Pub Date : 2021-01-19DOI: 10.1109/iccakm50778.2021.9357752
Mark Eugine Z. Francisco, Sonakshi Ruhela
The year 2020 started with an increase in usage of social media platforms specifically TikTok, an AI powered platform during the global pandemic. The study explored the relationship between behaviors and motivations of TikTok users and the role of artificial intelligence. An online survey was administered to 67 TikTok users to identify behaviors and motivations and to investigate the correlation between users' behaviors and motivations. The study found out patterns between behaviors and motivations which were tested by using correlational coefficient and one sample t-test. Based on the study there is a significant relationship between behaviors and motivations in using TikTok application and an increase in usage of TikTok during the year 2020. The study enlightened both TikTok users and non-users about its unforeseen benefits during the time of pandemic. Further, Artificial Intelligence enables the social platforms to have personalized content, prediction technology, and online mental health facility which can take over the world.
{"title":"Investigating TikTok as an AI user platform","authors":"Mark Eugine Z. Francisco, Sonakshi Ruhela","doi":"10.1109/iccakm50778.2021.9357752","DOIUrl":"https://doi.org/10.1109/iccakm50778.2021.9357752","url":null,"abstract":"The year 2020 started with an increase in usage of social media platforms specifically TikTok, an AI powered platform during the global pandemic. The study explored the relationship between behaviors and motivations of TikTok users and the role of artificial intelligence. An online survey was administered to 67 TikTok users to identify behaviors and motivations and to investigate the correlation between users' behaviors and motivations. The study found out patterns between behaviors and motivations which were tested by using correlational coefficient and one sample t-test. Based on the study there is a significant relationship between behaviors and motivations in using TikTok application and an increase in usage of TikTok during the year 2020. The study enlightened both TikTok users and non-users about its unforeseen benefits during the time of pandemic. Further, Artificial Intelligence enables the social platforms to have personalized content, prediction technology, and online mental health facility which can take over the world.","PeriodicalId":165854,"journal":{"name":"2021 2nd International Conference on Computation, Automation and Knowledge Management (ICCAKM)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114757097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-19DOI: 10.1109/iccakm50778.2021.9357733
Wedad Ahmed Al-Dhuraibi, M. Elhadef
Vehicular Ad-Hoc Network is an intelligent transportation system that provides wireless communication between vehicles and different objects in the road to increase human safety. Vehicular Ad-Hoc Networks are ideal target to many attacks due to the large number of vehicles communicating with each other continually and instantly through a wireless medium. Security is one of the safety aspects where saving human lives is very critical. Denial of Service Attack is one of the most dangerous attacks since it targets the availability of the network services. The goal of any type of Denial of Service Attack is to interrupt the services for legitimate users or prevent them from accessing the network resources. In this paper, we simulate Dynamic Distributed Denial of Service Attack in different scenarios using the VEINS framework, SUMO and OMNET++.
{"title":"Securing Vehicular Ad-Hoc Networks: A DDoS Case Study","authors":"Wedad Ahmed Al-Dhuraibi, M. Elhadef","doi":"10.1109/iccakm50778.2021.9357733","DOIUrl":"https://doi.org/10.1109/iccakm50778.2021.9357733","url":null,"abstract":"Vehicular Ad-Hoc Network is an intelligent transportation system that provides wireless communication between vehicles and different objects in the road to increase human safety. Vehicular Ad-Hoc Networks are ideal target to many attacks due to the large number of vehicles communicating with each other continually and instantly through a wireless medium. Security is one of the safety aspects where saving human lives is very critical. Denial of Service Attack is one of the most dangerous attacks since it targets the availability of the network services. The goal of any type of Denial of Service Attack is to interrupt the services for legitimate users or prevent them from accessing the network resources. In this paper, we simulate Dynamic Distributed Denial of Service Attack in different scenarios using the VEINS framework, SUMO and OMNET++.","PeriodicalId":165854,"journal":{"name":"2021 2nd International Conference on Computation, Automation and Knowledge Management (ICCAKM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128578472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-19DOI: 10.1109/iccakm50778.2021.9357699
Abdikarim Ali Moumin, Smitha S Kumar
The advances in modern computing technologies have achieved a breakthrough in the fields of artificial intelligence (AI) and the Internet of Things (IoT). One of the major achievements in the recent history is the ability of the computer software to classify and recognize some of the objects or sounds by learning data. In this paper, we have trained the software to recognize people using their voice utterances using TIMIT Acoustic Phonetic Continuous Speech Corpus. The speaker identity is enrolled by acquiring voice samples of the speaker. Relevant features are extracted, and a model is built using the extracted feature vectors. A pattern matching classification is applied to the model using artificial neural network techniques. Speaker verification system is built using Kaldi libraries to analyze acoustic features, while x-vector training is implemented using Tensor Flow. To achieve better performance, we have implemented a combination of multiple layers of TDNN (Time Delay Neural Networks) and LSTM (Long Short-Term Memory) deep neural networks.
{"title":"Automatic Speaker Recognition using Deep Neural Network Classifiers","authors":"Abdikarim Ali Moumin, Smitha S Kumar","doi":"10.1109/iccakm50778.2021.9357699","DOIUrl":"https://doi.org/10.1109/iccakm50778.2021.9357699","url":null,"abstract":"The advances in modern computing technologies have achieved a breakthrough in the fields of artificial intelligence (AI) and the Internet of Things (IoT). One of the major achievements in the recent history is the ability of the computer software to classify and recognize some of the objects or sounds by learning data. In this paper, we have trained the software to recognize people using their voice utterances using TIMIT Acoustic Phonetic Continuous Speech Corpus. The speaker identity is enrolled by acquiring voice samples of the speaker. Relevant features are extracted, and a model is built using the extracted feature vectors. A pattern matching classification is applied to the model using artificial neural network techniques. Speaker verification system is built using Kaldi libraries to analyze acoustic features, while x-vector training is implemented using Tensor Flow. To achieve better performance, we have implemented a combination of multiple layers of TDNN (Time Delay Neural Networks) and LSTM (Long Short-Term Memory) deep neural networks.","PeriodicalId":165854,"journal":{"name":"2021 2nd International Conference on Computation, Automation and Knowledge Management (ICCAKM)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126340183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-19DOI: 10.1109/ICCAKM50778.2021.9357747
Bhanu Sharma, Amar Singh, Jimmy Singla
WMN's or Wireless Mesh Network is a communication network that has features like self-healing., self-organizing and the ability to create a network automatically in its dynamic environment. It mainly consists of mesh routers., mesh clients and gateways which results in building a rich connection among the devices and nodes. Considering the functionalities of it., this paper presents an overview of different routing protocols for WMN's. In this paper., we analyzed the performances of soft computing and hard computing protocols i.e. AODV., DSR and BBBC. From simulations., we observed that on large networks BBBC based approach outperformed the performances of AODV and DSR.
{"title":"Recent Routing Approaches for WMN's: A State of Art","authors":"Bhanu Sharma, Amar Singh, Jimmy Singla","doi":"10.1109/ICCAKM50778.2021.9357747","DOIUrl":"https://doi.org/10.1109/ICCAKM50778.2021.9357747","url":null,"abstract":"WMN's or Wireless Mesh Network is a communication network that has features like self-healing., self-organizing and the ability to create a network automatically in its dynamic environment. It mainly consists of mesh routers., mesh clients and gateways which results in building a rich connection among the devices and nodes. Considering the functionalities of it., this paper presents an overview of different routing protocols for WMN's. In this paper., we analyzed the performances of soft computing and hard computing protocols i.e. AODV., DSR and BBBC. From simulations., we observed that on large networks BBBC based approach outperformed the performances of AODV and DSR.","PeriodicalId":165854,"journal":{"name":"2021 2nd International Conference on Computation, Automation and Knowledge Management (ICCAKM)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121269501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-19DOI: 10.1109/ICCAKM50778.2021.9357739
N. Mani, Soham Sanjay Parab, S. Manaswini, S. Philip, Parli B. Hari, Nrashant Singh
Forensic block chain is an emerging technique in the field of forensic science. It is a system integrated tool that helps in maintaining and representing the chain of custody, which ought to be maintained throughout the investigation. Forensic block chain is an approach wherein the investigators or law enforcement officials store the history of criminal case in a digitalized form on block chains which in turn stores the information on remote servers. The data regarding the criminal records are highly encrypted providing less probability for intruders to gain access into the system. Implementing artificial intelligence will help to manage and sort the data related to case records/criminal profile. AI helps in creating and analyzing a case report, and further processing of evidence. This will help the investigator to create more efficient hypothesis. Present study aims to link Artificial Intelligence to forensic block chain and develop a digitalize chain of custody of evidences that will help the forensic investigators to link the cases worldwide and help in solving crimes efficiently.
{"title":"Forensic Block Chain and it's linkage with Artificial Intelligence: A new Approach","authors":"N. Mani, Soham Sanjay Parab, S. Manaswini, S. Philip, Parli B. Hari, Nrashant Singh","doi":"10.1109/ICCAKM50778.2021.9357739","DOIUrl":"https://doi.org/10.1109/ICCAKM50778.2021.9357739","url":null,"abstract":"Forensic block chain is an emerging technique in the field of forensic science. It is a system integrated tool that helps in maintaining and representing the chain of custody, which ought to be maintained throughout the investigation. Forensic block chain is an approach wherein the investigators or law enforcement officials store the history of criminal case in a digitalized form on block chains which in turn stores the information on remote servers. The data regarding the criminal records are highly encrypted providing less probability for intruders to gain access into the system. Implementing artificial intelligence will help to manage and sort the data related to case records/criminal profile. AI helps in creating and analyzing a case report, and further processing of evidence. This will help the investigator to create more efficient hypothesis. Present study aims to link Artificial Intelligence to forensic block chain and develop a digitalize chain of custody of evidences that will help the forensic investigators to link the cases worldwide and help in solving crimes efficiently.","PeriodicalId":165854,"journal":{"name":"2021 2nd International Conference on Computation, Automation and Knowledge Management (ICCAKM)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121681257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-19DOI: 10.1109/iccakm50778.2021.9357721
Raveendran Meloth Swaroop, K. S. Siddharth
Injectors exiting annular liquid sheets and its subsequent atomization find relevance in rocket propulsion applications. Numerous studies have been performed by researchers in the past for understanding the dynamics of disintegration of annular liquid sheets into droplets under the influence of various factors. The factors mainly include the instabilities on the sheet caused by the effect of surrounding gas flow, in particular. The article abridges the findings from the prominent studies done in this field with a focus on how imaging was used a tool in quantifying the same.
{"title":"Annular liquid sheets and its dynamics - A review","authors":"Raveendran Meloth Swaroop, K. S. Siddharth","doi":"10.1109/iccakm50778.2021.9357721","DOIUrl":"https://doi.org/10.1109/iccakm50778.2021.9357721","url":null,"abstract":"Injectors exiting annular liquid sheets and its subsequent atomization find relevance in rocket propulsion applications. Numerous studies have been performed by researchers in the past for understanding the dynamics of disintegration of annular liquid sheets into droplets under the influence of various factors. The factors mainly include the instabilities on the sheet caused by the effect of surrounding gas flow, in particular. The article abridges the findings from the prominent studies done in this field with a focus on how imaging was used a tool in quantifying the same.","PeriodicalId":165854,"journal":{"name":"2021 2nd International Conference on Computation, Automation and Knowledge Management (ICCAKM)","volume":"268 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115792022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-19DOI: 10.1109/iccakm50778.2021.9357730
Bharat Kapila, T. Thind
Development innovation and speedy Network make it simple and monetary to spread data across the globe. This leads people to think about their safety and their jobs. Steganography is a methodology that stops unwanted consumers from going towards simple information. Steganography and sophisticated watermarking offer procedures for consumers to hide and blend their data with other details that makes it impossible for attackers to see them. In this paper the main purpose is to research a couple of steganography and mechanized watermarking systems in both spatial and repeat spaces.
{"title":"Review and analysis of data security using image steganography","authors":"Bharat Kapila, T. Thind","doi":"10.1109/iccakm50778.2021.9357730","DOIUrl":"https://doi.org/10.1109/iccakm50778.2021.9357730","url":null,"abstract":"Development innovation and speedy Network make it simple and monetary to spread data across the globe. This leads people to think about their safety and their jobs. Steganography is a methodology that stops unwanted consumers from going towards simple information. Steganography and sophisticated watermarking offer procedures for consumers to hide and blend their data with other details that makes it impossible for attackers to see them. In this paper the main purpose is to research a couple of steganography and mechanized watermarking systems in both spatial and repeat spaces.","PeriodicalId":165854,"journal":{"name":"2021 2nd International Conference on Computation, Automation and Knowledge Management (ICCAKM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128614678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-19DOI: 10.1109/iccakm50778.2021.9357726
Moomal Farhad, H. Ismail, S. Harous, M. Masud, A. Beg
In a system which involves interaction be- tween machines and humans, the recognition of emotion from audio has always been a focus of research. Emotion recognition can play an essential role in many fields, such as medicine, law, psychology, and customer services. In this paper, we present an empirical comparative analysis of several machine learning classifiers for emotion recognition in audio data. Evaluations are performed for a set of predefined emotions such as happy, sad, and angry from Arabic, English, and Urdu languages. Pitch and cepstral features are extracted from audio files and principal component analysis is applied for dimensionality reduction. Experiments show that random forest outperformed other classifiers on Urdu dataset with an accuracy of 78.75%. However, the performance of Meta iterative classifier on Arabic dataset was better than random forest and neural network with the accuracy of 70%. Classification of emotions on the English dataset, which do not differ much in terms of pitch and MFCC features, generated the lowest accuracies at or below 31%.
{"title":"Analysis of Emotion Recognition from Cross-lingual Speech: Arabic, English, and Urdu","authors":"Moomal Farhad, H. Ismail, S. Harous, M. Masud, A. Beg","doi":"10.1109/iccakm50778.2021.9357726","DOIUrl":"https://doi.org/10.1109/iccakm50778.2021.9357726","url":null,"abstract":"In a system which involves interaction be- tween machines and humans, the recognition of emotion from audio has always been a focus of research. Emotion recognition can play an essential role in many fields, such as medicine, law, psychology, and customer services. In this paper, we present an empirical comparative analysis of several machine learning classifiers for emotion recognition in audio data. Evaluations are performed for a set of predefined emotions such as happy, sad, and angry from Arabic, English, and Urdu languages. Pitch and cepstral features are extracted from audio files and principal component analysis is applied for dimensionality reduction. Experiments show that random forest outperformed other classifiers on Urdu dataset with an accuracy of 78.75%. However, the performance of Meta iterative classifier on Arabic dataset was better than random forest and neural network with the accuracy of 70%. Classification of emotions on the English dataset, which do not differ much in terms of pitch and MFCC features, generated the lowest accuracies at or below 31%.","PeriodicalId":165854,"journal":{"name":"2021 2nd International Conference on Computation, Automation and Knowledge Management (ICCAKM)","volume":"692 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115116367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-19DOI: 10.1109/ICCAKM50778.2021.9357759
Anupam Mehrotra, S. Menon
Banking and Financial services landscape is characterized by a parallel growth of FinTech on the one hand and Iot, Big Data, block chain, Artificial Intelligence (AI) and Machine Learning on the other. While the first round of challenges involved adapting to phenomenal FinTech growth and strategizing either by creating FinTech capability in house or collaborating with the Fin Tech companies. The next round of challenges as they are coming up are to fuse the fourth generation technologies like IoT, block chain, AI and robotics into the FinTech architecture so as to generate a holistic package of services primarily to meet the fast changing demand pattern of millennial customers through solutions like mobile payments, budgeting, crowd funding, Robo Advising, Insurance, crypto currency, block chain, etc. The intricacy of the challenge involves introducing the latest technologies within the FinTech framework to make banking and financial services nimble, smooth and more customer centric than ever. What logically follows is meeting adequately the regulatory demands and defeating cyber-threats in the process. The instant paper attempts to analyze the impact of newer technological innovations within the financial services sector and the need to unlock the potential of FinTech that it may offer in the years to come.
{"title":"Second Round of FinTech - Trends and Challenges","authors":"Anupam Mehrotra, S. Menon","doi":"10.1109/ICCAKM50778.2021.9357759","DOIUrl":"https://doi.org/10.1109/ICCAKM50778.2021.9357759","url":null,"abstract":"Banking and Financial services landscape is characterized by a parallel growth of FinTech on the one hand and Iot, Big Data, block chain, Artificial Intelligence (AI) and Machine Learning on the other. While the first round of challenges involved adapting to phenomenal FinTech growth and strategizing either by creating FinTech capability in house or collaborating with the Fin Tech companies. The next round of challenges as they are coming up are to fuse the fourth generation technologies like IoT, block chain, AI and robotics into the FinTech architecture so as to generate a holistic package of services primarily to meet the fast changing demand pattern of millennial customers through solutions like mobile payments, budgeting, crowd funding, Robo Advising, Insurance, crypto currency, block chain, etc. The intricacy of the challenge involves introducing the latest technologies within the FinTech framework to make banking and financial services nimble, smooth and more customer centric than ever. What logically follows is meeting adequately the regulatory demands and defeating cyber-threats in the process. The instant paper attempts to analyze the impact of newer technological innovations within the financial services sector and the need to unlock the potential of FinTech that it may offer in the years to come.","PeriodicalId":165854,"journal":{"name":"2021 2nd International Conference on Computation, Automation and Knowledge Management (ICCAKM)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128951311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-19DOI: 10.1109/iccakm50778.2021.9357698
Asif Iqbal Kawoosa, D. Prashar
A Smart Grid (SG) is an electrical infrastructure much like legacy power grid with scalable and pervasive two-way communications, timely control capabilities, large scale integration of distributed resources and efficient use of resources. The SG provides the features of pervasive smart monitoring technologies, automatic equipment fault sensing and self-healing. The features like ‘Wireless Automatic Meter Reading’ (WAMR), monitoring of power system stability, distributed energy resources optimization and applications of Demand Response system makes it intelligent infrastructure. Given some of these salient features, SGs without any doubt are the future power infrastructure of energy world. A smart grid has ability to connect millions of consumers and devices in a network which demand it to be highly robust, reliable and secure. Security is considered as one of the major challenges in the present-day smart grid systems because of its long-range communication on open networks. Cybercriminals, hackers, terrorists are trying to attack this national infrastructure due to their malicious intensions or to get control on the automated energy monitoring and remote controlling for personal gains. This review paper offers a comprehensive survey of understanding of Smart Grids, architecture of SGs, methodologies used, the communication protocols but the focus is mainly on the cyber-attacks carried out and solutions recommended on the smart grids. We finally discuss the various challenges in cyber security, the issues that still exist in the literature and current solution space with future research gap.
{"title":"A Review of Cyber Securities in Smart Grid Technology","authors":"Asif Iqbal Kawoosa, D. Prashar","doi":"10.1109/iccakm50778.2021.9357698","DOIUrl":"https://doi.org/10.1109/iccakm50778.2021.9357698","url":null,"abstract":"A Smart Grid (SG) is an electrical infrastructure much like legacy power grid with scalable and pervasive two-way communications, timely control capabilities, large scale integration of distributed resources and efficient use of resources. The SG provides the features of pervasive smart monitoring technologies, automatic equipment fault sensing and self-healing. The features like ‘Wireless Automatic Meter Reading’ (WAMR), monitoring of power system stability, distributed energy resources optimization and applications of Demand Response system makes it intelligent infrastructure. Given some of these salient features, SGs without any doubt are the future power infrastructure of energy world. A smart grid has ability to connect millions of consumers and devices in a network which demand it to be highly robust, reliable and secure. Security is considered as one of the major challenges in the present-day smart grid systems because of its long-range communication on open networks. Cybercriminals, hackers, terrorists are trying to attack this national infrastructure due to their malicious intensions or to get control on the automated energy monitoring and remote controlling for personal gains. This review paper offers a comprehensive survey of understanding of Smart Grids, architecture of SGs, methodologies used, the communication protocols but the focus is mainly on the cyber-attacks carried out and solutions recommended on the smart grids. We finally discuss the various challenges in cyber security, the issues that still exist in the literature and current solution space with future research gap.","PeriodicalId":165854,"journal":{"name":"2021 2nd International Conference on Computation, Automation and Knowledge Management (ICCAKM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116303057","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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