Pub Date : 2020-11-06DOI: 10.1109/PDGC50313.2020.9315810
M. Rashid, Harjeet Singh, Vishal Goyal
Functional Magnetic Resonance Imaging (fMRI) researchers are currently using various techniques for analyzing the cognitive states in brain images. Every time, it remains a challenge for such researchers to decode the brain information about stimuli affecting the related Region of Interest (ROI) from voxels of Brain Networks. In this paper, the authors used OpenCV library of Python to analyze various states of brain images. The images of each volume in the dataset are grouped into principal planes of fMRI views. Then operations of Dilation, Erosion, and Gaussian Blur are applied to all images for smoothening purposes. The authors believe that the procedure followed in this paper will be the optimal method for extracting brain images' features, which will improve the classification accuracy of the decoding of brain images in a much better way.
{"title":"Analyzing Functional Magnetic Resonance Brain Images with OpenCV2","authors":"M. Rashid, Harjeet Singh, Vishal Goyal","doi":"10.1109/PDGC50313.2020.9315810","DOIUrl":"https://doi.org/10.1109/PDGC50313.2020.9315810","url":null,"abstract":"Functional Magnetic Resonance Imaging (fMRI) researchers are currently using various techniques for analyzing the cognitive states in brain images. Every time, it remains a challenge for such researchers to decode the brain information about stimuli affecting the related Region of Interest (ROI) from voxels of Brain Networks. In this paper, the authors used OpenCV library of Python to analyze various states of brain images. The images of each volume in the dataset are grouped into principal planes of fMRI views. Then operations of Dilation, Erosion, and Gaussian Blur are applied to all images for smoothening purposes. The authors believe that the procedure followed in this paper will be the optimal method for extracting brain images' features, which will improve the classification accuracy of the decoding of brain images in a much better way.","PeriodicalId":347216,"journal":{"name":"2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125030873","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 : 2020-11-06DOI: 10.1109/PDGC50313.2020.9315785
S. Batra, Madhu Gupta, Jessica Singh, Devshri Srivastava, Isha Aggarwal
In this modern era of technology, the world is heavily dependent on technology no matter where one goes. Due to our heavy dependency on technology criminals have taken this advantage for their benefit. Cybercrime is quickly becoming one of the fastest rising forms of modern crimes. Cybercrime are well known for the downfall of so many companies, organizations and personal identities. The main intent of this paper is to define cybercrime, various types of cybercriminals and cybercrime affecting the world and its prevention. This paper will also analyse statistical data on various types of cybercrime and its growth in last few years.
{"title":"An Empirical Study of Cybercrime and Its Preventions","authors":"S. Batra, Madhu Gupta, Jessica Singh, Devshri Srivastava, Isha Aggarwal","doi":"10.1109/PDGC50313.2020.9315785","DOIUrl":"https://doi.org/10.1109/PDGC50313.2020.9315785","url":null,"abstract":"In this modern era of technology, the world is heavily dependent on technology no matter where one goes. Due to our heavy dependency on technology criminals have taken this advantage for their benefit. Cybercrime is quickly becoming one of the fastest rising forms of modern crimes. Cybercrime are well known for the downfall of so many companies, organizations and personal identities. The main intent of this paper is to define cybercrime, various types of cybercriminals and cybercrime affecting the world and its prevention. This paper will also analyse statistical data on various types of cybercrime and its growth in last few years.","PeriodicalId":347216,"journal":{"name":"2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130552659","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 : 2020-11-06DOI: 10.1109/PDGC50313.2020.9315825
Shakti Nagpal, V. Athavale, A. Saini, Ravindra Sharma
Global research team has announced that the health a management system at world level is in fear from CoV-19. Various statistical analysis has been done to check the preparedness to fight against CoV-19. Recent government responses of the different countries are also taken into the consideration while working for CoV-19 handling. Demographic trends are also added to add further content to potential impact of CoV-19 on healthcare services and system. This pandemic has raised a significant challenge to the economy of the different countries. Availability of beds are calculated on Per thousand people in different countries. Few of the countries analysis like Australia is having 2.6 beds per thousand people, while United Kingdom America is having 2.5 beds preparation over 1000 people. Per capita health spending in UK is marginally below the median. Hospital have been urged by government of different countries to postpone their surgeries and other treatments to provide the proper hospitality to cov-19 patients. India is at 145th place among 195 countries in healthcare access and Quality Index (HAQ)[1]. In this paper we have proposed a machine Learning model to predict the number of beds required as Cov-19 cases are increasing. Our Model Predicts the requirement for beds with 95% accuracy and acceptable p-value.
{"title":"Indian Health Care System is Ready to Fight Against COVID-19 A Machine Learning Tool for Forecast the Number of Beds","authors":"Shakti Nagpal, V. Athavale, A. Saini, Ravindra Sharma","doi":"10.1109/PDGC50313.2020.9315825","DOIUrl":"https://doi.org/10.1109/PDGC50313.2020.9315825","url":null,"abstract":"Global research team has announced that the health a management system at world level is in fear from CoV-19. Various statistical analysis has been done to check the preparedness to fight against CoV-19. Recent government responses of the different countries are also taken into the consideration while working for CoV-19 handling. Demographic trends are also added to add further content to potential impact of CoV-19 on healthcare services and system. This pandemic has raised a significant challenge to the economy of the different countries. Availability of beds are calculated on Per thousand people in different countries. Few of the countries analysis like Australia is having 2.6 beds per thousand people, while United Kingdom America is having 2.5 beds preparation over 1000 people. Per capita health spending in UK is marginally below the median. Hospital have been urged by government of different countries to postpone their surgeries and other treatments to provide the proper hospitality to cov-19 patients. India is at 145th place among 195 countries in healthcare access and Quality Index (HAQ)[1]. In this paper we have proposed a machine Learning model to predict the number of beds required as Cov-19 cases are increasing. Our Model Predicts the requirement for beds with 95% accuracy and acceptable p-value.","PeriodicalId":347216,"journal":{"name":"2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132860063","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 : 2020-11-06DOI: 10.1109/PDGC50313.2020.9315325
M. Shukla, Ashwani Kumar Dubey, Divya Upadhyay, Boris Novikov
Cloud provides a low maintenance and affordable storage to various applications and users. The data owner allows the cloud users to access the documents placed in the cloud service provider based on the user's access control vector provided to the cloud users by the data owners. In such type of scenarios, the confidentiality of the documents exchanged between the cloud service provider and the users should be maintained. The existing approaches used to provide this facility are not computation and communication efficient for performing key updating in the data owner side and the key recovery in the user side. This paper discusses the key management services provided to the cloud users. Remote key management and client-side key management are two approaches used by cloud servers. This paper also aims to discuss the method for destroying the encryption/decryption group keys for shared data to securing the data after deletion. Crypto Shredding or Crypto Throw technique is deployed for the same.
{"title":"Group Key Management in Cloud for Shared Media Sanitization","authors":"M. Shukla, Ashwani Kumar Dubey, Divya Upadhyay, Boris Novikov","doi":"10.1109/PDGC50313.2020.9315325","DOIUrl":"https://doi.org/10.1109/PDGC50313.2020.9315325","url":null,"abstract":"Cloud provides a low maintenance and affordable storage to various applications and users. The data owner allows the cloud users to access the documents placed in the cloud service provider based on the user's access control vector provided to the cloud users by the data owners. In such type of scenarios, the confidentiality of the documents exchanged between the cloud service provider and the users should be maintained. The existing approaches used to provide this facility are not computation and communication efficient for performing key updating in the data owner side and the key recovery in the user side. This paper discusses the key management services provided to the cloud users. Remote key management and client-side key management are two approaches used by cloud servers. This paper also aims to discuss the method for destroying the encryption/decryption group keys for shared data to securing the data after deletion. Crypto Shredding or Crypto Throw technique is deployed for the same.","PeriodicalId":347216,"journal":{"name":"2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132259234","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 : 2020-11-06DOI: 10.1109/PDGC50313.2020.9315764
Y. Supriya, G. Kumar, Dammu Sowjanya, D. Yadav, Devarakonda Lakshmi Kameshwari
Malware is derived from malicious software which mitigate to attacks on the computer systems and collecting private data. The survey is available in huge evidences to suggest its impact in global losses. Malware detectors are basic tools to protect from the same malware attacks. Therefore, it is important to require study on malware detection techniques, to avoid and identify the type of malware attacked on systems. In this manuscript, a survey report is available to defend against malware attacks and analysis techniques. There are many malware detection techniques, such as signature and anomaly detection techniques with an idea of comparison and decision making about its strengths. This provides as a user reference to the end user for likely detailed information.
{"title":"Malware Detection Techniques: A Survey","authors":"Y. Supriya, G. Kumar, Dammu Sowjanya, D. Yadav, Devarakonda Lakshmi Kameshwari","doi":"10.1109/PDGC50313.2020.9315764","DOIUrl":"https://doi.org/10.1109/PDGC50313.2020.9315764","url":null,"abstract":"Malware is derived from malicious software which mitigate to attacks on the computer systems and collecting private data. The survey is available in huge evidences to suggest its impact in global losses. Malware detectors are basic tools to protect from the same malware attacks. Therefore, it is important to require study on malware detection techniques, to avoid and identify the type of malware attacked on systems. In this manuscript, a survey report is available to defend against malware attacks and analysis techniques. There are many malware detection techniques, such as signature and anomaly detection techniques with an idea of comparison and decision making about its strengths. This provides as a user reference to the end user for likely detailed information.","PeriodicalId":347216,"journal":{"name":"2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133577503","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 : 2020-11-06DOI: 10.1109/PDGC50313.2020.9315773
Swati Sharma, Aryaman Sharma
The pandemic has hit the individuals at both personal, social and professional front triggering emotional crisis leading to stress, anxiety and other related problems. However, some countries are now easing down on restrictions by going from lock down to unlocking in a phased manner. As life springs back to action the sentiments and emotions of people are bound to change. It therefore becomes imperative to understand the emotions and sentiments of people after seven months of outbreak when the people are more informed about the nature of disease, steps for prevention and also have hope for a vaccine coming up in near future. The study analyses the sentiments of the people from the USA and India by text mining using R Studio. The study has various implications for academicians as it adds to the existing knowledge pool. The findings provide guidance to the policy makers to tailor their support policies in response to the emotional state of their people and also assists the marketers to tailor the communication strategies in the light of the emotional state of the target market.
{"title":"Twitter Sentiment Analysis During Unlock Period of COVID-19","authors":"Swati Sharma, Aryaman Sharma","doi":"10.1109/PDGC50313.2020.9315773","DOIUrl":"https://doi.org/10.1109/PDGC50313.2020.9315773","url":null,"abstract":"The pandemic has hit the individuals at both personal, social and professional front triggering emotional crisis leading to stress, anxiety and other related problems. However, some countries are now easing down on restrictions by going from lock down to unlocking in a phased manner. As life springs back to action the sentiments and emotions of people are bound to change. It therefore becomes imperative to understand the emotions and sentiments of people after seven months of outbreak when the people are more informed about the nature of disease, steps for prevention and also have hope for a vaccine coming up in near future. The study analyses the sentiments of the people from the USA and India by text mining using R Studio. The study has various implications for academicians as it adds to the existing knowledge pool. The findings provide guidance to the policy makers to tailor their support policies in response to the emotional state of their people and also assists the marketers to tailor the communication strategies in the light of the emotional state of the target market.","PeriodicalId":347216,"journal":{"name":"2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC)","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115008921","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 : 2020-11-06DOI: 10.1109/PDGC50313.2020.9315835
N. Kaur, H. Aggarwal
Retrieval of the semantic data becomes a time consuming and a highly tedious task. Ontology plays a maj or role in the retrieval of semantic data. In this paper the researcher has presented the methodology of music domain ontology construction using protegé 5.0 which is the best and the most commonly used Editor, intended to enhance information retrieval. The researcher has developed the string_ ontology in music domain using protege 5.0 and the working of ontology has been tested using the Descriptive Logic ontology query language. The novelty of this paper is that the researcher has constructed this string ontology in music domain from scratch and no such ontology has been constructed earlier.
{"title":"Semantic Information Retrieval using String Ontology in Music Domain using Protege5.0","authors":"N. Kaur, H. Aggarwal","doi":"10.1109/PDGC50313.2020.9315835","DOIUrl":"https://doi.org/10.1109/PDGC50313.2020.9315835","url":null,"abstract":"Retrieval of the semantic data becomes a time consuming and a highly tedious task. Ontology plays a maj or role in the retrieval of semantic data. In this paper the researcher has presented the methodology of music domain ontology construction using protegé 5.0 which is the best and the most commonly used Editor, intended to enhance information retrieval. The researcher has developed the string_ ontology in music domain using protege 5.0 and the working of ontology has been tested using the Descriptive Logic ontology query language. The novelty of this paper is that the researcher has constructed this string ontology in music domain from scratch and no such ontology has been constructed earlier.","PeriodicalId":347216,"journal":{"name":"2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC)","volume":"8 Suppl A 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116821070","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 : 2020-11-06DOI: 10.1109/PDGC50313.2020.9315840
V. Aski, V. Dhaka, Sunil Kumar, Anubha Parashar, Akshata Ladagi
The recent advancements in ubiquitous sensing powered by Wireless Computing Technologies (WCT) and Cloud Computing Services (CCS) have introduced a new thinking ability amongst researchers and healthcare professionals for building secure and connected healthcare systems. The integration of Internet of Things (IoT) in healthcare services further brings in several challenges with it, mainly including encrypted communication through vulnerable wireless medium, authentication and access control algorithms and ownership transfer schemes (important patient information). Major concern of such giant connected systems lies in creating the data handling strategies which is collected from the billions of heterogeneous devices distributed across the hospital network. Besides, the resource constrained nature of IoT would make these goals difficult to achieve. Motivated by aforementioned deliberations, this paper introduces a novel approach in designing a security framework for edge-computing based connected healthcare systems. An efficient, multi-factor access control and ownership transfer mechanism for edge-computing based futuristic healthcare applications is the core of proposed framework. Data scalability is achieved by employing distributed approach for clustering techniques that analyze and aggregate voluminous data acquired from heterogeneous devices individually before it transits the to the cloud. Moreover, data/device ownership transfer scheme is considered to be the first time in its kind. During ownership transfer phase, medical server facilitates user to transfer the patient information/ device ownership rights to the other registered users. In order to avoid the existing mistakes, we propose a formal and informal security analysis, that ensures the resistance towards most common IoT attacks such as insider attack, denial of distributed service (DDoS) attack and traceability attacks.
{"title":"A Multi-Factor Access Control and Ownership Transfer Framework for Future Generation Healthcare Systems","authors":"V. Aski, V. Dhaka, Sunil Kumar, Anubha Parashar, Akshata Ladagi","doi":"10.1109/PDGC50313.2020.9315840","DOIUrl":"https://doi.org/10.1109/PDGC50313.2020.9315840","url":null,"abstract":"The recent advancements in ubiquitous sensing powered by Wireless Computing Technologies (WCT) and Cloud Computing Services (CCS) have introduced a new thinking ability amongst researchers and healthcare professionals for building secure and connected healthcare systems. The integration of Internet of Things (IoT) in healthcare services further brings in several challenges with it, mainly including encrypted communication through vulnerable wireless medium, authentication and access control algorithms and ownership transfer schemes (important patient information). Major concern of such giant connected systems lies in creating the data handling strategies which is collected from the billions of heterogeneous devices distributed across the hospital network. Besides, the resource constrained nature of IoT would make these goals difficult to achieve. Motivated by aforementioned deliberations, this paper introduces a novel approach in designing a security framework for edge-computing based connected healthcare systems. An efficient, multi-factor access control and ownership transfer mechanism for edge-computing based futuristic healthcare applications is the core of proposed framework. Data scalability is achieved by employing distributed approach for clustering techniques that analyze and aggregate voluminous data acquired from heterogeneous devices individually before it transits the to the cloud. Moreover, data/device ownership transfer scheme is considered to be the first time in its kind. During ownership transfer phase, medical server facilitates user to transfer the patient information/ device ownership rights to the other registered users. In order to avoid the existing mistakes, we propose a formal and informal security analysis, that ensures the resistance towards most common IoT attacks such as insider attack, denial of distributed service (DDoS) attack and traceability attacks.","PeriodicalId":347216,"journal":{"name":"2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134470449","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 : 2020-11-06DOI: 10.1109/PDGC50313.2020.9315326
Kriti Verma, Mehak Beakta, P. Srivastava, N. U. Khan
Fatigueness of the driver is considered a major cause that account to a large numbers of death worldwide. Thus it becomes necessary to develop a system that can help reduce such accidents. During drowsy state, significant differences in the facial features of the driver are observed in comparison to the normal state. The system proposed in the paper is focused on detection as well as alarming the driver after recording the physiological state of the driver. We made use of the non-intrusive approach which monitors the subject in real-time, wherein the blinking of eyes as well as the mouth shape (yawn) of the operator are observed, and if the operator's eyes are shut for more than the threshold value, or the operator is yawning, or if both of them are detected at the same instance then the driver's state is concluded for precautions. The proposed system is designed using Python Language, and OpenCV application is used for image processing employing the use of Viola - Jones Algorithm for the detection of facial features.
{"title":"A Non-intrusive Approach for Driver's Drowsiness Detection","authors":"Kriti Verma, Mehak Beakta, P. Srivastava, N. U. Khan","doi":"10.1109/PDGC50313.2020.9315326","DOIUrl":"https://doi.org/10.1109/PDGC50313.2020.9315326","url":null,"abstract":"Fatigueness of the driver is considered a major cause that account to a large numbers of death worldwide. Thus it becomes necessary to develop a system that can help reduce such accidents. During drowsy state, significant differences in the facial features of the driver are observed in comparison to the normal state. The system proposed in the paper is focused on detection as well as alarming the driver after recording the physiological state of the driver. We made use of the non-intrusive approach which monitors the subject in real-time, wherein the blinking of eyes as well as the mouth shape (yawn) of the operator are observed, and if the operator's eyes are shut for more than the threshold value, or the operator is yawning, or if both of them are detected at the same instance then the driver's state is concluded for precautions. The proposed system is designed using Python Language, and OpenCV application is used for image processing employing the use of Viola - Jones Algorithm for the detection of facial features.","PeriodicalId":347216,"journal":{"name":"2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122063336","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 : 2020-11-06DOI: 10.1109/PDGC50313.2020.9315818
Meghna Dhalaria, Ekta Gandotra
The wide use of mobile phones has become a significant driving force behind a severe increase in malware attacks. These malware applications are hidden in the normal applications which make their classification and detection challenging. The existing techniques are based on signature based approach and are unable to detect unknown malware. In this paper, we propose a technique based on static and dynamic features for the detection of Android malware. We applied a chi-square feature selection algorithm to choose the appropriate features that contribute for detecting malware. After that, we stacked the different base classifiers to improve the detection rate. Furthermore, we compared the proposed method with existing well known machine learning classifiers. The experimental results demonstrate that the proposed technique (K-NN_ RF) achieves better detection accuracy i.e. 98.02%.
{"title":"Android Malware Detection using Chi-Square Feature Selection and Ensemble Learning Method","authors":"Meghna Dhalaria, Ekta Gandotra","doi":"10.1109/PDGC50313.2020.9315818","DOIUrl":"https://doi.org/10.1109/PDGC50313.2020.9315818","url":null,"abstract":"The wide use of mobile phones has become a significant driving force behind a severe increase in malware attacks. These malware applications are hidden in the normal applications which make their classification and detection challenging. The existing techniques are based on signature based approach and are unable to detect unknown malware. In this paper, we propose a technique based on static and dynamic features for the detection of Android malware. We applied a chi-square feature selection algorithm to choose the appropriate features that contribute for detecting malware. After that, we stacked the different base classifiers to improve the detection rate. Furthermore, we compared the proposed method with existing well known machine learning classifiers. The experimental results demonstrate that the proposed technique (K-NN_ RF) achieves better detection accuracy i.e. 98.02%.","PeriodicalId":347216,"journal":{"name":"2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125816046","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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