Pub Date : 2023-03-08DOI: 10.1109/ITIKD56332.2023.10100036
Aisha Alshamsi, Z. Maamar, M. Kuhail
Establishing an adequate and flexible access control over assets in an organization is one of the main pillars of a successful information and technology security-strategy. To ensure efficient use of these assets in terms of availability, safety, and confidentiality, organizations roll out different strategies and adopt different techniques. These strategies and techniques could be based on roles to set access controls (Role-Based Access Control). Despite its popularity, there is an increasing interest in addressing RBAC's limitations with focus on how to enforce an adequate level of access control over the available resources and how to define a flexible control over these resources so that accessibility and authenticity are achieved at the right time and right place. This paper addresses some of these limitations by adopting the Open Digital Rights Language (ODRL) to express who can do what, where, when, and how. ODRL is a policy language that offers flexible control over digital content. By weaving ODRL into RBAC, this paper illustrates how to specify what users are allowed, not allowed, and must be allowed to do through a set of constrained rules specialized into permissions, prohibitions, and duties.
{"title":"Towards an approach for weaving Open Digital Rights Language into Role-Based Access Control","authors":"Aisha Alshamsi, Z. Maamar, M. Kuhail","doi":"10.1109/ITIKD56332.2023.10100036","DOIUrl":"https://doi.org/10.1109/ITIKD56332.2023.10100036","url":null,"abstract":"Establishing an adequate and flexible access control over assets in an organization is one of the main pillars of a successful information and technology security-strategy. To ensure efficient use of these assets in terms of availability, safety, and confidentiality, organizations roll out different strategies and adopt different techniques. These strategies and techniques could be based on roles to set access controls (Role-Based Access Control). Despite its popularity, there is an increasing interest in addressing RBAC's limitations with focus on how to enforce an adequate level of access control over the available resources and how to define a flexible control over these resources so that accessibility and authenticity are achieved at the right time and right place. This paper addresses some of these limitations by adopting the Open Digital Rights Language (ODRL) to express who can do what, where, when, and how. ODRL is a policy language that offers flexible control over digital content. By weaving ODRL into RBAC, this paper illustrates how to specify what users are allowed, not allowed, and must be allowed to do through a set of constrained rules specialized into permissions, prohibitions, and duties.","PeriodicalId":283631,"journal":{"name":"2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125218944","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 : 2023-03-08DOI: 10.1109/ITIKD56332.2023.10099567
Maryam Waheed Alawadhi, Wasan Shaker Awad
As the cyber security field enhanced within years, threats and vulnerabilities have increased massively among the world by each second. Such risks have resulted an immediate action by businesses and organization by implementing and deploying different technologies in order to secure and defend such attacks that may cause problematic actions by hackers. This paper will discuss one of the key techniques to increase the security for the organizations' data. Multi-Factor Authentication (MFA) is known as a technique that uses two - or more- factors of authentication when accessing the systems/software of the business in order to rise data's protection. However, to design and plan the implementation of such technique, another model is presented and benchmarked with other models mentioned to improve the representation of MFA using Petri Nets.
{"title":"Multi-Factor Authentication Modeling using Petri Nets: Review","authors":"Maryam Waheed Alawadhi, Wasan Shaker Awad","doi":"10.1109/ITIKD56332.2023.10099567","DOIUrl":"https://doi.org/10.1109/ITIKD56332.2023.10099567","url":null,"abstract":"As the cyber security field enhanced within years, threats and vulnerabilities have increased massively among the world by each second. Such risks have resulted an immediate action by businesses and organization by implementing and deploying different technologies in order to secure and defend such attacks that may cause problematic actions by hackers. This paper will discuss one of the key techniques to increase the security for the organizations' data. Multi-Factor Authentication (MFA) is known as a technique that uses two - or more- factors of authentication when accessing the systems/software of the business in order to rise data's protection. However, to design and plan the implementation of such technique, another model is presented and benchmarked with other models mentioned to improve the representation of MFA using Petri Nets.","PeriodicalId":283631,"journal":{"name":"2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125796692","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 : 2023-03-08DOI: 10.1109/ITIKD56332.2023.10100328
Abdelrahman Shata, Zineddine N. Haitaamar, A. Benkrid
The COVID-19 pandemic took the world by surprise, and everything came to a halt. The education sector had to adjust accordingly by shifting to online learning. If the online delivery experience was overall successful, assessment integrity becomes questionable as examinees still manage to circumvent the anti-plagiarism mechanism put in place. In this paper, we propose an artificial intelligence solution using face and head pose detection to estimate the neutral position of the examinee which will form the basis to detect any suspicious behavior. The resulting implementation achieved a 97% accuracy when detecting the examinee in the frame and a 98% accuracy when there are multiple faces detected.
{"title":"Baseline Estimation in Face Detection for AI Proctored Examinations through Convoluted Neural Networks","authors":"Abdelrahman Shata, Zineddine N. Haitaamar, A. Benkrid","doi":"10.1109/ITIKD56332.2023.10100328","DOIUrl":"https://doi.org/10.1109/ITIKD56332.2023.10100328","url":null,"abstract":"The COVID-19 pandemic took the world by surprise, and everything came to a halt. The education sector had to adjust accordingly by shifting to online learning. If the online delivery experience was overall successful, assessment integrity becomes questionable as examinees still manage to circumvent the anti-plagiarism mechanism put in place. In this paper, we propose an artificial intelligence solution using face and head pose detection to estimate the neutral position of the examinee which will form the basis to detect any suspicious behavior. The resulting implementation achieved a 97% accuracy when detecting the examinee in the frame and a 98% accuracy when there are multiple faces detected.","PeriodicalId":283631,"journal":{"name":"2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125580288","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 : 2023-03-08DOI: 10.1109/ITIKD56332.2023.10100192
V. Subramanian, Jayakumar V. Karunamurthy, Balaji Ramachandran
LoRa is the de facto wireless platform of the Internet of Things (IoT). It is a smart and globally accepted low power ultra-long range, low-data rate communication protocol widely used for low frequent sensor telemetry and actuation. The simplicity, license-free spectrum, and long range enable the end user to transmit data even to Low Earth Orbit (LEO) satellites. The relative velocity of the LEO satellite from a stationary transmitter on the earth's surface is very high and time-varying, because of its short orbital period and high velocity, due to which the doppler shift and doppler rate are more prominent. LEO satellite signal reception is highest at the mid-pass duration, but unfortunately, the doppler rate is also highest during the same duration. In LoRa communication protocol, a higher spreading factor (SF12) results in better signal reception and communication range. But the LoRa communication at a higher spreading factor (SF12) results in packet error mainly due to the doppler rate, due to which a transmitter is forced to choose a lower spreading factor (SF9). This paper looks at precisely emulating the doppler shift and doppler rate for the entire pass duration of a LEO satellite using dynamic external hardware clock manipulation on an SX1262 LoRa chipset. A low-cost transmitter-side hardware doppler compensation technique is also explored, which encourages the transmitter to use a higher spreading factor (SF12) for better-guaranteed packet reception by the satellite.
{"title":"Hardware doppler shift emulation and compensation for LoRa LEO satellite communication","authors":"V. Subramanian, Jayakumar V. Karunamurthy, Balaji Ramachandran","doi":"10.1109/ITIKD56332.2023.10100192","DOIUrl":"https://doi.org/10.1109/ITIKD56332.2023.10100192","url":null,"abstract":"LoRa is the de facto wireless platform of the Internet of Things (IoT). It is a smart and globally accepted low power ultra-long range, low-data rate communication protocol widely used for low frequent sensor telemetry and actuation. The simplicity, license-free spectrum, and long range enable the end user to transmit data even to Low Earth Orbit (LEO) satellites. The relative velocity of the LEO satellite from a stationary transmitter on the earth's surface is very high and time-varying, because of its short orbital period and high velocity, due to which the doppler shift and doppler rate are more prominent. LEO satellite signal reception is highest at the mid-pass duration, but unfortunately, the doppler rate is also highest during the same duration. In LoRa communication protocol, a higher spreading factor (SF12) results in better signal reception and communication range. But the LoRa communication at a higher spreading factor (SF12) results in packet error mainly due to the doppler rate, due to which a transmitter is forced to choose a lower spreading factor (SF9). This paper looks at precisely emulating the doppler shift and doppler rate for the entire pass duration of a LEO satellite using dynamic external hardware clock manipulation on an SX1262 LoRa chipset. A low-cost transmitter-side hardware doppler compensation technique is also explored, which encourages the transmitter to use a higher spreading factor (SF12) for better-guaranteed packet reception by the satellite.","PeriodicalId":283631,"journal":{"name":"2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114213779","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 : 2023-03-08DOI: 10.1109/ITIKD56332.2023.10100257
Abdulla Hussain Ali Mohamed, S. Subramanian
With the blooming of technology, the financial sector has shown various number of improvements and has provided multiple e-financial services. Frauds can occur easily and quickly in data that lack safety levels. Although there are many laws that reduces the outcome of hacking, but unfortunately these laws cannot keep up with the enormous increase of hacking attacks level that are present. In this research, Bayes point machine, Random Forest, Cat Boost, Decision tree and Isolation Forest algorithms were applied on the credit card dataset, and it was found that Random Forest algorithm was outperforming well comparing to other algorithms.
{"title":"Fraud Classification In Financial Statements Using Machine Learning Techniques","authors":"Abdulla Hussain Ali Mohamed, S. Subramanian","doi":"10.1109/ITIKD56332.2023.10100257","DOIUrl":"https://doi.org/10.1109/ITIKD56332.2023.10100257","url":null,"abstract":"With the blooming of technology, the financial sector has shown various number of improvements and has provided multiple e-financial services. Frauds can occur easily and quickly in data that lack safety levels. Although there are many laws that reduces the outcome of hacking, but unfortunately these laws cannot keep up with the enormous increase of hacking attacks level that are present. In this research, Bayes point machine, Random Forest, Cat Boost, Decision tree and Isolation Forest algorithms were applied on the credit card dataset, and it was found that Random Forest algorithm was outperforming well comparing to other algorithms.","PeriodicalId":283631,"journal":{"name":"2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116287752","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 : 2023-03-08DOI: 10.1109/ITIKD56332.2023.10099838
Noor Alsayed, W. Awad
Combining machine learning and labor market data is advantageous for jobseekers, companies, and decision-makers. Jobs in great demand in the future can be predicted using machine learning algorithms and data collected from the labor market. This study highlights the importance of labor market analysis and the economic impact of merging machine learning with labor market analysis as media impacts the labor market. This study presents a framework model recommended for analyzing online job postings and news to determine in-demand industries, occupations, and skills. The study indicates that the framework simulates labor market intelligence where results are more efficient and give a faster examination of labor market trends-utilizing the news offered reliable insight into forthcoming labor market trends.
{"title":"A framework for Labor Market Analysis using Machine Learning","authors":"Noor Alsayed, W. Awad","doi":"10.1109/ITIKD56332.2023.10099838","DOIUrl":"https://doi.org/10.1109/ITIKD56332.2023.10099838","url":null,"abstract":"Combining machine learning and labor market data is advantageous for jobseekers, companies, and decision-makers. Jobs in great demand in the future can be predicted using machine learning algorithms and data collected from the labor market. This study highlights the importance of labor market analysis and the economic impact of merging machine learning with labor market analysis as media impacts the labor market. This study presents a framework model recommended for analyzing online job postings and news to determine in-demand industries, occupations, and skills. The study indicates that the framework simulates labor market intelligence where results are more efficient and give a faster examination of labor market trends-utilizing the news offered reliable insight into forthcoming labor market trends.","PeriodicalId":283631,"journal":{"name":"2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125716048","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 : 2023-03-08DOI: 10.1109/ITIKD56332.2023.10099608
Husain Abdulla, Hamed S. Al-Raweshidy, W. Awad
The IoT has various applications in various industries, including logistics tracking, healthcare, automotive, and smart cities. To prepare for a future in which the IoT is everywhere and accessible from anywhere, it is more necessary than ever to address significant IoT security concerns. Traditional methods of securing IoT networks, which include applying security in the form of a “patch” against known vulnerabilities, are ineffective due to the growing scale of IoT networks, the characteristics of IoT devices, and the complexity of IoT networks. Machine Learning-based security systems and solutions have the potential to address the issues in traditional approaches to improve the security of the IoT Networks. In this paper, we show the existing challenges in securing IoT devices. We also explore the gaps in the research related to applying machine learning to securing IoT Devices. Through this research, we aim to encourage researchers to discover techniques to make the Internet of Things ecosystem safer.
{"title":"The Era of Internet of Things: Towards better security using machine learning","authors":"Husain Abdulla, Hamed S. Al-Raweshidy, W. Awad","doi":"10.1109/ITIKD56332.2023.10099608","DOIUrl":"https://doi.org/10.1109/ITIKD56332.2023.10099608","url":null,"abstract":"The IoT has various applications in various industries, including logistics tracking, healthcare, automotive, and smart cities. To prepare for a future in which the IoT is everywhere and accessible from anywhere, it is more necessary than ever to address significant IoT security concerns. Traditional methods of securing IoT networks, which include applying security in the form of a “patch” against known vulnerabilities, are ineffective due to the growing scale of IoT networks, the characteristics of IoT devices, and the complexity of IoT networks. Machine Learning-based security systems and solutions have the potential to address the issues in traditional approaches to improve the security of the IoT Networks. In this paper, we show the existing challenges in securing IoT devices. We also explore the gaps in the research related to applying machine learning to securing IoT Devices. Through this research, we aim to encourage researchers to discover techniques to make the Internet of Things ecosystem safer.","PeriodicalId":283631,"journal":{"name":"2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133763457","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 : 2023-03-08DOI: 10.1109/ITIKD56332.2023.10100329
Husain al Ansari, Fatema Alnasser
This research paper assesses the influence of knowledge sharing on reinforcing knowledge sharing in the context of AI in Bahrain. Since civic engagement is mainly made up of two components which are trust and value, the research seeks to examine the influence of knowledge sharing both on trust and value. The research is a quantitative one that makes use of the experimental design. The research makes use of the questionnaire as a research tool for collecting data. An experiment is applied on the sample of the research in which a chatbot is applied to examine university students' knowledge about using AI for the purpose of knowledge sharing especially through social media platforms. The questionnaire is applied in Pre-experiment stage and post-experiment. The population included 387university students. One hundred were required to complete it pre the experiment. The post-experiment stage 263responses were delivered. The data analysis made the researcher conclude that there is a significant difference toward the influence of knowledge sharing on Civic engagement in the kingdom of Bahrain attributed to the data collected pre and post the experiment. It was also concluded that the relationships between knowledge sharing and civic engagement, and between knowledge sharing and trust and values, indicate a conceptual framework which adds to the existing body of literature in this knowledge domain.
{"title":"The Role of Knowledge Sharing in Reinforcing Civic Engagement Practices in the context of Artificial Intelligence: The Case of the Kingdom of Bahrain","authors":"Husain al Ansari, Fatema Alnasser","doi":"10.1109/ITIKD56332.2023.10100329","DOIUrl":"https://doi.org/10.1109/ITIKD56332.2023.10100329","url":null,"abstract":"This research paper assesses the influence of knowledge sharing on reinforcing knowledge sharing in the context of AI in Bahrain. Since civic engagement is mainly made up of two components which are trust and value, the research seeks to examine the influence of knowledge sharing both on trust and value. The research is a quantitative one that makes use of the experimental design. The research makes use of the questionnaire as a research tool for collecting data. An experiment is applied on the sample of the research in which a chatbot is applied to examine university students' knowledge about using AI for the purpose of knowledge sharing especially through social media platforms. The questionnaire is applied in Pre-experiment stage and post-experiment. The population included 387university students. One hundred were required to complete it pre the experiment. The post-experiment stage 263responses were delivered. The data analysis made the researcher conclude that there is a significant difference toward the influence of knowledge sharing on Civic engagement in the kingdom of Bahrain attributed to the data collected pre and post the experiment. It was also concluded that the relationships between knowledge sharing and civic engagement, and between knowledge sharing and trust and values, indicate a conceptual framework which adds to the existing body of literature in this knowledge domain.","PeriodicalId":283631,"journal":{"name":"2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)","volume":"437 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123608895","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 : 2023-03-08DOI: 10.1109/ITIKD56332.2023.10099674
Eman H. Alkhammash
This paper proposes a new semantic framework for a job recommendation based on OWL ontology. The proposed framework will aid in the job search and recruitment process. The framework consists of a number of techniques: A web crawler is used to collect information from various web sites, the OWL job recommendation ontology provides a well-defined semantic model related to the job domain, SP ARQL constructs queries on OWL ontologies, EasyRDF allows sending SP ARQL queries to a third party server Virtuoso which will handle it and retrieve the results. The proposed framework recommends a suitable career opportunity for people based on their qualifications, skills, technological background, and so on. The OWL job recommendation ontology has been developed using Protégé 5.5.0 and the main components of the concepts and relations are discussed. The OWL ontology gives semantics to job information gathered from the web and enables more effective management, sharing, and recommendation of job information.
{"title":"Semantic-based Job Recommendation Framework Using OWL Ontology","authors":"Eman H. Alkhammash","doi":"10.1109/ITIKD56332.2023.10099674","DOIUrl":"https://doi.org/10.1109/ITIKD56332.2023.10099674","url":null,"abstract":"This paper proposes a new semantic framework for a job recommendation based on OWL ontology. The proposed framework will aid in the job search and recruitment process. The framework consists of a number of techniques: A web crawler is used to collect information from various web sites, the OWL job recommendation ontology provides a well-defined semantic model related to the job domain, SP ARQL constructs queries on OWL ontologies, EasyRDF allows sending SP ARQL queries to a third party server Virtuoso which will handle it and retrieve the results. The proposed framework recommends a suitable career opportunity for people based on their qualifications, skills, technological background, and so on. The OWL job recommendation ontology has been developed using Protégé 5.5.0 and the main components of the concepts and relations are discussed. The OWL ontology gives semantics to job information gathered from the web and enables more effective management, sharing, and recommendation of job information.","PeriodicalId":283631,"journal":{"name":"2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)","volume":"206 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132444341","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 : 2023-03-08DOI: 10.1109/ITIKD56332.2023.10099671
Moaiad Ahmed Khder, Samer Shorman, Ahmed Ali, Mohammed O. Al-Mudaifa
online games provide a competitive environment where most players compete and try to gain advantages by efficiently using game mechanics and resources provided by the gameplay loop. This competitive nature of online games sometimes goes above and beyond where some players resort to using unethical methods such as: Cheating, exploiting bugs and vulnerabilities which provide them with unfair advantages over most normal players. This results in normal players leaving the game as they lose the desire to continue playing in an unfair environment. Failure to combat such behaviour causes huge damage to the player base, game itself, company revenue and reputation. Persistent Massively Multiplayer Online Games can contain thousands of players sharing the same world view. the large number of updates performed each second has made storing the game state a big challenge, the game state should not be lost when a crash or failure to the server happen, commonly implemented solution fixes this problem by trading consistency with efficiency due to the database limited capability of handling large amount of data. This paper aims to shed a light on current popular user data storage methods, their vulnerabilities and propose a solution.. This paper aims to shed a light on current popular user data storage methods, their vulnerabilities and propose a solution
{"title":"Online Games Data Storing Methods, Vulnerabilities, and Solutions","authors":"Moaiad Ahmed Khder, Samer Shorman, Ahmed Ali, Mohammed O. Al-Mudaifa","doi":"10.1109/ITIKD56332.2023.10099671","DOIUrl":"https://doi.org/10.1109/ITIKD56332.2023.10099671","url":null,"abstract":"online games provide a competitive environment where most players compete and try to gain advantages by efficiently using game mechanics and resources provided by the gameplay loop. This competitive nature of online games sometimes goes above and beyond where some players resort to using unethical methods such as: Cheating, exploiting bugs and vulnerabilities which provide them with unfair advantages over most normal players. This results in normal players leaving the game as they lose the desire to continue playing in an unfair environment. Failure to combat such behaviour causes huge damage to the player base, game itself, company revenue and reputation. Persistent Massively Multiplayer Online Games can contain thousands of players sharing the same world view. the large number of updates performed each second has made storing the game state a big challenge, the game state should not be lost when a crash or failure to the server happen, commonly implemented solution fixes this problem by trading consistency with efficiency due to the database limited capability of handling large amount of data. This paper aims to shed a light on current popular user data storage methods, their vulnerabilities and propose a solution.. This paper aims to shed a light on current popular user data storage methods, their vulnerabilities and propose a solution","PeriodicalId":283631,"journal":{"name":"2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130263280","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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