Pub Date : 2019-12-01DOI: 10.1109/CSCI49370.2019.00014
Abdulwahab Alazeb, B. Panda
The evolution of the utilization of technologies in nearly all aspects of life has produced an enormous amount of data essential in a smart city. Therefore, maximizing the benefits of technologies such as cloud computing, fog computing, and the Internet of things is important to manage and manipulate data in smart cities. However, certain types of data are sensitive and risky and may be infiltrated by malicious attacks. As a result, such data may be corrupted, thereby causing concern. The damage inflicted by an attacker on a set of data can spread through an entire database. Valid transactions that have read corrupted data can update other data items based on the values read. In this study, we introduce a unique model that uses fog computing in smart cities to manage utility service companies and consumer data. We also propose a novel technique to assess damage to data caused by an attack. Thus, original data can be recovered, and a database can be returned to its consistent state as no attacking has occurred.
{"title":"Maintaining Data Integrity in Fog Computing Based Critical Infrastructure Systems","authors":"Abdulwahab Alazeb, B. Panda","doi":"10.1109/CSCI49370.2019.00014","DOIUrl":"https://doi.org/10.1109/CSCI49370.2019.00014","url":null,"abstract":"The evolution of the utilization of technologies in nearly all aspects of life has produced an enormous amount of data essential in a smart city. Therefore, maximizing the benefits of technologies such as cloud computing, fog computing, and the Internet of things is important to manage and manipulate data in smart cities. However, certain types of data are sensitive and risky and may be infiltrated by malicious attacks. As a result, such data may be corrupted, thereby causing concern. The damage inflicted by an attacker on a set of data can spread through an entire database. Valid transactions that have read corrupted data can update other data items based on the values read. In this study, we introduce a unique model that uses fog computing in smart cities to manage utility service companies and consumer data. We also propose a novel technique to assess damage to data caused by an attack. Thus, original data can be recovered, and a database can be returned to its consistent state as no attacking has occurred.","PeriodicalId":103662,"journal":{"name":"2019 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132764602","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 : 2019-12-01DOI: 10.1109/CSCI49370.2019.00264
Abeer Abdel Khaleq, Ilkyeun Ra
Cloud applications are becoming more containerized in nature. Developing a cloud application based on a microservice architecture imposes different challenges including scalability at the container level. What adds to the challenge is that applications have different QoS requirements and different characteristics requiring a customized scaling approach. In this paper, we present an agnostic approach algorithm for microservices autoscaling deployed on the Google Kubernetes Engine. Our algorithm adapts the Kubernetes autoscaling paradigm based on the application characteristics and resource requirements. Initial testing of the algorithm on different microservices requirements show an enhancement in the microservice response time up to 20% compared to the default autoscaling paradigm.
{"title":"Agnostic Approach for Microservices Autoscaling in Cloud Applications","authors":"Abeer Abdel Khaleq, Ilkyeun Ra","doi":"10.1109/CSCI49370.2019.00264","DOIUrl":"https://doi.org/10.1109/CSCI49370.2019.00264","url":null,"abstract":"Cloud applications are becoming more containerized in nature. Developing a cloud application based on a microservice architecture imposes different challenges including scalability at the container level. What adds to the challenge is that applications have different QoS requirements and different characteristics requiring a customized scaling approach. In this paper, we present an agnostic approach algorithm for microservices autoscaling deployed on the Google Kubernetes Engine. Our algorithm adapts the Kubernetes autoscaling paradigm based on the application characteristics and resource requirements. Initial testing of the algorithm on different microservices requirements show an enhancement in the microservice response time up to 20% compared to the default autoscaling paradigm.","PeriodicalId":103662,"journal":{"name":"2019 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"253 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132842326","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 : 2019-12-01DOI: 10.1109/CSCI49370.2019.00044
Tobias Eggendorfer, Volker Eiseler
Tactical Data Links (TDL) and Computer Science meet usually when it comes to interoperability andimplementation. However looking at it from an IT security perspective, some interesting issues occur. These become more relevant the more military hard-and software is built using commercial of the shelf (COTS) systems, that are usually implemented using standard Internet technology and software development patterns. This paper looks at Link 16, Link 11 and VMF security considerations and how compatible they are to current IT security standards. Typical security issues are discussed and concepts to mitigate them presented, which however need to be analysed for their suitability to TDL.
{"title":"On the Relevance of IT Security in TDL","authors":"Tobias Eggendorfer, Volker Eiseler","doi":"10.1109/CSCI49370.2019.00044","DOIUrl":"https://doi.org/10.1109/CSCI49370.2019.00044","url":null,"abstract":"Tactical Data Links (TDL) and Computer Science meet usually when it comes to interoperability andimplementation. However looking at it from an IT security perspective, some interesting issues occur. These become more relevant the more military hard-and software is built using commercial of the shelf (COTS) systems, that are usually implemented using standard Internet technology and software development patterns. This paper looks at Link 16, Link 11 and VMF security considerations and how compatible they are to current IT security standards. Typical security issues are discussed and concepts to mitigate them presented, which however need to be analysed for their suitability to TDL.","PeriodicalId":103662,"journal":{"name":"2019 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116987576","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 : 2019-12-01DOI: 10.1109/CSCI49370.2019.00238
Ananth N. Ramaseri Chandra, Fatima El Jamiy, H. Reza
Information delivery in a visual format is always a better way of communication. Even with many data visualization techniques available, visualizing enormous amounts of data has always been a challenge. With recent advancements in technology, many new visualization techniques unfold, one of which is visualizing data through Augmented reality(AR). AR and big data have always gone together as AR requires large data sets to render information virtually in a real-time environment, and big data provides the same. In this paper, we explore some of the conventional visualization techniques and discuss the scope and possibilities for AR data visualizations. We also explore the areas implementing the technique of visualizing big data with AR. The advantages and limitations are also discussed.
{"title":"Augmented Reality for Big Data Visualization: A Review","authors":"Ananth N. Ramaseri Chandra, Fatima El Jamiy, H. Reza","doi":"10.1109/CSCI49370.2019.00238","DOIUrl":"https://doi.org/10.1109/CSCI49370.2019.00238","url":null,"abstract":"Information delivery in a visual format is always a better way of communication. Even with many data visualization techniques available, visualizing enormous amounts of data has always been a challenge. With recent advancements in technology, many new visualization techniques unfold, one of which is visualizing data through Augmented reality(AR). AR and big data have always gone together as AR requires large data sets to render information virtually in a real-time environment, and big data provides the same. In this paper, we explore some of the conventional visualization techniques and discuss the scope and possibilities for AR data visualizations. We also explore the areas implementing the technique of visualizing big data with AR. The advantages and limitations are also discussed.","PeriodicalId":103662,"journal":{"name":"2019 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"267 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131157778","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 : 2019-12-01DOI: 10.1109/CSCI49370.2019.00158
C. V. Gonzalez, Gwang Jung
To handle cyber security threats, we need to develop courses to educate students about cyber security concepts, methods to handle various attacks in the cyber space. In this paper, we address what resources would be required to develop courses to effectively teach students the cyber security concepts and methods at small colleges or universities with limited resources.
{"title":"Teaching Cyber Security Topics Effectively in a College or University with Limited Resources","authors":"C. V. Gonzalez, Gwang Jung","doi":"10.1109/CSCI49370.2019.00158","DOIUrl":"https://doi.org/10.1109/CSCI49370.2019.00158","url":null,"abstract":"To handle cyber security threats, we need to develop courses to educate students about cyber security concepts, methods to handle various attacks in the cyber space. In this paper, we address what resources would be required to develop courses to effectively teach students the cyber security concepts and methods at small colleges or universities with limited resources.","PeriodicalId":103662,"journal":{"name":"2019 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131626956","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 : 2019-12-01DOI: 10.1109/CSCI49370.2019.00100
A. K. Panda, B. Kosko
A system of rules can approximate a trained neural classifier after sampling from that classifier. The rules define a generalized probability mixture that then describes the classifier. The size or granularity of the rule if-parts defines a foam-like structure with a few large rule if-part set bubbles in patternclass centers and many smaller if-part sets near class borders. The rule foam's mixture gives a Bayesian posterior over the rules. The posterior describes the relative importance of each rule for each observed input and output. The foam's mixture also gives the conditional variance that measures the uncertainty in its output. So the rule base is statistically interpretable as well as modular and adaptive. A rule foam with 1000 Gaussian rules approximated a 96.85% accurate MNIST neural classifier and had itself 95.66% classification accuracy. Foams can also approximate other foams. Some approximator foams out-performed the target foam that generated their training data. The rule foam's granularity mitigates the rule explosion inherent in the rule-based approximator's graph-covering structure
{"title":"Converting Neural Networks to Rule Foam","authors":"A. K. Panda, B. Kosko","doi":"10.1109/CSCI49370.2019.00100","DOIUrl":"https://doi.org/10.1109/CSCI49370.2019.00100","url":null,"abstract":"A system of rules can approximate a trained neural classifier after sampling from that classifier. The rules define a generalized probability mixture that then describes the classifier. The size or granularity of the rule if-parts defines a foam-like structure with a few large rule if-part set bubbles in patternclass centers and many smaller if-part sets near class borders. The rule foam's mixture gives a Bayesian posterior over the rules. The posterior describes the relative importance of each rule for each observed input and output. The foam's mixture also gives the conditional variance that measures the uncertainty in its output. So the rule base is statistically interpretable as well as modular and adaptive. A rule foam with 1000 Gaussian rules approximated a 96.85% accurate MNIST neural classifier and had itself 95.66% classification accuracy. Foams can also approximate other foams. Some approximator foams out-performed the target foam that generated their training data. The rule foam's granularity mitigates the rule explosion inherent in the rule-based approximator's graph-covering structure","PeriodicalId":103662,"journal":{"name":"2019 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134241878","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 : 2019-12-01DOI: 10.1109/CSCI49370.2019.00224
Ahlam Mallak, Akash Sonnad, M. Fathi
A Mobile Wireless Sensor Network (MWSN) is a network of mobile sensor nodes that are spatially separated in an open or closed space, which work altogether to sense various system environmental and physical parameters. The state-of-the art is full of approaches for modelling WSNs and MWSNs using different simulation tools and programming languages. Such models require the system expert interference to change the simulated model itself whenever any change is required. Without this interference or having knowledge of the simulated system, these models tend to generate fixed-case sensor data and lack the dynamicity and the ability for further user-specific changes at run-time. In this paper, a two-phase dynamic simulation toolbox -so-called 'SenGen'- is presented and tested, where a full simulation of an indoor MWSN system is established using Simulink. Then a Graphical User Interface (GUI) is created with MATLAB, to overall perform as a dynamic toolbox for sensor data generation in MWSNs.
{"title":"SenGen: A Two-Phase Dynamic Simulation and Toolbox of an Indoor Mobile Wireless Sensor Network for Sensor Monitoring and Dataset Generation","authors":"Ahlam Mallak, Akash Sonnad, M. Fathi","doi":"10.1109/CSCI49370.2019.00224","DOIUrl":"https://doi.org/10.1109/CSCI49370.2019.00224","url":null,"abstract":"A Mobile Wireless Sensor Network (MWSN) is a network of mobile sensor nodes that are spatially separated in an open or closed space, which work altogether to sense various system environmental and physical parameters. The state-of-the art is full of approaches for modelling WSNs and MWSNs using different simulation tools and programming languages. Such models require the system expert interference to change the simulated model itself whenever any change is required. Without this interference or having knowledge of the simulated system, these models tend to generate fixed-case sensor data and lack the dynamicity and the ability for further user-specific changes at run-time. In this paper, a two-phase dynamic simulation toolbox -so-called 'SenGen'- is presented and tested, where a full simulation of an indoor MWSN system is established using Simulink. Then a Graphical User Interface (GUI) is created with MATLAB, to overall perform as a dynamic toolbox for sensor data generation in MWSNs.","PeriodicalId":103662,"journal":{"name":"2019 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133957499","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 : 2019-12-01DOI: 10.1109/CSCI49370.2019.00185
Raksha Pahlad, B. Gatsheni
Leaders at company AB within different functional areas needed to effectively facilitate the integration of BI initiatives into business operations. Semi-structured interviews were used to extract key concepts and attributes relevant to business functional areas, from business leaders and these were related to BI techniques. Thematic analysis on collected data was used to identify critical success factors (CSFs). A conceptual framework was developed which comprises business CSFs that are related to opportunities for value derivation from BI activities. This framework can be used as a guideline by Company AB for opportunity assessment and BI implementation, thereby enabling Company AB to leverage the value of BI. A decision tree predictive analytics model whose business rules potentially assist in proactive churn management for companies that have customer transaction volumes as a feature, was developed. This analytics model shows that claims that are not submitted to a client's historically most frequently used medical aids and variances in transactional claim volumes of more than 20%, are good indicators of a client churn. Companies that provide value to the private healthcare industry via the facilitation and management of transactional data flows between healthcare providers and medical aid administrators will benefit from the insights derived from this model.
{"title":"A Framework for Leveraging Business Intelligence to Manage Transactional Data Flows between Private Healthcare Providers and Medical Aid Administrators","authors":"Raksha Pahlad, B. Gatsheni","doi":"10.1109/CSCI49370.2019.00185","DOIUrl":"https://doi.org/10.1109/CSCI49370.2019.00185","url":null,"abstract":"Leaders at company AB within different functional areas needed to effectively facilitate the integration of BI initiatives into business operations. Semi-structured interviews were used to extract key concepts and attributes relevant to business functional areas, from business leaders and these were related to BI techniques. Thematic analysis on collected data was used to identify critical success factors (CSFs). A conceptual framework was developed which comprises business CSFs that are related to opportunities for value derivation from BI activities. This framework can be used as a guideline by Company AB for opportunity assessment and BI implementation, thereby enabling Company AB to leverage the value of BI. A decision tree predictive analytics model whose business rules potentially assist in proactive churn management for companies that have customer transaction volumes as a feature, was developed. This analytics model shows that claims that are not submitted to a client's historically most frequently used medical aids and variances in transactional claim volumes of more than 20%, are good indicators of a client churn. Companies that provide value to the private healthcare industry via the facilitation and management of transactional data flows between healthcare providers and medical aid administrators will benefit from the insights derived from this model.","PeriodicalId":103662,"journal":{"name":"2019 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114076837","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 : 2019-12-01DOI: 10.1109/CSCI49370.2019.00141
Samuel Ndueso John, Etinosa Noma-Osaghae, K. Okokpujie, Chinonso Okereke, Joshua Ananaba, O. Omoruyi
Road crashes account for over a million deaths around the world every year. It is one of the leading causes of death for young people between the ages of fifteen and twenty-nine. Road accidents cause a whooping loss of up to three percent of the many nations' Gross Domestic Product (GDP) and ninety percent of these accidents occur in low to middle income countries with a sizable fifty-four percent share of the world's vehicular population. One of the Sustainable Development Goals (SDGs) is the reduction of road accidents around the world by half of its current value by 2020. This goal becomes a hit if low to medium-income nations get safer roads. This paper proposes a collision avoidance system that provides drivers with an automated preemptive response to impending car accidents with the aid of distance predictive analysis via sensors connected to the braking system of the vehicle, which in turn slows down the speed of the vehicle or completely stops it from moving altogether. The proposed collision avoidance system makes use of ultrasonic sensors and a unique localization algorithm to deliver a largely user-based vehicular protection from collision.
{"title":"Vehicle Collision Avoidance System Using Localization Algorithm and Predictive Analysis","authors":"Samuel Ndueso John, Etinosa Noma-Osaghae, K. Okokpujie, Chinonso Okereke, Joshua Ananaba, O. Omoruyi","doi":"10.1109/CSCI49370.2019.00141","DOIUrl":"https://doi.org/10.1109/CSCI49370.2019.00141","url":null,"abstract":"Road crashes account for over a million deaths around the world every year. It is one of the leading causes of death for young people between the ages of fifteen and twenty-nine. Road accidents cause a whooping loss of up to three percent of the many nations' Gross Domestic Product (GDP) and ninety percent of these accidents occur in low to middle income countries with a sizable fifty-four percent share of the world's vehicular population. One of the Sustainable Development Goals (SDGs) is the reduction of road accidents around the world by half of its current value by 2020. This goal becomes a hit if low to medium-income nations get safer roads. This paper proposes a collision avoidance system that provides drivers with an automated preemptive response to impending car accidents with the aid of distance predictive analysis via sensors connected to the braking system of the vehicle, which in turn slows down the speed of the vehicle or completely stops it from moving altogether. The proposed collision avoidance system makes use of ultrasonic sensors and a unique localization algorithm to deliver a largely user-based vehicular protection from collision.","PeriodicalId":103662,"journal":{"name":"2019 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122361852","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 : 2019-12-01DOI: 10.1109/CSCI49370.2019.00034
Zackary Foreman, Thomas Bekman, T. Augustine, H. Jafarian
Currently, the guidelines for business entities to collect and use consumer information from online sources is guided by the Fair Information Practice Principles set forth by the Federal Trade Commission in the United States. These guidelines are inadequate, outdated, and provide little protection for consumers. Moreover, there are many techniques to anonymize the stored data that was collected by large companies and governments. However, what does not exist is a framework that is capable of evaluating and scoring the effects of this information in the event of a data breach. In this work, a framework for scoring and evaluating the vulnerability of private data is presented. This framework is created to be used in parallel with currently adopted frameworks that are used to score and evaluate other areas of deficiencies within the software, including CVSS and CWSS. It is dubbed the Privacy Assessment Vulnerability Scoring System (PAVSS) and quantifies the privacy-breach vulnerability an individual takes on when using an online platform. This framework is based on a set of hypotheses about user behavior, inherent properties of an online platform, and the usefulness of available data in performing a cyber attack. The weight each of these metrics has within our model is determined by surveying cybersecurity experts. Finally, we test the validity of our user-behavior based hypotheses, and indirectly our model by analyzing user posts from a large twitter data set.
{"title":"PAVSS: Privacy Assessment Vulnerability Scoring System","authors":"Zackary Foreman, Thomas Bekman, T. Augustine, H. Jafarian","doi":"10.1109/CSCI49370.2019.00034","DOIUrl":"https://doi.org/10.1109/CSCI49370.2019.00034","url":null,"abstract":"Currently, the guidelines for business entities to collect and use consumer information from online sources is guided by the Fair Information Practice Principles set forth by the Federal Trade Commission in the United States. These guidelines are inadequate, outdated, and provide little protection for consumers. Moreover, there are many techniques to anonymize the stored data that was collected by large companies and governments. However, what does not exist is a framework that is capable of evaluating and scoring the effects of this information in the event of a data breach. In this work, a framework for scoring and evaluating the vulnerability of private data is presented. This framework is created to be used in parallel with currently adopted frameworks that are used to score and evaluate other areas of deficiencies within the software, including CVSS and CWSS. It is dubbed the Privacy Assessment Vulnerability Scoring System (PAVSS) and quantifies the privacy-breach vulnerability an individual takes on when using an online platform. This framework is based on a set of hypotheses about user behavior, inherent properties of an online platform, and the usefulness of available data in performing a cyber attack. The weight each of these metrics has within our model is determined by surveying cybersecurity experts. Finally, we test the validity of our user-behavior based hypotheses, and indirectly our model by analyzing user posts from a large twitter data set.","PeriodicalId":103662,"journal":{"name":"2019 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124087577","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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