Pub Date : 2021-12-01DOI: 10.1109/uemcon53757.2021.9666549
Baker Al Smadi, A. A. AlQahtani, Hosam Alamleh
Credit card fraud is one of the most critical threats affecting individuals and companies worldwide, particularly with the growing number of financial transactions involving credit cards every day. The most common threats are likely to come from database breaches and identity theft. All these threats put the security of financial transactions at severe risk and require a fundamental solution. This paper aims to suggest a secure online payment system that significantly improves credit card security. Our system can be particularly resilient to potential cyber-attacks, unauthorized users, man-in-the-middle, and guessing attacks for credit card number generation or illegal financial activities by utilizing a secure communication channel between the cardholder and server. Our system uses a shared secret and a verification token that allow both sides to communicate through an encrypted channel. Furthermore, our system is designed to generate a one-time credit card number at the user’s machine that is verified by the server without sharing the credit card number over the network. Our approach combines machine learning (ML) algorithms with unique temporary credit card numbers in one integrated system, which is the first approach in the online credit card protection system. The new security system generates a one-time-use credit card number for each transaction with a predetermined amount of money. Simultaneously, the system can detect potential fraud utilizing ML algorithm with new critical features such as the IMEI or IP address, the transaction’s location, and other features.
{"title":"Secure and Fraud Proof Online Payment System for Credit Cards","authors":"Baker Al Smadi, A. A. AlQahtani, Hosam Alamleh","doi":"10.1109/uemcon53757.2021.9666549","DOIUrl":"https://doi.org/10.1109/uemcon53757.2021.9666549","url":null,"abstract":"Credit card fraud is one of the most critical threats affecting individuals and companies worldwide, particularly with the growing number of financial transactions involving credit cards every day. The most common threats are likely to come from database breaches and identity theft. All these threats put the security of financial transactions at severe risk and require a fundamental solution. This paper aims to suggest a secure online payment system that significantly improves credit card security. Our system can be particularly resilient to potential cyber-attacks, unauthorized users, man-in-the-middle, and guessing attacks for credit card number generation or illegal financial activities by utilizing a secure communication channel between the cardholder and server. Our system uses a shared secret and a verification token that allow both sides to communicate through an encrypted channel. Furthermore, our system is designed to generate a one-time credit card number at the user’s machine that is verified by the server without sharing the credit card number over the network. Our approach combines machine learning (ML) algorithms with unique temporary credit card numbers in one integrated system, which is the first approach in the online credit card protection system. The new security system generates a one-time-use credit card number for each transaction with a predetermined amount of money. Simultaneously, the system can detect potential fraud utilizing ML algorithm with new critical features such as the IMEI or IP address, the transaction’s location, and other features.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114344327","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 : 2021-12-01DOI: 10.1109/uemcon53757.2021.9666645
R. R. Maaliw
Student learning optimization is one of the main goals of education. A conventional e-learning system fails to accomplish its true purpose due to the lack or absence of personalization features. This paper presents an end-to-end approach for supporting students’ diverse needs by classifying their learning styles in a virtual learning environment (VLE) and embedding the discovered knowledge in an adaptive e-learning system prototype. Furthermore, we validated different models’ accuracies and comparative consistencies to manual methods using 704,592 interactions log data of 898 learners. Quantitative results show that the Support Vector Machine (SVM) achieves cross-validated accuracies of 88%, 86%, and 87% (processing, perception & input) of the Felder-Silverman Learning Style Model (FSLSM) and the Decision Tree (DT) for the understanding dimension with 86% accuracy.
{"title":"A Personalized Virtual Learning Environment Using Multiple Modeling Techniques","authors":"R. R. Maaliw","doi":"10.1109/uemcon53757.2021.9666645","DOIUrl":"https://doi.org/10.1109/uemcon53757.2021.9666645","url":null,"abstract":"Student learning optimization is one of the main goals of education. A conventional e-learning system fails to accomplish its true purpose due to the lack or absence of personalization features. This paper presents an end-to-end approach for supporting students’ diverse needs by classifying their learning styles in a virtual learning environment (VLE) and embedding the discovered knowledge in an adaptive e-learning system prototype. Furthermore, we validated different models’ accuracies and comparative consistencies to manual methods using 704,592 interactions log data of 898 learners. Quantitative results show that the Support Vector Machine (SVM) achieves cross-validated accuracies of 88%, 86%, and 87% (processing, perception & input) of the Felder-Silverman Learning Style Model (FSLSM) and the Decision Tree (DT) for the understanding dimension with 86% accuracy.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"183 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113987778","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 : 2021-12-01DOI: 10.1109/UEMCON53757.2021.9666512
Alem Huayta Uribe, Jalber Brayan Macuri Vasquez, Alexander Claudio Miranda Yauri, Deyby Huamanchahua
This research presents the design and control of an automatic monitoring system of the main water parameters for rainbow trout culture, which is a freshwater species distributed in the high Andean zones along with the Andes mountain range, which will be given through mechatronic systems. This work presents the control and monitoring of temperature, dissolved oxygen level, pH, and water level independently so that monitoring and control are simple. The procedure shows the use of different sensors that capture the water parameters such as the use of a Ceratex analog sensor to measure the pH, also the PT100 that will help us to calculate the temperature, and finally an Oxymax sensor for dissolved oxygen, all this helps us to extend the species and prevent its extinction, For the part of the programmed environment the information will be sent and displayed in the visual environment of the system, parallel to this the controller will act based on the information received, to maintain the water parameters in the appropriate range for rainbow trout, which are dissolved oxygen greater than 6 mg / l and less than 8. 5mg/l, within the temperature level, the species lives in waters of 9° to 14° C and with a pH of 6.6 to 7.9. In addition, the automatic mechatronic system implemented will facilitate and improve the monitoring and control of water parameters for rainbow trout culture.
{"title":"Control and Monitoring System of Hydraulic Parameters for Rainbow Trout Culture","authors":"Alem Huayta Uribe, Jalber Brayan Macuri Vasquez, Alexander Claudio Miranda Yauri, Deyby Huamanchahua","doi":"10.1109/UEMCON53757.2021.9666512","DOIUrl":"https://doi.org/10.1109/UEMCON53757.2021.9666512","url":null,"abstract":"This research presents the design and control of an automatic monitoring system of the main water parameters for rainbow trout culture, which is a freshwater species distributed in the high Andean zones along with the Andes mountain range, which will be given through mechatronic systems. This work presents the control and monitoring of temperature, dissolved oxygen level, pH, and water level independently so that monitoring and control are simple. The procedure shows the use of different sensors that capture the water parameters such as the use of a Ceratex analog sensor to measure the pH, also the PT100 that will help us to calculate the temperature, and finally an Oxymax sensor for dissolved oxygen, all this helps us to extend the species and prevent its extinction, For the part of the programmed environment the information will be sent and displayed in the visual environment of the system, parallel to this the controller will act based on the information received, to maintain the water parameters in the appropriate range for rainbow trout, which are dissolved oxygen greater than 6 mg / l and less than 8. 5mg/l, within the temperature level, the species lives in waters of 9° to 14° C and with a pH of 6.6 to 7.9. In addition, the automatic mechatronic system implemented will facilitate and improve the monitoring and control of water parameters for rainbow trout culture.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"157 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124227664","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 : 2021-12-01DOI: 10.1109/UEMCON53757.2021.9666693
Mohsin Asad, A. Singha
The Gallium-Nitride (GaN) based converters can operate in a high frequency range without compromising the efficiency as compared to silicon based converters. However, the reverse conduction loss during dead-time in GaN degrades the efficiency; thus, optimization of dead-time is required to improve the efficiency. This paper proposes a real-time dead-time optimization controller for the synchronous boost converter. The proposed controller samples only the inductor current and output voltage at the rate of switching frequency to determine the optimal dead-time. Thus, this is suitable for high-frequency converters. Furthermore, the proposed controller requires only a few switching cycles to compute the optimal dead-time. A prototype of the boost converter is developed using GaN FET from GaN System and the proposed dead-time controller is implemented using a TI digital controller.
{"title":"Real-Time Dead-Time Optimization in a GaN-Based Boost Converter Using a Digital Controller","authors":"Mohsin Asad, A. Singha","doi":"10.1109/UEMCON53757.2021.9666693","DOIUrl":"https://doi.org/10.1109/UEMCON53757.2021.9666693","url":null,"abstract":"The Gallium-Nitride (GaN) based converters can operate in a high frequency range without compromising the efficiency as compared to silicon based converters. However, the reverse conduction loss during dead-time in GaN degrades the efficiency; thus, optimization of dead-time is required to improve the efficiency. This paper proposes a real-time dead-time optimization controller for the synchronous boost converter. The proposed controller samples only the inductor current and output voltage at the rate of switching frequency to determine the optimal dead-time. Thus, this is suitable for high-frequency converters. Furthermore, the proposed controller requires only a few switching cycles to compute the optimal dead-time. A prototype of the boost converter is developed using GaN FET from GaN System and the proposed dead-time controller is implemented using a TI digital controller.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125772328","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 : 2021-12-01DOI: 10.1109/UEMCON53757.2021.9666607
T. T. Khoei, Shereen S. Ismail, N. Kaabouch
Smart grid is an emerging technology that transfers power to users intelligently through two-way communication. Despite the benefits of this network, it is prone to different cyber-attacks. One solution to address this issue is the use of intrusion detection systems. Several studies have been conducted to investigate the shortcomings of such system, which include low detection rates and high false alarms; however, these studies did not completely address these issues. Motivated by the existing gaps, we investigate the performance of boosting-based models, namely Adaptive Boosting, Gradient Boosting, and Categorical Boosting, in detecting cyber-attacks on smart grid networks. The performance evaluation is conducted based on accuracy, probability of detection, probability of misdetection, and probability of false alarm. The results of the models were compared with those of three widely used traditional machine learning models, namely support vector machine, naïve Bayes, and K nearest neighbor. The benchmark of CICDDoS 2019 is selected as a dataset for training, validation, and testing. The ReliefF feature selection technique is used to identify the most important features for training the models. We also used the Tree-structured Parzen Estimator optimization technique to find the best hyperparameters for each model and ensure optimal performance. The results show that the boosting-based models outperform the three traditional models, and the Categorical Boosting classifier has the best results in terms of the four-evaluation metrics.
{"title":"Boosting-based Models with Tree-structured Parzen Estimator Optimization to Detect Intrusion Attacks on Smart Grid","authors":"T. T. Khoei, Shereen S. Ismail, N. Kaabouch","doi":"10.1109/UEMCON53757.2021.9666607","DOIUrl":"https://doi.org/10.1109/UEMCON53757.2021.9666607","url":null,"abstract":"Smart grid is an emerging technology that transfers power to users intelligently through two-way communication. Despite the benefits of this network, it is prone to different cyber-attacks. One solution to address this issue is the use of intrusion detection systems. Several studies have been conducted to investigate the shortcomings of such system, which include low detection rates and high false alarms; however, these studies did not completely address these issues. Motivated by the existing gaps, we investigate the performance of boosting-based models, namely Adaptive Boosting, Gradient Boosting, and Categorical Boosting, in detecting cyber-attacks on smart grid networks. The performance evaluation is conducted based on accuracy, probability of detection, probability of misdetection, and probability of false alarm. The results of the models were compared with those of three widely used traditional machine learning models, namely support vector machine, naïve Bayes, and K nearest neighbor. The benchmark of CICDDoS 2019 is selected as a dataset for training, validation, and testing. The ReliefF feature selection technique is used to identify the most important features for training the models. We also used the Tree-structured Parzen Estimator optimization technique to find the best hyperparameters for each model and ensure optimal performance. The results show that the boosting-based models outperform the three traditional models, and the Categorical Boosting classifier has the best results in terms of the four-evaluation metrics.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132209506","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 : 2021-12-01DOI: 10.1109/uemcon53757.2021.9666712
Ida Sèmévo Tognisse, Jules R. Dégila, A. Kora
Access to the Internet, new information, and communication technologies are becoming necessary in human life. However, for people in rural and remote areas, connectivity remains scarce and a big challenge. It is a fact that telecommunication services are primarily deployed in urban areas, for which the return on investment is more evident, to the detriment of rural and isolated areas. However, the absence of these services constitutes a hindrance to socio-economic development. In this paper, we consider that rural connectivity presents specific needs and peculiarities. We first recall the challenges to removing barriers to connectivity in rural areas. Second, we argue that improving access to technology requires expanding mobile networks and implementing appropriate technologies. Thus, this article takes stock of the technologies suitable to rural, poor, and isolated areas. After analyzing and discussing each technology and highlighting the impact of the choice of technology on the challenges of connectivity in remote areas, this paper proposes an architecture for future networks based on existing solutions to eliminate the coverage gap in rural areas.
{"title":"Connecting Rural Areas: A Solution Approach to Bridging the Coverage Gap","authors":"Ida Sèmévo Tognisse, Jules R. Dégila, A. Kora","doi":"10.1109/uemcon53757.2021.9666712","DOIUrl":"https://doi.org/10.1109/uemcon53757.2021.9666712","url":null,"abstract":"Access to the Internet, new information, and communication technologies are becoming necessary in human life. However, for people in rural and remote areas, connectivity remains scarce and a big challenge. It is a fact that telecommunication services are primarily deployed in urban areas, for which the return on investment is more evident, to the detriment of rural and isolated areas. However, the absence of these services constitutes a hindrance to socio-economic development. In this paper, we consider that rural connectivity presents specific needs and peculiarities. We first recall the challenges to removing barriers to connectivity in rural areas. Second, we argue that improving access to technology requires expanding mobile networks and implementing appropriate technologies. Thus, this article takes stock of the technologies suitable to rural, poor, and isolated areas. After analyzing and discussing each technology and highlighting the impact of the choice of technology on the challenges of connectivity in remote areas, this paper proposes an architecture for future networks based on existing solutions to eliminate the coverage gap in rural areas.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131621661","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 : 2021-12-01DOI: 10.1109/uemcon53757.2021.9666602
Amin H. Al-Ka'bi
In this research work, a proposed method for extending the lifetime of energy-constrained Mobile wireless sensor networks (MWSNs) is presented. This method is based on the fact that RF signal carries both information and energy at the same time. Hence, by increasing the efficiency of energy harvesting from radio frequency (RF) signals, the lifetime of the wireless network can be significantly extended. The Simultaneous Wireless Information and Power Transfer (SWIPT) in this technique enables harvesting of energy by relay nodes which in turn can be used for wireless data transmission. In order to enhance the lifetime of the mobile wireless network, the transmitted RF energy can be recycled at the receiver side. On the other hand, a balance between energy harvesting and wireless data transmission is required in order to maximize the overall efficiency of the system. Particle Swarm Optimization (PSO) is employed to obtain the optimum resource allocation policies which maximizes the system energy efficiency. A cost function is framed for this purpose and PSO attains maximum energy efficiency by improving the solution of the cost function at each iteration with respect to given constraints.
{"title":"Enhancement of Energy Harvesting Efficiency in Mobile Wireless Sensor Networks","authors":"Amin H. Al-Ka'bi","doi":"10.1109/uemcon53757.2021.9666602","DOIUrl":"https://doi.org/10.1109/uemcon53757.2021.9666602","url":null,"abstract":"In this research work, a proposed method for extending the lifetime of energy-constrained Mobile wireless sensor networks (MWSNs) is presented. This method is based on the fact that RF signal carries both information and energy at the same time. Hence, by increasing the efficiency of energy harvesting from radio frequency (RF) signals, the lifetime of the wireless network can be significantly extended. The Simultaneous Wireless Information and Power Transfer (SWIPT) in this technique enables harvesting of energy by relay nodes which in turn can be used for wireless data transmission. In order to enhance the lifetime of the mobile wireless network, the transmitted RF energy can be recycled at the receiver side. On the other hand, a balance between energy harvesting and wireless data transmission is required in order to maximize the overall efficiency of the system. Particle Swarm Optimization (PSO) is employed to obtain the optimum resource allocation policies which maximizes the system energy efficiency. A cost function is framed for this purpose and PSO attains maximum energy efficiency by improving the solution of the cost function at each iteration with respect to given constraints.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132608828","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 : 2021-12-01DOI: 10.1109/uemcon53757.2021.9666697
Joseph Spanilo, David Edwards, Sunjae Park, Mira Yun
Google Maps has made it easy for people to plan their commute based on how busy a road is. This has also been expanded to help users understand how busy a store may be during the day. However this feature has not been applied to buildings with much depth. DenCity aims to solve this problem by showing a way that the number of users can be tracked without having to implement new hardware to existing infrastructure and without the user having to participate. DenCity uses the WiFi signals sent out by devices to track the number of users near an access point. As a result it makes it possible for users to know the number of people within a building or given area.
{"title":"DenCity: A WiFi Location Tracking Solution","authors":"Joseph Spanilo, David Edwards, Sunjae Park, Mira Yun","doi":"10.1109/uemcon53757.2021.9666697","DOIUrl":"https://doi.org/10.1109/uemcon53757.2021.9666697","url":null,"abstract":"Google Maps has made it easy for people to plan their commute based on how busy a road is. This has also been expanded to help users understand how busy a store may be during the day. However this feature has not been applied to buildings with much depth. DenCity aims to solve this problem by showing a way that the number of users can be tracked without having to implement new hardware to existing infrastructure and without the user having to participate. DenCity uses the WiFi signals sent out by devices to track the number of users near an access point. As a result it makes it possible for users to know the number of people within a building or given area.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128939132","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 : 2021-12-01DOI: 10.1109/UEMCON53757.2021.9666530
Albert H Carlson, Garret Gang, Torsten Gang, Bhaskar Ghosh, I. Dutta
Cybersecurity professionals have relied on the key space of a cipher to compare encryption algorithms and select the best encryptions for transmitted data. Peer reviewed strong ciphers have been assumed to maintain strength for all messages. It is thought that only brute force attacks can break these ciphers, so the key space calculation for these algorithms uses the maximum key space to determine the unicity distance. Unfortunately, the key space is heavily dependent on the user and habits of the user, as well as the content of the message. In this paper, we present factors that affect the key space size and show that the effects of these factors can seriously decrease the security of a cipher for a particular message. By considering these factors, a cybersecurity practitioner can properly assess vulnerability and choose the best security for that message.
{"title":"Evaluating True Cryptographic Key Space Size","authors":"Albert H Carlson, Garret Gang, Torsten Gang, Bhaskar Ghosh, I. Dutta","doi":"10.1109/UEMCON53757.2021.9666530","DOIUrl":"https://doi.org/10.1109/UEMCON53757.2021.9666530","url":null,"abstract":"Cybersecurity professionals have relied on the key space of a cipher to compare encryption algorithms and select the best encryptions for transmitted data. Peer reviewed strong ciphers have been assumed to maintain strength for all messages. It is thought that only brute force attacks can break these ciphers, so the key space calculation for these algorithms uses the maximum key space to determine the unicity distance. Unfortunately, the key space is heavily dependent on the user and habits of the user, as well as the content of the message. In this paper, we present factors that affect the key space size and show that the effects of these factors can seriously decrease the security of a cipher for a particular message. By considering these factors, a cybersecurity practitioner can properly assess vulnerability and choose the best security for that message.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133522201","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 : 2021-12-01DOI: 10.1109/UEMCON53757.2021.9666573
Suzanna E. Schmeelk, Kutub Thakur, M. Ali, Denise M. Dragos, Abdullah Al-Hayajneh, Bryan Rendra Pramana
Data has been collected and stored for thousands of years. Securing data during the digital age has remained difficult. Research shows that in 2018 there was over 33 zettabytes of data, which is approximately an equivalent to 129 billion 256GB mobile devices of data. Risk management in recent years has made attempts at balancing data security risks with organizational business and budgetary requirements. This research examines high probability data security threats and mitigations. It then reports on the threats in connection with the top United States healthcare data breaches reported during the COVID outbreak to the Health and Human Services (HHS) between June 11, 2020 and June 11, 2021. The data analysis shows that there were nine breaches of over a million affected individuals reported to HHS affecting 15,936,679 individuals in total. Five-million individuals is approximately larger than the populations of Los Angeles, New York, and Chicago combined. We connect the common security risks with the reports of these incidents to gain insights into common network security concerns and inform future network architectures and risk mitigations.
{"title":"Top Reported Data Security Risks in the Age of COVID-19","authors":"Suzanna E. Schmeelk, Kutub Thakur, M. Ali, Denise M. Dragos, Abdullah Al-Hayajneh, Bryan Rendra Pramana","doi":"10.1109/UEMCON53757.2021.9666573","DOIUrl":"https://doi.org/10.1109/UEMCON53757.2021.9666573","url":null,"abstract":"Data has been collected and stored for thousands of years. Securing data during the digital age has remained difficult. Research shows that in 2018 there was over 33 zettabytes of data, which is approximately an equivalent to 129 billion 256GB mobile devices of data. Risk management in recent years has made attempts at balancing data security risks with organizational business and budgetary requirements. This research examines high probability data security threats and mitigations. It then reports on the threats in connection with the top United States healthcare data breaches reported during the COVID outbreak to the Health and Human Services (HHS) between June 11, 2020 and June 11, 2021. The data analysis shows that there were nine breaches of over a million affected individuals reported to HHS affecting 15,936,679 individuals in total. Five-million individuals is approximately larger than the populations of Los Angeles, New York, and Chicago combined. We connect the common security risks with the reports of these incidents to gain insights into common network security concerns and inform future network architectures and risk mitigations.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133617577","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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