Pub Date : 2017-11-01DOI: 10.1109/ICRCICN.2017.8234520
Swapan Santra, S. Paul
Power system stabilizer (PSS) is extensively used to enhance the angular stability by providing damping to the generator's oscillation. An electric torque is enforced in the rotor shaft in phase with the speed variation to provide this damping. In this paper a PSO based Robust Power System Stabilizer (RPSS) design has been proposed depending upon mixed sensitivity based H output feedback control in linear matrix inequality (LMI) framework. In this approach, PSO based norm minimization technique is applied for weighting function and controller parameter selection. In controller parameter selection, H∞/H2 multi objective control has been proposed. The efficacy of the RPSS, designed through approach has been investigated by simulation of a single machine associated with infinite bus scheme for various loading conditions employing MATLAB.
{"title":"PSO based robust power system stabilizer design using mixed sensitivity based H output-feedback control in LMI approach","authors":"Swapan Santra, S. Paul","doi":"10.1109/ICRCICN.2017.8234520","DOIUrl":"https://doi.org/10.1109/ICRCICN.2017.8234520","url":null,"abstract":"Power system stabilizer (PSS) is extensively used to enhance the angular stability by providing damping to the generator's oscillation. An electric torque is enforced in the rotor shaft in phase with the speed variation to provide this damping. In this paper a PSO based Robust Power System Stabilizer (RPSS) design has been proposed depending upon mixed sensitivity based H output feedback control in linear matrix inequality (LMI) framework. In this approach, PSO based norm minimization technique is applied for weighting function and controller parameter selection. In controller parameter selection, H∞/H2 multi objective control has been proposed. The efficacy of the RPSS, designed through approach has been investigated by simulation of a single machine associated with infinite bus scheme for various loading conditions employing MATLAB.","PeriodicalId":166298,"journal":{"name":"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126891524","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 : 2017-11-01DOI: 10.1109/ICRCICN.2017.8234516
Priyanka Nath, Sumran Kilam, A. Swetapadma
In this work a machine learning approach is proposed for prediction of volatile substance abuse. Machine learning technique used in this work is artificial neural networks (ANN). Two ANN modules are designed, ANN-D to predict whether a person is using VSA or not and ANN-C to predict the time of use. Input features used are age, gender, country, ethnicity, education, neuroticism, openness to experience, extraversion, agreeableness, conscientiousness, impulsiveness, sensation seeking etc. Input features are given to the ANN-Dmodule to predict if volatile substance abuse (VSA) has been done by the person or not. ANN-C module predicts the use of VSA in terms of time such as day, week, month, year, decade, beforea decade, etc. The accuracy of the ANN-D module is found to be 81% and ANN-C module is 71.9%. Hence the proposed method can be used for drug analysis to some extent.
{"title":"A machine learning approach to predict volatile substance abuse for drug risk analysis","authors":"Priyanka Nath, Sumran Kilam, A. Swetapadma","doi":"10.1109/ICRCICN.2017.8234516","DOIUrl":"https://doi.org/10.1109/ICRCICN.2017.8234516","url":null,"abstract":"In this work a machine learning approach is proposed for prediction of volatile substance abuse. Machine learning technique used in this work is artificial neural networks (ANN). Two ANN modules are designed, ANN-D to predict whether a person is using VSA or not and ANN-C to predict the time of use. Input features used are age, gender, country, ethnicity, education, neuroticism, openness to experience, extraversion, agreeableness, conscientiousness, impulsiveness, sensation seeking etc. Input features are given to the ANN-Dmodule to predict if volatile substance abuse (VSA) has been done by the person or not. ANN-C module predicts the use of VSA in terms of time such as day, week, month, year, decade, beforea decade, etc. The accuracy of the ANN-D module is found to be 81% and ANN-C module is 71.9%. Hence the proposed method can be used for drug analysis to some extent.","PeriodicalId":166298,"journal":{"name":"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125991269","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 : 2017-11-01DOI: 10.1109/ICRCICN.2017.8234491
Dr. Naween Kumar, D. Dash
Recently, several studies have considered the use of mobile sink (MS) for data gathering in wireless sensor networks. As, it can enhance lifetime of the sensor network by distributing load among the sensors. In some delay-critical applications, a mobile sink is allowed to move along a predefined path. However, due to the predefined path and relatively slower speed of mobile sink, data gathering from sensors may delayed. Thus, time-sensitive data collection in a constrained path environment using mobile sink has increased attention in the research community. Our proposed paper focuses on finding a sub-path on a given path in the network such that the mobile sink can collect maximum data from the network within given time. We refer it as maximum data gathering by optimal sub-path finding problem (MDGOSP). We develop a deterministic algorithm to solve it. Furthermore, performance of the proposed algorithm is validated through simulation experiments using MATLAB.
{"title":"Time-sensitive data collection with path-constrained mobile sink in WSN","authors":"Dr. Naween Kumar, D. Dash","doi":"10.1109/ICRCICN.2017.8234491","DOIUrl":"https://doi.org/10.1109/ICRCICN.2017.8234491","url":null,"abstract":"Recently, several studies have considered the use of mobile sink (MS) for data gathering in wireless sensor networks. As, it can enhance lifetime of the sensor network by distributing load among the sensors. In some delay-critical applications, a mobile sink is allowed to move along a predefined path. However, due to the predefined path and relatively slower speed of mobile sink, data gathering from sensors may delayed. Thus, time-sensitive data collection in a constrained path environment using mobile sink has increased attention in the research community. Our proposed paper focuses on finding a sub-path on a given path in the network such that the mobile sink can collect maximum data from the network within given time. We refer it as maximum data gathering by optimal sub-path finding problem (MDGOSP). We develop a deterministic algorithm to solve it. Furthermore, performance of the proposed algorithm is validated through simulation experiments using MATLAB.","PeriodicalId":166298,"journal":{"name":"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126001874","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 : 2017-11-01DOI: 10.1109/ICRCICN.2017.8234521
D. Mishra, T. Panigrahi, A. Mohanty, P. Ray
Present work introduces a most popular evolution based algorithm and applied in two degree of freedom proportional integral Derivative (TDOFPID) Controller based multi area power system. Differential Evolution (DE) optimization technique is applied here to tune the TDOFPID gains. In each area of system consists of Automatic generation control with addition of non-linarites. In this model time delay, Generation rate constraints (GRC) and reheat turbine is added to make non-linearity. At first attempt simulation is being done in two area with DE optimistion technique. Next attempt a series connected Flexible Alternating Current Transmission (FACT) device such as Interline Power Flow Control (IPFC) is included into the system and simulated. DE is also used to get the optimum value of TDOFPID controller having Integral time absolute error (ITAE) has been the objective function. At last robustness analysis is done with varying parameter and different loading conditions. It is seen that, TDOFPID with IPFC gives better response compared to others.
{"title":"Multi-area interconnected automatic generation control with IPFC and TDOFPID controller","authors":"D. Mishra, T. Panigrahi, A. Mohanty, P. Ray","doi":"10.1109/ICRCICN.2017.8234521","DOIUrl":"https://doi.org/10.1109/ICRCICN.2017.8234521","url":null,"abstract":"Present work introduces a most popular evolution based algorithm and applied in two degree of freedom proportional integral Derivative (TDOFPID) Controller based multi area power system. Differential Evolution (DE) optimization technique is applied here to tune the TDOFPID gains. In each area of system consists of Automatic generation control with addition of non-linarites. In this model time delay, Generation rate constraints (GRC) and reheat turbine is added to make non-linearity. At first attempt simulation is being done in two area with DE optimistion technique. Next attempt a series connected Flexible Alternating Current Transmission (FACT) device such as Interline Power Flow Control (IPFC) is included into the system and simulated. DE is also used to get the optimum value of TDOFPID controller having Integral time absolute error (ITAE) has been the objective function. At last robustness analysis is done with varying parameter and different loading conditions. It is seen that, TDOFPID with IPFC gives better response compared to others.","PeriodicalId":166298,"journal":{"name":"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127404896","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 : 2017-11-01DOI: 10.1109/ICRCICN.2017.8234475
S. Dhar, Hiranmoy Roy, M. Majumder, Chitrita Biswas, Anindita Sarkar
Underwater image segmentation becomes a difficult and challenging task due to various perturbations present in the water. In this paper we propose a novel method for underwater image segmentation based on M-band wavelet transform and human psychovisual phenomenon(HVS). The M-band wavelet transform captures the texture of the underwater image by decomposing the image into sub bands with different scales and orientations. The proper sub bands for segmentation are selected depending on the HVS. The HVS imitates the original visual technique of a human being and it is used to divide each sub band into Weber, De-Vries Rose and Saturation regions. A sub band is selected for segmentation depending on those three regions. The performance of the proposed method is found to be superior than that of the stare-of-the-art methods for underwater image segmentation on standard data set.
{"title":"A novel method for underwater image segmentation based on M-band wavelet transform and human psychovisual phenomenon(HVS)","authors":"S. Dhar, Hiranmoy Roy, M. Majumder, Chitrita Biswas, Anindita Sarkar","doi":"10.1109/ICRCICN.2017.8234475","DOIUrl":"https://doi.org/10.1109/ICRCICN.2017.8234475","url":null,"abstract":"Underwater image segmentation becomes a difficult and challenging task due to various perturbations present in the water. In this paper we propose a novel method for underwater image segmentation based on M-band wavelet transform and human psychovisual phenomenon(HVS). The M-band wavelet transform captures the texture of the underwater image by decomposing the image into sub bands with different scales and orientations. The proper sub bands for segmentation are selected depending on the HVS. The HVS imitates the original visual technique of a human being and it is used to divide each sub band into Weber, De-Vries Rose and Saturation regions. A sub band is selected for segmentation depending on those three regions. The performance of the proposed method is found to be superior than that of the stare-of-the-art methods for underwater image segmentation on standard data set.","PeriodicalId":166298,"journal":{"name":"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125221311","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 : 2017-11-01DOI: 10.1109/ICRCICN.2017.8234472
D. Mandal, Arpitam Chatterjee, B. Tudu
Turmeric quality mainly depends on Curcumin which not only imparts yellow color of turmeric but also the principal Curcuminod of turmeric. Chemicals with yellow colors e.g. Metanil yellow are often mixed to turmeric powder for achieving the attractive yellow color without much change in taste. Consumption of adulterant can cause health hazards. The detection of unwanted mixing of adulterant with food is vital but difficult to achieve manually. The paper presents a machine vision based approach for detection of adulterant with turmeric powder. The frequency domain analysis of color projection features along with principal component analysis is being performed in this paper for identification between adulterant mixed and unmixed verities of turmeric powder samples. Here a class separability measure is used to find the separation index to validate the class separation objectively. The experimental results show that the presented method may be considered as a potential tool.
{"title":"A machine vision based approach towards identification of adulterant in turmeric powder","authors":"D. Mandal, Arpitam Chatterjee, B. Tudu","doi":"10.1109/ICRCICN.2017.8234472","DOIUrl":"https://doi.org/10.1109/ICRCICN.2017.8234472","url":null,"abstract":"Turmeric quality mainly depends on Curcumin which not only imparts yellow color of turmeric but also the principal Curcuminod of turmeric. Chemicals with yellow colors e.g. Metanil yellow are often mixed to turmeric powder for achieving the attractive yellow color without much change in taste. Consumption of adulterant can cause health hazards. The detection of unwanted mixing of adulterant with food is vital but difficult to achieve manually. The paper presents a machine vision based approach for detection of adulterant with turmeric powder. The frequency domain analysis of color projection features along with principal component analysis is being performed in this paper for identification between adulterant mixed and unmixed verities of turmeric powder samples. Here a class separability measure is used to find the separation index to validate the class separation objectively. The experimental results show that the presented method may be considered as a potential tool.","PeriodicalId":166298,"journal":{"name":"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131535677","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 : 2017-11-01DOI: 10.1109/ICRCICN.2017.8234508
Purbanka Pahari, Piyali Basak, Anasua Sarkar
Pancreatic ductal adenocarcinoma (PDAC) is one of most aggressive malignancy. The identification of Biomarker for PDAC is an ongoing challenge. The high dimensional PDAC gene expression dataset in Gene Expression Omnibus(GEO) database, is analyzed in this work. To select those genes which are relevant as well as with least redundancy among them, we use successive approaches like Filter methods and Normalization phase. In this work, after pre-processing of the data, we have used three types of spectral clustering methods, Unnormalized, Ng-Jordan and proposed entropy based Shi-Malik spectral clustering algorithms to find important genetic and biological information. There we have applied new Shannon's Entropy based distance measure to identify the clusters on Pancreatic dataset. Some Biomarkers are identified through KEGG Pathway analysis. The Biological analysis and functional correlation of genes based on Gene Ontology(GO) terms show that the proposed method is helpful for the selection of Biomarkers.
{"title":"Biomarker detection on Pancreatic cancer dataset using entropy based spectral clustering","authors":"Purbanka Pahari, Piyali Basak, Anasua Sarkar","doi":"10.1109/ICRCICN.2017.8234508","DOIUrl":"https://doi.org/10.1109/ICRCICN.2017.8234508","url":null,"abstract":"Pancreatic ductal adenocarcinoma (PDAC) is one of most aggressive malignancy. The identification of Biomarker for PDAC is an ongoing challenge. The high dimensional PDAC gene expression dataset in Gene Expression Omnibus(GEO) database, is analyzed in this work. To select those genes which are relevant as well as with least redundancy among them, we use successive approaches like Filter methods and Normalization phase. In this work, after pre-processing of the data, we have used three types of spectral clustering methods, Unnormalized, Ng-Jordan and proposed entropy based Shi-Malik spectral clustering algorithms to find important genetic and biological information. There we have applied new Shannon's Entropy based distance measure to identify the clusters on Pancreatic dataset. Some Biomarkers are identified through KEGG Pathway analysis. The Biological analysis and functional correlation of genes based on Gene Ontology(GO) terms show that the proposed method is helpful for the selection of Biomarkers.","PeriodicalId":166298,"journal":{"name":"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127274199","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 : 2017-11-01DOI: 10.1109/ICRCICN.2017.8234536
Tamojit Saha, Sandeepan Sengupta, Tanmoy Dasgupta
Steganography is a form of secret communication in which a secret message (text, image) is hidden inside a carrier message (text, image). While in cryptography, the goal is to make everything unreadable to the ones who do not know the password, in steganography, on the other hand, the goal is to camouflage a message inside an apparently innocent carrier. In other words, while cryptography conceals the message itself, steganography conceals the existence of the message. Since, this form of communication potentially attracts unsavoury people to secretly hide messages in plain sight, there have been many efforts on different fronts to detect the possibility of the existence of steganography in images and other multimedia objects. Most of such algorithms use different statistical analysis based attacks for detecting potential cases of steganography. In light of this, the present methodology demonstrates the development of a set of algorithms designed to implement a spatial domain steganography technique that is capable of withstanding such attacks. The merits of the present methodology has also been assessed quantitatively.
{"title":"Chaotic cipher based spatial domain steganography with strong resistance against statistical attacks","authors":"Tamojit Saha, Sandeepan Sengupta, Tanmoy Dasgupta","doi":"10.1109/ICRCICN.2017.8234536","DOIUrl":"https://doi.org/10.1109/ICRCICN.2017.8234536","url":null,"abstract":"Steganography is a form of secret communication in which a secret message (text, image) is hidden inside a carrier message (text, image). While in cryptography, the goal is to make everything unreadable to the ones who do not know the password, in steganography, on the other hand, the goal is to camouflage a message inside an apparently innocent carrier. In other words, while cryptography conceals the message itself, steganography conceals the existence of the message. Since, this form of communication potentially attracts unsavoury people to secretly hide messages in plain sight, there have been many efforts on different fronts to detect the possibility of the existence of steganography in images and other multimedia objects. Most of such algorithms use different statistical analysis based attacks for detecting potential cases of steganography. In light of this, the present methodology demonstrates the development of a set of algorithms designed to implement a spatial domain steganography technique that is capable of withstanding such attacks. The merits of the present methodology has also been assessed quantitatively.","PeriodicalId":166298,"journal":{"name":"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128181665","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 : 2017-11-01DOI: 10.1109/ICRCICN.2017.8234514
Sobhan Sarkar, Soumyadeep Baidya, J. Maiti
Though accident data have been collected across industries, they may inherently contain uncertainty of randomness and fuzziness which in turn leads to misleading interpretation of the analysis. To handle the issue of uncertainty within accident data, the present work proposes a rough set theory (RST)-based approach to provide rule-based solution to the industry to minimize the number of accidents at work. Using RST and RST-based rule generation algorithm Learning by Example Module: Version 2 (LEM2), 279 important rules are extracted from the accident data obtained from an integrated steel industry to analyze the incident outcomes (injury, near miss and property damage). The results of the proposed methodology explore some of the important findings which are useful for the industry perspective. Therefore, the RST-based approach can be effective and efficient as well because of its potential to produce good results in the presence of uncertainty in data.
虽然事故数据是跨行业收集的，但它们可能固有地包含随机性和模糊性的不确定性，从而导致对分析的误导性解释。为了处理事故数据中的不确定性问题，本工作提出了一种基于粗糙集理论(RST)的方法，为行业提供基于规则的解决方案，以最大限度地减少工作中的事故数量。利用RST和基于RST的规则生成算法LEM2 (Learning by Example Module: Version 2)，从某综合钢铁行业的事故数据中提取279条重要规则，对事故结果(伤害、险些和财产损失)进行分析。提出的方法的结果探讨了一些重要的发现，这些发现对行业的观点是有用的。因此，基于rst的方法也是有效和高效的，因为它有可能在数据存在不确定性的情况下产生良好的结果。
{"title":"Application of rough set theory in accident analysis at work: A case study","authors":"Sobhan Sarkar, Soumyadeep Baidya, J. Maiti","doi":"10.1109/ICRCICN.2017.8234514","DOIUrl":"https://doi.org/10.1109/ICRCICN.2017.8234514","url":null,"abstract":"Though accident data have been collected across industries, they may inherently contain uncertainty of randomness and fuzziness which in turn leads to misleading interpretation of the analysis. To handle the issue of uncertainty within accident data, the present work proposes a rough set theory (RST)-based approach to provide rule-based solution to the industry to minimize the number of accidents at work. Using RST and RST-based rule generation algorithm Learning by Example Module: Version 2 (LEM2), 279 important rules are extracted from the accident data obtained from an integrated steel industry to analyze the incident outcomes (injury, near miss and property damage). The results of the proposed methodology explore some of the important findings which are useful for the industry perspective. Therefore, the RST-based approach can be effective and efficient as well because of its potential to produce good results in the presence of uncertainty in data.","PeriodicalId":166298,"journal":{"name":"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132280909","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 : 2017-11-01DOI: 10.1109/ICRCICN.2017.8234526
Ramkrishna Das, S. Dutta
Steganography is the practice of concealing information of one object within other non secret object. We replace least significant bits from enveloped image with the bits of original image at the time of LSB based image steganography. This approach is not as secured as retrieving the least significant bits from the enveloped image will provide all the information of original image. So in the proposed system, we rearrange all the pixels of the original and the enveloped image using prime and non-prime positions of the pixels. Again we reposition all the pixels using one of the user defined pixel repositioning algorithms (PRONE (positional reverse odd normal even), PRENO (positional reverse even normal odd), CRENO (continuous reverse even normal odd), CRONE (continuous reverse odd normal even)) chosen by the user for original and enveloped image separately. Lastly we perform user defined BWMAS operation (Bitwise Masking & Alternate Sequence) between the bits of original image and the least significant bits of the enveloped image. As all the pixels of both enveloped and original images are repositioned, so the pixels from original image are chosen actually in non sequential manner and the pixels, taken from enveloped image for BWMAS operation are also in non sequential manner. Only the proper sequences of the encrypted pixels defined by the user defined algorithms are being able to retrieve the information of the original image. We introduce Bitwise Masking & Alternate Sequence operation for the first time in state of XOR operation. Thus an attempt is made to increase the security of the image encryption system.
{"title":"An approach for secured image encryption scheme using user defined operator based steganographic technique with pixels repositioning schemes","authors":"Ramkrishna Das, S. Dutta","doi":"10.1109/ICRCICN.2017.8234526","DOIUrl":"https://doi.org/10.1109/ICRCICN.2017.8234526","url":null,"abstract":"Steganography is the practice of concealing information of one object within other non secret object. We replace least significant bits from enveloped image with the bits of original image at the time of LSB based image steganography. This approach is not as secured as retrieving the least significant bits from the enveloped image will provide all the information of original image. So in the proposed system, we rearrange all the pixels of the original and the enveloped image using prime and non-prime positions of the pixels. Again we reposition all the pixels using one of the user defined pixel repositioning algorithms (PRONE (positional reverse odd normal even), PRENO (positional reverse even normal odd), CRENO (continuous reverse even normal odd), CRONE (continuous reverse odd normal even)) chosen by the user for original and enveloped image separately. Lastly we perform user defined BWMAS operation (Bitwise Masking & Alternate Sequence) between the bits of original image and the least significant bits of the enveloped image. As all the pixels of both enveloped and original images are repositioned, so the pixels from original image are chosen actually in non sequential manner and the pixels, taken from enveloped image for BWMAS operation are also in non sequential manner. Only the proper sequences of the encrypted pixels defined by the user defined algorithms are being able to retrieve the information of the original image. We introduce Bitwise Masking & Alternate Sequence operation for the first time in state of XOR operation. Thus an attempt is made to increase the security of the image encryption system.","PeriodicalId":166298,"journal":{"name":"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125225259","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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