataset confirm, that the new time window concept is very promising, since an user-accepted exploitment of time flexibility yields to less transportation costs. Further, our mixed integer program (MIP) determining appointment time windows, can also be used as a very fast preprocessing technique to shrink time windows in transportation problems, which yields to energy-efficient computation.
时间窗在交通网络物理系统(CPS)设计中具有重要意义。针对大多数运输系统中固定的取货或送货时间窗口不能充分体现客户的时间灵活性的问题，本文在外生弹性时间窗口内分配一定长度的优化取货或送货时间窗口(预约)。灵活时间窗口中的约会概念使客户能够报告他们真正的时间灵活性，同时保持取件或交付时间窗口短。通过将顾客的时间灵活性大量地整合到运输系统的优化中，它是名副其实的网络物理社会系统(cyber physical social system, CPSS)。cordeau数据集的模拟证实，新的时间窗口概念非常有前途，因为用户接受的时间灵活性的利用可以降低运输成本。此外，我们的混合整数规划(MIP)确定预约时间窗口，也可以作为一种非常快速的预处理技术来缩小运输问题的时间窗口，从而产生节能计算。
{"title":"Energy-efficient Cyber Physical Social System for Transportation with Appointments","authors":"Matthias Dziubany, A. Schmeink, Guido Dartmann","doi":"10.1109/MECO58584.2023.10155043","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10155043","url":null,"abstract":"Time windows have great importance in the design of cyber physical systems (CPS) for transportation. In contrast to most transportation systems, where the time flexibility of customers is inadequately represented by fixed pick-up or delivery time windows, this paper assigns optimized pick-up or delivery time windows (appointments) with certain length inside exogenous flexibility time windows. The concept of appointments in flexibility time windows enables customers to report their true time flexibility, while keeping the pick-up or delivery time window short. By integrating the customers time flexibility substantially in the optimization of the transportation system, it well-deserved the description of cyber physical social system (CPSS). Simulations on the cordeau dataset confirm, that the new time window concept is very promising, since an user-accepted exploitment of time flexibility yields to less transportation costs. Further, our mixed integer program (MIP) determining appointment time windows, can also be used as a very fast preprocessing technique to shrink time windows in transportation problems, which yields to energy-efficient computation.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"253 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134061605","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}
Pub Date : 2023-06-06DOI: 10.1109/MECO58584.2023.10154990
A. Levina, Andrew Plotnikov, Efim Ashmarov
This paper will illustrate a new class of analysis off hash functions. The method will be demonstrated on the algorithm SHA-256. The idea behind the attack is to represent the algorithm as Boolean equations and solve them using tree notation. The new attack will help to speed up the process of finding vulnerabilities in hash functions, which may help to create more secure hash functions in the future. Despite the fact that the article will describe the approbation of the method only on SHA-256, these results can also be extrapolated to other hashing algorithms, since the idea, presented in this method, does not depend on an algorithm specification.
{"title":"New Method of Hash Functions Analysis","authors":"A. Levina, Andrew Plotnikov, Efim Ashmarov","doi":"10.1109/MECO58584.2023.10154990","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10154990","url":null,"abstract":"This paper will illustrate a new class of analysis off hash functions. The method will be demonstrated on the algorithm SHA-256. The idea behind the attack is to represent the algorithm as Boolean equations and solve them using tree notation. The new attack will help to speed up the process of finding vulnerabilities in hash functions, which may help to create more secure hash functions in the future. Despite the fact that the article will describe the approbation of the method only on SHA-256, these results can also be extrapolated to other hashing algorithms, since the idea, presented in this method, does not depend on an algorithm specification.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"280 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123434930","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}
Pub Date : 2023-06-06DOI: 10.1109/MECO58584.2023.10155084
D. Borissova, Iliyan Barzev, R. Yoshinov, Monka Kotseva
The rapid development of ICT technologies, together with applications, has led to a huge amount of data exchanged in the Internet space. The protection of this data, used both by individual households and by business and scientific organizations, appears to be essential. To be able to protect huge amounts of data against malware attacks, researchers are to be able to understand the malware mechanism to propose adequate measures. For this purpose, proper virtual machine software that is at the core of research efforts for malware detection is to used. Due to the virtualization, multiple OS instances on a single physical machine could be simulated to detect and analysis of malware. In this regard, the selection of appropriate virtual machine software is of great importance, and in the current article, two group decision-making models are proposed. These models were applied in the selection of VM software for desktop Windows deployment. The obtained results demonstrated the applicability of both models.
{"title":"Group Decision-Making Models for Selection of Virtual Machine Software for Malware Detection Purposes","authors":"D. Borissova, Iliyan Barzev, R. Yoshinov, Monka Kotseva","doi":"10.1109/MECO58584.2023.10155084","DOIUrl":"https://doi.org/10.1109/MECO58584.2023.10155084","url":null,"abstract":"The rapid development of ICT technologies, together with applications, has led to a huge amount of data exchanged in the Internet space. The protection of this data, used both by individual households and by business and scientific organizations, appears to be essential. To be able to protect huge amounts of data against malware attacks, researchers are to be able to understand the malware mechanism to propose adequate measures. For this purpose, proper virtual machine software that is at the core of research efforts for malware detection is to used. Due to the virtualization, multiple OS instances on a single physical machine could be simulated to detect and analysis of malware. In this regard, the selection of appropriate virtual machine software is of great importance, and in the current article, two group decision-making models are proposed. These models were applied in the selection of VM software for desktop Windows deployment. The obtained results demonstrated the applicability of both models.","PeriodicalId":187825,"journal":{"name":"2023 12th Mediterranean Conference on Embedded Computing (MECO)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125140423","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}
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