Pub Date : 2020-10-07DOI: 10.1109/I-SMAC49090.2020.9243310
A. Srinivasan, Sharavanee D P, S. P, Surendran S, Suryaprakash S, Jino Hans W
Engine oil is a vital factor in the efficient functioning of any automobile. It acts as a lubricant to reduce friction between the mechanical parts and also keeps the engine cool by dissipating the heat. During this process, parameters such as viscosity of oil changes. Engine oil is changed at regular intervals of time without checking its quality. This can lead to wastage as the real health of engine oil during an oil change is unknown. This paper discusses an efficient way to monitor the health of the engine to minimize the wastage. By adapting the traditional falling ball method of measuring the viscosity of a liquid, an in situ miniaturized prototype is fabricated. The prototype consists of a narrow and hollow cylindrical tube with slits to allow the movement of oil through it. At the floor of the tube, two sensory electrodes are placed and at the top, an electromagnet attached. A steel ball is placed inside the tube and is made to move freely. The whole setup is attached to a servo motor and is controlled by an Arduino Nano. With this prototype, the average fall time of the ball through the oil is calculated and viscosity is found using the Stokes Law.
{"title":"Arduino based Automated Viscometer for Oil Health Monitoring","authors":"A. Srinivasan, Sharavanee D P, S. P, Surendran S, Suryaprakash S, Jino Hans W","doi":"10.1109/I-SMAC49090.2020.9243310","DOIUrl":"https://doi.org/10.1109/I-SMAC49090.2020.9243310","url":null,"abstract":"Engine oil is a vital factor in the efficient functioning of any automobile. It acts as a lubricant to reduce friction between the mechanical parts and also keeps the engine cool by dissipating the heat. During this process, parameters such as viscosity of oil changes. Engine oil is changed at regular intervals of time without checking its quality. This can lead to wastage as the real health of engine oil during an oil change is unknown. This paper discusses an efficient way to monitor the health of the engine to minimize the wastage. By adapting the traditional falling ball method of measuring the viscosity of a liquid, an in situ miniaturized prototype is fabricated. The prototype consists of a narrow and hollow cylindrical tube with slits to allow the movement of oil through it. At the floor of the tube, two sensory electrodes are placed and at the top, an electromagnet attached. A steel ball is placed inside the tube and is made to move freely. The whole setup is attached to a servo motor and is controlled by an Arduino Nano. With this prototype, the average fall time of the ball through the oil is calculated and viscosity is found using the Stokes Law.","PeriodicalId":432766,"journal":{"name":"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123882897","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 : 2020-10-07DOI: 10.1109/I-SMAC49090.2020.9243351
M. Ramkumar, A. Amudha, M. Sivaramkrishnan., S. Divyapriya, P. Nagaveni, G. Emayavaramban, V. Mansoor
The development of countries to alleviate control demands is focused on load shedding or power intrusion. In the centre of market fraud, non-controllers use a low degree of compliance management material. The related network of solar light-based voltaic photograph (PV) inverters is commonly used for household reinforcement via and via housetop. The battery is supplied by the network in full battery state. As the sole-based strength is used to charge the battery, the voltage of the PV frame is used. In addition to the usual system, the proposed control exchange structure for supervision is successful. The proposed controller was effective with a smaller private system in order to fulfil the stack demand for and stature heap of the programming matrix for the spanning of light hours for the reference, the proposed unit also fills out the household to-lattice (H2 G) structure. Keywords: Load shedding, PV, Inverter
{"title":"Micro Grid based Low Price Residential Home to Grid - Modeling and Control of Power Management System","authors":"M. Ramkumar, A. Amudha, M. Sivaramkrishnan., S. Divyapriya, P. Nagaveni, G. Emayavaramban, V. Mansoor","doi":"10.1109/I-SMAC49090.2020.9243351","DOIUrl":"https://doi.org/10.1109/I-SMAC49090.2020.9243351","url":null,"abstract":"The development of countries to alleviate control demands is focused on load shedding or power intrusion. In the centre of market fraud, non-controllers use a low degree of compliance management material. The related network of solar light-based voltaic photograph (PV) inverters is commonly used for household reinforcement via and via housetop. The battery is supplied by the network in full battery state. As the sole-based strength is used to charge the battery, the voltage of the PV frame is used. In addition to the usual system, the proposed control exchange structure for supervision is successful. The proposed controller was effective with a smaller private system in order to fulfil the stack demand for and stature heap of the programming matrix for the spanning of light hours for the reference, the proposed unit also fills out the household to-lattice (H2 G) structure. Keywords: Load shedding, PV, Inverter","PeriodicalId":432766,"journal":{"name":"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124873214","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}
This paper is mainly focused on the low cost technique to measure both AC and DC voltage along with current by using very low cost components. The system can also be easily monitored via a smartphone. The work is intended for the engineering students as most of the Voltmeter/Ammeter is very expensive. Not only that, the acquired data can be stored as per the requirements. New features can be added very easily with this ammeter/voltmeter as well. Whole task was implemented with the help of popular micro-controller ATmega328p to reduce the cost.
{"title":"Low Cost Voltage and Current Measurement Technique using ATmega328p","authors":"Fahad Faisal, Asif Karim, Md. Zahid Hasan, Bharanidharan Shanmugam, Muntasir Mahdi, Nazmun Nessa Moon","doi":"10.1109/I-SMAC49090.2020.9243404","DOIUrl":"https://doi.org/10.1109/I-SMAC49090.2020.9243404","url":null,"abstract":"This paper is mainly focused on the low cost technique to measure both AC and DC voltage along with current by using very low cost components. The system can also be easily monitored via a smartphone. The work is intended for the engineering students as most of the Voltmeter/Ammeter is very expensive. Not only that, the acquired data can be stored as per the requirements. New features can be added very easily with this ammeter/voltmeter as well. Whole task was implemented with the help of popular micro-controller ATmega328p to reduce the cost.","PeriodicalId":432766,"journal":{"name":"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121571728","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 : 2020-10-07DOI: 10.1109/I-SMAC49090.2020.9243597
N. V. Swati, I. M
Schizophrenia is a neurological disorder which has drawn a lot of attention around the world. It includes symptoms such as social withdrawal, hallucinations, delusions, confused thinking leading to other major disorders including obsessive-compulsive disorder and panic disorder. Diagnosis of psychological disorders is difficult based on one's behavioral changes. It is difficult to diagnose the exact psychological disorder due to similar symptom exhibition. More the time is taken to diagnose; more is the chance of leading to permanent disablement. In this regard, ongoing research projects are ranging from craniological studies using fMRI to retinal imaging analysis to diagnose various psychological disorders. Machine learning for image analysis in the medical domain has proven successful. This paper discusses the evolution of Schizophrenia detection technologies in relation to structural changes in brain and eye using different machine learning classification algorithms.
{"title":"Machine Learning Systems for Detecting Schizophrenia","authors":"N. V. Swati, I. M","doi":"10.1109/I-SMAC49090.2020.9243597","DOIUrl":"https://doi.org/10.1109/I-SMAC49090.2020.9243597","url":null,"abstract":"Schizophrenia is a neurological disorder which has drawn a lot of attention around the world. It includes symptoms such as social withdrawal, hallucinations, delusions, confused thinking leading to other major disorders including obsessive-compulsive disorder and panic disorder. Diagnosis of psychological disorders is difficult based on one's behavioral changes. It is difficult to diagnose the exact psychological disorder due to similar symptom exhibition. More the time is taken to diagnose; more is the chance of leading to permanent disablement. In this regard, ongoing research projects are ranging from craniological studies using fMRI to retinal imaging analysis to diagnose various psychological disorders. Machine learning for image analysis in the medical domain has proven successful. This paper discusses the evolution of Schizophrenia detection technologies in relation to structural changes in brain and eye using different machine learning classification algorithms.","PeriodicalId":432766,"journal":{"name":"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116722172","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 : 2020-10-07DOI: 10.1109/I-SMAC49090.2020.9243575
M. Vasan
Word-of-Mouth Communication (WOMC) is viewed as an imperative form of promotion, particularly it plays a significant role in product selection. This paper aims to explore factors influencing word of mouth communication among users of personal care products. This study adopted the qualitative method of research. A questionnaire was designed to gather data from the 750 respondents. The Factor analysis identified seven major factors of WOMC namely reciprocity, information sharing desire, self-enhancement, source credibility, brand selection, purchase decision, and opinion seeking. The result of SEM proves that purchase decision and reciprocity are the effective factors among the receivers of WOMC. The study results will assist the marketing managers to comprehend the factors possible to influence among receivers of WOMC.
{"title":"Effectiveness of Word of Mouth Communication: Receiver Perspectives","authors":"M. Vasan","doi":"10.1109/I-SMAC49090.2020.9243575","DOIUrl":"https://doi.org/10.1109/I-SMAC49090.2020.9243575","url":null,"abstract":"Word-of-Mouth Communication (WOMC) is viewed as an imperative form of promotion, particularly it plays a significant role in product selection. This paper aims to explore factors influencing word of mouth communication among users of personal care products. This study adopted the qualitative method of research. A questionnaire was designed to gather data from the 750 respondents. The Factor analysis identified seven major factors of WOMC namely reciprocity, information sharing desire, self-enhancement, source credibility, brand selection, purchase decision, and opinion seeking. The result of SEM proves that purchase decision and reciprocity are the effective factors among the receivers of WOMC. The study results will assist the marketing managers to comprehend the factors possible to influence among receivers of WOMC.","PeriodicalId":432766,"journal":{"name":"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125078318","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 : 2020-10-07DOI: 10.1109/I-SMAC49090.2020.9243428
Shweta Joshi, Geetha R. Chillarge
Nowadays organization use the cloud infrastructure to store data as no local setup needed in the user system. To retrieve files from the cloud, the user needs internet service. When the internet comes into the picture, a lot of attacks happens on the cloud, and to detect & prevent those attacks, cloud forensics is used. Secure user log file on the cloud is also important as the cloud log contains valuable information which helps in forensics investigation. Previously designed logging systems have some drawbacks for providing security to the cloud user. The existing system provides security on user files which is uploaded by the user or they provide login authentication of the user. In this secure logging, the scheme is provided by encrypting cloud logs (sensitive information of the user) using encryption techniques and it identifies DDoS (distributed denial of service) assault on the cloud framework. It is distinguished through investigating accessible cloud logs in the cloud server. Encryption algorithms will be utilized to build the security of the logging system and to keep up secrecy and protection of client information.
{"title":"Secure Log Scheme for Cloud Forensics","authors":"Shweta Joshi, Geetha R. Chillarge","doi":"10.1109/I-SMAC49090.2020.9243428","DOIUrl":"https://doi.org/10.1109/I-SMAC49090.2020.9243428","url":null,"abstract":"Nowadays organization use the cloud infrastructure to store data as no local setup needed in the user system. To retrieve files from the cloud, the user needs internet service. When the internet comes into the picture, a lot of attacks happens on the cloud, and to detect & prevent those attacks, cloud forensics is used. Secure user log file on the cloud is also important as the cloud log contains valuable information which helps in forensics investigation. Previously designed logging systems have some drawbacks for providing security to the cloud user. The existing system provides security on user files which is uploaded by the user or they provide login authentication of the user. In this secure logging, the scheme is provided by encrypting cloud logs (sensitive information of the user) using encryption techniques and it identifies DDoS (distributed denial of service) assault on the cloud framework. It is distinguished through investigating accessible cloud logs in the cloud server. Encryption algorithms will be utilized to build the security of the logging system and to keep up secrecy and protection of client information.","PeriodicalId":432766,"journal":{"name":"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122614250","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 : 2020-10-07DOI: 10.1109/I-SMAC49090.2020.9243386
G. Ali, Aqeel Luaibi
To learn a hierarchal representation of data, deep learning techniques can be used that use multiple processing layers, and produce state of art results. Many models and methods are designed in deep learning for classification in natural language processing (NLP). Various classification algorithms have been used for Arabic documents classification, but they have two problems High dimensional feature representation and the low accuracy of the classification. In this work, an important experiment is made by using deep related models and methods for classifying Arabic text also compare our model with various models. Also to forward a full understand, present and future of deep learning in Arabic text classification and have obtained encouraging results.
{"title":"Microcontroller based Automatic Sun Tracking Solar Panel","authors":"G. Ali, Aqeel Luaibi","doi":"10.1109/I-SMAC49090.2020.9243386","DOIUrl":"https://doi.org/10.1109/I-SMAC49090.2020.9243386","url":null,"abstract":"To learn a hierarchal representation of data, deep learning techniques can be used that use multiple processing layers, and produce state of art results. Many models and methods are designed in deep learning for classification in natural language processing (NLP). Various classification algorithms have been used for Arabic documents classification, but they have two problems High dimensional feature representation and the low accuracy of the classification. In this work, an important experiment is made by using deep related models and methods for classifying Arabic text also compare our model with various models. Also to forward a full understand, present and future of deep learning in Arabic text classification and have obtained encouraging results.","PeriodicalId":432766,"journal":{"name":"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131585923","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 : 2020-10-07DOI: 10.1109/I-SMAC49090.2020.9243592
A. Yasmin, S. Kamalakkannan
New online mode learns more about different kinetic models. Frequency algorithm reduces the loss function, which directly compensates for the error between the required and the actual acceleration. It allows the use of green acceleration principles such as speed accelerators and TensorFlow as a helper function of the robot mode. The use of direct loss eliminates the problem of learning outside the scope of indirect loss programs, usually in their current state. The power of re-learning creates a trend online tip according to standard non-linear parameters updating and updating online can correct frequency varied operating error during big data real-world generation. JEDEC reduced the machine learning sequence by a combined multi-dimension robust management robust study is planned for future tasks. This paper describes the operation and control of the controller for analytical, there is a clear link between the size of the compressor, the vibration level and the lens pool, learning new machine learning tools. In particular, JEDEC(Joint Electron Device Engineering Council) would like to use relational PACELC(Partition exists for Availability/consistency Else Latency/consistency) theoretical analysis to obtain the same summary and intensity The results of frequency case will also focus on increasing demand Important task balance, especially Restore model other types of contractions, as well as the connection between this reduced style adapter control and the learned control style multi-dimensions in sushisen algorithm using reduces these updates Deep Lanning Networks. Therefore, BDA data Partitioning helps to reduce the complexity of the calculation in the learning process and classification of data storage.
新的在线模式学习了更多不同的动力学模型。频率算法减小了损失函数，直接补偿了所需加速度与实际加速度之间的误差。它允许使用绿色加速原理，如速度加速器和TensorFlow作为机器人模式的辅助功能。直接损失的使用消除了在间接损失程序范围之外的学习问题，通常在它们的当前状态下。再学习的力量根据标准的非线性参数更新产生趋势在线提示，在线更新可以纠正大数据现实生成过程中的频变操作误差。JEDEC通过组合多维鲁棒管理减少了机器学习序列，并计划对未来的任务进行鲁棒研究。本文介绍了控制器的操作和控制进行分析，压缩机的大小、振动水平和镜头池之间有明确的联系，学习新的机器学习工具。特别是JEDEC(联合电子器件工程委员会)希望利用关系PACELC(Partition exists for Availability/consistency Else Latency/consistency)理论分析得到相同的总结和强度，频率情况下的结果也将重点放在增加需求的重要任务平衡上，特别是Restore模型其他类型的收缩。以及在sushisen算法中使用减少这些更新的深度学习网络中，这种简化风格适配器控制与学习风格多维度之间的联系。因此，BDA数据分区有助于降低学习过程中计算和数据存储分类的复杂性。
{"title":"PACELC: Enchantment multi-dimension TensorFlow for value creation through Big Data","authors":"A. Yasmin, S. Kamalakkannan","doi":"10.1109/I-SMAC49090.2020.9243592","DOIUrl":"https://doi.org/10.1109/I-SMAC49090.2020.9243592","url":null,"abstract":"New online mode learns more about different kinetic models. Frequency algorithm reduces the loss function, which directly compensates for the error between the required and the actual acceleration. It allows the use of green acceleration principles such as speed accelerators and TensorFlow as a helper function of the robot mode. The use of direct loss eliminates the problem of learning outside the scope of indirect loss programs, usually in their current state. The power of re-learning creates a trend online tip according to standard non-linear parameters updating and updating online can correct frequency varied operating error during big data real-world generation. JEDEC reduced the machine learning sequence by a combined multi-dimension robust management robust study is planned for future tasks. This paper describes the operation and control of the controller for analytical, there is a clear link between the size of the compressor, the vibration level and the lens pool, learning new machine learning tools. In particular, JEDEC(Joint Electron Device Engineering Council) would like to use relational PACELC(Partition exists for Availability/consistency Else Latency/consistency) theoretical analysis to obtain the same summary and intensity The results of frequency case will also focus on increasing demand Important task balance, especially Restore model other types of contractions, as well as the connection between this reduced style adapter control and the learned control style multi-dimensions in sushisen algorithm using reduces these updates Deep Lanning Networks. Therefore, BDA data Partitioning helps to reduce the complexity of the calculation in the learning process and classification of data storage.","PeriodicalId":432766,"journal":{"name":"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128019081","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 : 2020-10-07DOI: 10.1109/I-SMAC49090.2020.9243413
K. Tharageswari, D.Selva Pandian, Laxmi Raja, R. Dhanapal
As indicated by the Health foundations, illnesses brought about by an undesirable way of life speak to the main source of death everywhere throughout the world. Along these lines, it is pivotal to monitor and evade clients' unfortunate practices. Existing wellbeing observing methodologies despite everything face numerous challenges of restricted knowledge because of deficient medicinal services information. Hence, this article proposes a shrewd individual wellbeing counsel for comprehensive and clever wellbeing checking and direction. The monitoring of personal healthcare screens both physiological and mental conditions of the client. The Score obtained from this layout is expected to assess the general wellbeing status of the client. At last, a testbed for check of possibility and relevance of the proposed framework was created. The experimental and reproduction results have indicated that the ace presented approach is effective for appropriate client state checking.
{"title":"Monitoring Smart Devices for Personal Health Care Using Deep Analytics","authors":"K. Tharageswari, D.Selva Pandian, Laxmi Raja, R. Dhanapal","doi":"10.1109/I-SMAC49090.2020.9243413","DOIUrl":"https://doi.org/10.1109/I-SMAC49090.2020.9243413","url":null,"abstract":"As indicated by the Health foundations, illnesses brought about by an undesirable way of life speak to the main source of death everywhere throughout the world. Along these lines, it is pivotal to monitor and evade clients' unfortunate practices. Existing wellbeing observing methodologies despite everything face numerous challenges of restricted knowledge because of deficient medicinal services information. Hence, this article proposes a shrewd individual wellbeing counsel for comprehensive and clever wellbeing checking and direction. The monitoring of personal healthcare screens both physiological and mental conditions of the client. The Score obtained from this layout is expected to assess the general wellbeing status of the client. At last, a testbed for check of possibility and relevance of the proposed framework was created. The experimental and reproduction results have indicated that the ace presented approach is effective for appropriate client state checking.","PeriodicalId":432766,"journal":{"name":"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133688205","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 : 2020-10-07DOI: 10.1109/I-SMAC49090.2020.9243431
Komal P. Kansara, Bintu Kadhiwala
In today's world, trillions of persons are providing their data to social network data provider for connecting, interacting and data sharing with other users. The data provider may utilize these collected data for analysis purpose. Alternatively, multiple data providers prefer collaboration to attain enhanced analysis outcomes from the collected collaborated data. For such collaboration, the data providers do not share their data directly due to privacy issues instead they share the collected data with the trusted data publisher. The data publisher combines these collected data and subsequently publishes the data. Data collected at trusted data publisher site from multiple providers contain individuals' information that may be sensitive. Hence, the privacy of individuals may be compromised if it is published by the publisher in its original form. As a consequence, in literature, various non-cryptographic approaches are discussed for privacy-preserving collaborative social network data publishing. The motive of this paper is to emphasize the evaluation of these existing approaches with the help of different parameters.
{"title":"Non-cryptographic Approaches for Collaborative Social Network Data Publishing - A Survey","authors":"Komal P. Kansara, Bintu Kadhiwala","doi":"10.1109/I-SMAC49090.2020.9243431","DOIUrl":"https://doi.org/10.1109/I-SMAC49090.2020.9243431","url":null,"abstract":"In today's world, trillions of persons are providing their data to social network data provider for connecting, interacting and data sharing with other users. The data provider may utilize these collected data for analysis purpose. Alternatively, multiple data providers prefer collaboration to attain enhanced analysis outcomes from the collected collaborated data. For such collaboration, the data providers do not share their data directly due to privacy issues instead they share the collected data with the trusted data publisher. The data publisher combines these collected data and subsequently publishes the data. Data collected at trusted data publisher site from multiple providers contain individuals' information that may be sensitive. Hence, the privacy of individuals may be compromised if it is published by the publisher in its original form. As a consequence, in literature, various non-cryptographic approaches are discussed for privacy-preserving collaborative social network data publishing. The motive of this paper is to emphasize the evaluation of these existing approaches with the help of different parameters.","PeriodicalId":432766,"journal":{"name":"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115534699","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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