M. Rozi, Y. G. Sucahyo, Arfive Gandhi, Y. Ruldeviyani
Financial Technology (fintech) has been immerged extensively in the last decade. In the realm of disruptive world, there are many areas in which startup companies are developing their business. There is always contradiction when dealing with innovation as core of digital disruption and how privacy remains as hot issues at the edge of everybody's talks. Internet plays important roles to sustain the trends. As rapidly growing country, 68% of Indonesian has access to the Internet. It drives startup companies on financial technology to innovate more and besides that they must comply to regulation in regard with personal data protection. This research aims to appraise how startup company on financial technology protect users' personal data. Personal data protection principles from international organization and Indonesian regulation regarding personal data protection are used to appraise how ABC Corp as a startup company that deliver financial technology service in Indonesian society. To ensure that its service is qualified and trustable, ABC Corp should be appraised using relevant criteria and qualitative approach. The results showed that most of regulations from sectorial supervising agency have been adhered by ABC Corp. The results bring meaningful insight to improve performance on personal data protection. They can became lessons for similar emerging startup companies in financial technology when acquiring their qualifications to protect users' personal data and keep their sustainability.
{"title":"Appraising Personal Data Protection in Startup Companies in Financial Technology: A Case Study of ABC Corp","authors":"M. Rozi, Y. G. Sucahyo, Arfive Gandhi, Y. Ruldeviyani","doi":"10.1145/3379310.3379322","DOIUrl":"https://doi.org/10.1145/3379310.3379322","url":null,"abstract":"Financial Technology (fintech) has been immerged extensively in the last decade. In the realm of disruptive world, there are many areas in which startup companies are developing their business. There is always contradiction when dealing with innovation as core of digital disruption and how privacy remains as hot issues at the edge of everybody's talks. Internet plays important roles to sustain the trends. As rapidly growing country, 68% of Indonesian has access to the Internet. It drives startup companies on financial technology to innovate more and besides that they must comply to regulation in regard with personal data protection. This research aims to appraise how startup company on financial technology protect users' personal data. Personal data protection principles from international organization and Indonesian regulation regarding personal data protection are used to appraise how ABC Corp as a startup company that deliver financial technology service in Indonesian society. To ensure that its service is qualified and trustable, ABC Corp should be appraised using relevant criteria and qualitative approach. The results showed that most of regulations from sectorial supervising agency have been adhered by ABC Corp. The results bring meaningful insight to improve performance on personal data protection. They can became lessons for similar emerging startup companies in financial technology when acquiring their qualifications to protect users' personal data and keep their sustainability.","PeriodicalId":348326,"journal":{"name":"Proceedings of the 2020 2nd Asia Pacific Information Technology Conference","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121661813","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}
A Fast Particle Swarm Optimization (FPSO) is proposed to improve the convergence response speed for some potential application scenarios such as the online or dynamical optimization environment which requires the fast convergence ability of an optimizer. Classical gradient-based optimization methods are good at finding the local optimal value of a convex region yet usually failure in searching the global optimal value of a multimodal problem. To further develop the characteristics of PSO with respect to the fast convergence and the global optimization, a pseudo-gradient method is proposed for calculating the approximate gradient at the location of the global best solution (gBest) of a swarm to refine the convergence accuracy of the gBest so as to accelerate the local convergence speed. The experimental results show that the performance of the proposed algorithm is significantly better than those of the five chosen competitive algorithms on a series of benchmark test functions with different characteristics. Furthermore, the sensitivity of the new introduced parameter in the proposed algorithm is empirically analyzed by a special experiment for recommending its best range of value.
{"title":"A Fast Particle Swarm Optimization Algorithm by Refining the Global Best Solution","authors":"Wang Hu, Yu Zhang, Junjie Hu, Yan Qi, Guoming Lu","doi":"10.1145/3379310.3379328","DOIUrl":"https://doi.org/10.1145/3379310.3379328","url":null,"abstract":"A Fast Particle Swarm Optimization (FPSO) is proposed to improve the convergence response speed for some potential application scenarios such as the online or dynamical optimization environment which requires the fast convergence ability of an optimizer. Classical gradient-based optimization methods are good at finding the local optimal value of a convex region yet usually failure in searching the global optimal value of a multimodal problem. To further develop the characteristics of PSO with respect to the fast convergence and the global optimization, a pseudo-gradient method is proposed for calculating the approximate gradient at the location of the global best solution (gBest) of a swarm to refine the convergence accuracy of the gBest so as to accelerate the local convergence speed. The experimental results show that the performance of the proposed algorithm is significantly better than those of the five chosen competitive algorithms on a series of benchmark test functions with different characteristics. Furthermore, the sensitivity of the new introduced parameter in the proposed algorithm is empirically analyzed by a special experiment for recommending its best range of value.","PeriodicalId":348326,"journal":{"name":"Proceedings of the 2020 2nd Asia Pacific Information Technology Conference","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128076352","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}
Justin Daniel G. Baugbog, Mhir John Paul Manalo, Jose Mari M. Salonga, Elizabeth P. Naval, Eugenia R. Zhuo
Nowadays the percentage of old aged people that have Alzheimer's disease has increased over the years. Alzheimer's disease is one of the most crucial diseases that our loved ones might acquire. In this study, a device for patients with Alzheimer's disease and a mobile application for the guardian/s to lessen their stress and worries when taking care of the patient were developed. It is called Patient Security & Supervision Equipment(PS & SE), which has a 3-layer security, mainly: [1] The door alert that is equipped with modules like UHF RFID reader which is used as an identifier for the patient, and an activator for the PIR sensor, a motion detector and, a Wi-Fi module for the connection of the door alert to send notifications to the mobile application; [2] The wearable device that is equipped with modules, such as a GPS tracker to know the location of the patient, a GSM module used by the GPS module in sending coordinates to the Firebase database, and a UHF RFID tag. [3] Lastly, the mobile application, named as PSSE, is used by the guardian/s to check the location of the patient. Passcode security is required before accessing the application. Based on a series of testing, the device's accuracy and efficiency for locating the patient depend on the signal/speed of the internet on a certain location. Hence, the system is said to be viable and feasible in the medial industry for its application of Alzheimer's patients and the other mentally challenged patients after the evaluation and validation of a specialist doctor.
{"title":"Wearable Device Equipped with Door Alert and Mobile App for Security and Supervision","authors":"Justin Daniel G. Baugbog, Mhir John Paul Manalo, Jose Mari M. Salonga, Elizabeth P. Naval, Eugenia R. Zhuo","doi":"10.1145/3379310.3379314","DOIUrl":"https://doi.org/10.1145/3379310.3379314","url":null,"abstract":"Nowadays the percentage of old aged people that have Alzheimer's disease has increased over the years. Alzheimer's disease is one of the most crucial diseases that our loved ones might acquire. In this study, a device for patients with Alzheimer's disease and a mobile application for the guardian/s to lessen their stress and worries when taking care of the patient were developed. It is called Patient Security & Supervision Equipment(PS & SE), which has a 3-layer security, mainly: [1] The door alert that is equipped with modules like UHF RFID reader which is used as an identifier for the patient, and an activator for the PIR sensor, a motion detector and, a Wi-Fi module for the connection of the door alert to send notifications to the mobile application; [2] The wearable device that is equipped with modules, such as a GPS tracker to know the location of the patient, a GSM module used by the GPS module in sending coordinates to the Firebase database, and a UHF RFID tag. [3] Lastly, the mobile application, named as PSSE, is used by the guardian/s to check the location of the patient. Passcode security is required before accessing the application. Based on a series of testing, the device's accuracy and efficiency for locating the patient depend on the signal/speed of the internet on a certain location. Hence, the system is said to be viable and feasible in the medial industry for its application of Alzheimer's patients and the other mentally challenged patients after the evaluation and validation of a specialist doctor.","PeriodicalId":348326,"journal":{"name":"Proceedings of the 2020 2nd Asia Pacific Information Technology Conference","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130027312","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}
Patient data archiving in a medical institution is a relatively critical asset. If the data are managed by irresponsible parties, it will be risky both for the patients and the institutions. Therefore, data securing of patients are required to prevent negative impacts. The method in this study uses a prototype cycle, in making patient registration applications online. The technique used in this study is a combination of MD5 and SHA256 to be optimized for the data sent from database to the users, so that the encryption results in concise filing and timing.
{"title":"Data Securing of Patients in Cloud Computing Using A Combination of SHA256 and MD5","authors":"D. Jatikusumo, Ida Nurhaida","doi":"10.1145/3379310.3381043","DOIUrl":"https://doi.org/10.1145/3379310.3381043","url":null,"abstract":"Patient data archiving in a medical institution is a relatively critical asset. If the data are managed by irresponsible parties, it will be risky both for the patients and the institutions. Therefore, data securing of patients are required to prevent negative impacts. The method in this study uses a prototype cycle, in making patient registration applications online. The technique used in this study is a combination of MD5 and SHA256 to be optimized for the data sent from database to the users, so that the encryption results in concise filing and timing.","PeriodicalId":348326,"journal":{"name":"Proceedings of the 2020 2nd Asia Pacific Information Technology Conference","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134110227","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}
Tommy Wijaya Sagala, M. Saputri, Rahmad Mahendra, I. Budi
This study aims to predict stock price movement using combination of technical analysis and sentiment analysis. When conducting stock transactions, the traders consider not only market activities but also the sentiments expressed within information reported in media. We build the classifier to categorize the price quotes into one of three classes: "up", "down", and "constant". We conduct the experiment with several algorithms, i.e. Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Naïve Bayes. The results of our empirical study is that the highest accuracy achieved from the method combining features from historical data and online media sentiment, on 5 days trading window using the SVM algorithm.
{"title":"Stock Price Movement Prediction Using Technical Analysis and Sentiment Analysis","authors":"Tommy Wijaya Sagala, M. Saputri, Rahmad Mahendra, I. Budi","doi":"10.1145/3379310.3381045","DOIUrl":"https://doi.org/10.1145/3379310.3381045","url":null,"abstract":"This study aims to predict stock price movement using combination of technical analysis and sentiment analysis. When conducting stock transactions, the traders consider not only market activities but also the sentiments expressed within information reported in media. We build the classifier to categorize the price quotes into one of three classes: \"up\", \"down\", and \"constant\". We conduct the experiment with several algorithms, i.e. Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Naïve Bayes. The results of our empirical study is that the highest accuracy achieved from the method combining features from historical data and online media sentiment, on 5 days trading window using the SVM algorithm.","PeriodicalId":348326,"journal":{"name":"Proceedings of the 2020 2nd Asia Pacific Information Technology Conference","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134267511","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}
The purpose of this research is to develop a disaster location detector application, specifically about flood that happens in the area of Jakarta, Indonesia. According to social media data updated by the users of twitter, search inquiry is done by its users with the keyword 'seputaran banjir' (in Bahasa Indonesia) which is combined with the Location Based Service function of the determined word search. The method in creating this application is Extreme Programming that uses repetitive and incremental development process approach. By using twitter status data about Jakarta's area, this application has been successfully developed and the result can be shown in the form of twitter status updates from its users that contain words about flood. The search results of flood location validation are coordinates, which are done by checking the availability of the geospatial information from each update of the data. The average accuracy of the search result is 83.7% out of all the location search results.
{"title":"D-Loc Apps: A Location Detection Application Based on Social Media Platform in the Event of A Flood Disaster","authors":"D. Fitrianah, D. Jatikusumo, Ida Nurhaida","doi":"10.1145/3379310.3381041","DOIUrl":"https://doi.org/10.1145/3379310.3381041","url":null,"abstract":"The purpose of this research is to develop a disaster location detector application, specifically about flood that happens in the area of Jakarta, Indonesia. According to social media data updated by the users of twitter, search inquiry is done by its users with the keyword 'seputaran banjir' (in Bahasa Indonesia) which is combined with the Location Based Service function of the determined word search. The method in creating this application is Extreme Programming that uses repetitive and incremental development process approach. By using twitter status data about Jakarta's area, this application has been successfully developed and the result can be shown in the form of twitter status updates from its users that contain words about flood. The search results of flood location validation are coordinates, which are done by checking the availability of the geospatial information from each update of the data. The average accuracy of the search result is 83.7% out of all the location search results.","PeriodicalId":348326,"journal":{"name":"Proceedings of the 2020 2nd Asia Pacific Information Technology Conference","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114615250","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}
Mining social media is the process of defining, analyzing, and extracting applicative patterns and trends from row social media data. Social media are very popular way of expressing opinions and interacting with many individual in the online world. However growing number of social network delusion among various age categories are recently noted. Mental sickness can have a deep influence on person, families, and society as well. Hence, we propose a framework that analyzes Social Network Delusion (SND) and investigates the addiction ratio. This work first defines the framework for analyzing the social network delusion based on mining online social behavior that provides an early stage opportunity to identify SNDs (Social Network Delusion). The proposed system mainly works in three phases. Feature extraction and analysis of the various posts posted by the users on Facebook, Instagram and Twitter is performed by using mining algorithm in the first step. The SND prediction using the extracted features is done in the second phase; Third phase uses the predicted results as an input for investigating the addiction ratio. We investigate the addiction ratio among different genders and age groups for analyzing the prevention strategies against growing number of SND.
{"title":"Identifying Social Network Delusion to Investigate Addiction Ratio using Data Mining","authors":"K. Thakre, Deepali Dawande, Vaidehi S. Thakre","doi":"10.1145/3379310.3379321","DOIUrl":"https://doi.org/10.1145/3379310.3379321","url":null,"abstract":"Mining social media is the process of defining, analyzing, and extracting applicative patterns and trends from row social media data. Social media are very popular way of expressing opinions and interacting with many individual in the online world. However growing number of social network delusion among various age categories are recently noted. Mental sickness can have a deep influence on person, families, and society as well. Hence, we propose a framework that analyzes Social Network Delusion (SND) and investigates the addiction ratio. This work first defines the framework for analyzing the social network delusion based on mining online social behavior that provides an early stage opportunity to identify SNDs (Social Network Delusion). The proposed system mainly works in three phases. Feature extraction and analysis of the various posts posted by the users on Facebook, Instagram and Twitter is performed by using mining algorithm in the first step. The SND prediction using the extracted features is done in the second phase; Third phase uses the predicted results as an input for investigating the addiction ratio. We investigate the addiction ratio among different genders and age groups for analyzing the prevention strategies against growing number of SND.","PeriodicalId":348326,"journal":{"name":"Proceedings of the 2020 2nd Asia Pacific Information Technology Conference","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128908112","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}
Ismail Parewai, M. As, Tsunenori Mine, Mario Koeppen
?Food quality inspection is an essential factor in our daily lives. Food inspection is analyzing heterogeneous food data from different sources for perception, recognition, judgment, and monitoring. This study aims to provide an accurate system in image processing techniques for the inspection and classification of sashimi food damage based on detecting external data. The external texture was identified based on the visible and invisible system that was acquired using multispectral technology. We proposed the Grey Level Co-occurrence Matrix (GLCM) model for analysis of the texture features of images and the classification process was performed using Artificial Neural Network (ANN) method. This study showed that multispectral technology is a useful system for the assessment of sashimi food and the experimental also indicates that the invisible channels have the potential in the classification model, since the hidden texture features that are not clearly visible to the human eye.
{"title":"Identification and Classification of Sashimi Food Using Multispectral Technology","authors":"Ismail Parewai, M. As, Tsunenori Mine, Mario Koeppen","doi":"10.1145/3379310.3379317","DOIUrl":"https://doi.org/10.1145/3379310.3379317","url":null,"abstract":"?Food quality inspection is an essential factor in our daily lives. Food inspection is analyzing heterogeneous food data from different sources for perception, recognition, judgment, and monitoring. This study aims to provide an accurate system in image processing techniques for the inspection and classification of sashimi food damage based on detecting external data. The external texture was identified based on the visible and invisible system that was acquired using multispectral technology. We proposed the Grey Level Co-occurrence Matrix (GLCM) model for analysis of the texture features of images and the classification process was performed using Artificial Neural Network (ANN) method. This study showed that multispectral technology is a useful system for the assessment of sashimi food and the experimental also indicates that the invisible channels have the potential in the classification model, since the hidden texture features that are not clearly visible to the human eye.","PeriodicalId":348326,"journal":{"name":"Proceedings of the 2020 2nd Asia Pacific Information Technology Conference","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130561663","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}
Lecturers in Indonesia have a fundamental obligation to conduct Tri Dharma activities consisting of teaching, research and community service. Most higher education institutions use Tri Dharma as a measure of lecturer's performance. In addition, lecturer activity data related to Tri Dharma is needed by the head of study program and department related to research, publication and community service to be stored which will be used as a source of data during the accreditation process. This paper discusses the application development of lecturer performance reports using the Model View Controller (MVC) architecture with Java programming language. The result is a desktop-based application that will be used by the head of the study program and the lecturers.
{"title":"Application of Lecturer Performance Report in Indonesia with Model View Controller (MVC) Architecture","authors":"Ester Lumba, Alexander Waworuntu","doi":"10.1145/3379310.3379320","DOIUrl":"https://doi.org/10.1145/3379310.3379320","url":null,"abstract":"Lecturers in Indonesia have a fundamental obligation to conduct Tri Dharma activities consisting of teaching, research and community service. Most higher education institutions use Tri Dharma as a measure of lecturer's performance. In addition, lecturer activity data related to Tri Dharma is needed by the head of study program and department related to research, publication and community service to be stored which will be used as a source of data during the accreditation process. This paper discusses the application development of lecturer performance reports using the Model View Controller (MVC) architecture with Java programming language. The result is a desktop-based application that will be used by the head of the study program and the lecturers.","PeriodicalId":348326,"journal":{"name":"Proceedings of the 2020 2nd Asia Pacific Information Technology Conference","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130795340","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}
Cryptojacking is the act of using an individual's or an organization's computational power in order to mine cryptocurrency. In some scenarios, this can be considered as a monetization strategy, very much similar to advertisements. But to do so without the explicit consent of the computer owners is considered illegitimate. During previous years, attackers' focus was heavily laid on browser-based cryptojacking. However, it was noted that the attackers are now shifting their attention to more robust, more superior targets, such as cloud servers and cloud infrastructure. This paper analyses 11 forms of practical scenarios of cryptojacking attacks that are targeted towards cloud infrastructure. We carefully look at their similarities and properties, comparing those features with the limitations of existing literature regarding the detection systems. In this paper, we survey the attack forms, and we also survey the limitations of existing literature as an attempt to outline the research gap between the practical scenarios and existing work.
{"title":"A Survey of Attack Instances of Cryptojacking Targeting Cloud Infrastructure","authors":"K.P.K.C. Jayasinghe, Guhanathan Poravi","doi":"10.1145/3379310.3379323","DOIUrl":"https://doi.org/10.1145/3379310.3379323","url":null,"abstract":"Cryptojacking is the act of using an individual's or an organization's computational power in order to mine cryptocurrency. In some scenarios, this can be considered as a monetization strategy, very much similar to advertisements. But to do so without the explicit consent of the computer owners is considered illegitimate. During previous years, attackers' focus was heavily laid on browser-based cryptojacking. However, it was noted that the attackers are now shifting their attention to more robust, more superior targets, such as cloud servers and cloud infrastructure. This paper analyses 11 forms of practical scenarios of cryptojacking attacks that are targeted towards cloud infrastructure. We carefully look at their similarities and properties, comparing those features with the limitations of existing literature regarding the detection systems. In this paper, we survey the attack forms, and we also survey the limitations of existing literature as an attempt to outline the research gap between the practical scenarios and existing work.","PeriodicalId":348326,"journal":{"name":"Proceedings of the 2020 2nd Asia Pacific Information Technology Conference","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126744332","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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