Mohammad Naderi Dehkordi - Academia.edu (original) (raw)

Papers by Mohammad Naderi Dehkordi

privacy preserving social network

— Enterprise Architecture is an approach for understanding, engineering, and managing all enterpr... more — Enterprise Architecture is an approach for understanding, engineering, and managing all enterprise elements and their relationships. In order to better explain the concepts defined in the quality attributes in enterprise architecture and their relationships, the quality scenarios are used. Because of the breadth and variety of enterprise architecture quality scenarios, the cost of implementation scenarios is high. Therefore, prioritization and selection of optimal scenarios, in terms of quality attributes satisfaction, before implementation, is very important. Due to the diversity of stakeholders, large number of scenarios and possible selections, prioritization scenarios involves searching a large state space and considering all of the possible selections which is not precise. Genetic Algorithm is the intelligent algorithm that solves the problems based on metaheuristic search. This paper presents an innovative method for prioritizing quality scenarios, based on the knowledge and...

By developing information technology and production methods and collecting data, a great amount o... more By developing information technology and production methods and collecting data, a great amount of data is daily being collected in commercial, medical databases. Some of this information is important with respect to competition concept in organizations and individual misuses. Nowadays in order to mine knowledge among a great amount of data, data mining tools are used. In order to protect information, fast processing and preventing from revealing private data to keep privacy is presented in data mining. In this article, some techniques in preserving privacy of association rule mining are introduced and some hiding algorithms of association rules are evaluated.

AbstractThis paper focuses on hiding sensitive association rule which is an important research pr... more AbstractThis paper focuses on hiding sensitive association rule which is an important research problem in privacy preserving data mining. For this, we present an algorithm that decreases confidence of sensitive rules to below minimum threshold by removing selective item among items of consequent sensitive rule (R.H.S) for each selective transaction. Finally, we qualitatively compare the efficiency of the proposed algorithm with that of already published algorithms in hiding association rules. *Author for correspondence

Association rule mining is one of the most important techniques of data mining that are used to e... more Association rule mining is one of the most important techniques of data mining that are used to extract the association patterns from large databases. Association rules are one of the most important assets of any organization that can be used for business development and profitability increase. Association rules contain sensitive information that threatens the privacy of its publication and they should be hidden before publishing the database. The aim of hiding association rules is to delete sensitive association rules from the published database so that possible side effects are reduced. In this paper, we present a heuristic algorithm DCR to hide sensitive association rules. In the proposed algorithm, two clustering operations are performed on the sensitive association rules and finally, a bunch of smaller clusters is chosen to hide. A selection of a smaller bunch of clusters reduces the changes in the database and side effects. The results of performing experiments on real databas...

Abstract—Text summarization is a process that reduces the size of the text document and extracts ... more Abstract—Text summarization is a process that reduces the size of the text document and extracts significant sentences from a text document. We present a novel technique for text summarization. The originality of technique lies on exploiting local and global properties of words and identifying significant words. The local property of word can be considered as the sum of normalized term frequency multiplied by its weight and normalized number of sentences containing that word multiplied by its weight. If local score of a word is less than local score threshold, we remove that word. Global property can be thought of as maximum semantic similarity between a word and title words. Also we introduce an iterative algorithm to identify significant words. This algorithm converges to the fixed number of significant words after some iterations and the number of iterations strongly depends on the text document. We used a two-layered backpropagation neural network with three neurons in the hidde...

Advances in Computer Science : an International Journal, 2015

Increasing use of data mining process and extracting of association rules caused the introduction... more Increasing use of data mining process and extracting of association rules caused the introduction of privacy preserving in data mining. A complete publication of the database is inconsistent with security policies and it would result in disclosure of some sensitive data after performing data mining. Individuals and organizations should secure the database before the publication, because if they neglect this issue they will be harmed. The owners of database consider factors such as database size, precision in immunization and velocity in choosing the right approach in order to hide the association rules. Besides the large volume of data and precision in immunization, we should optimize the time of operation and this is one of the issues that has received a little attention. In this paper, FHA algorithm is introduced for hiding sensitive patterns. In this algorithm, it is being tried to reduce the overload of ordering transactions by decreasing database scans. Also, we have reduced th...

Majlesi Journal of Electrical Engineering, 2016

Data mining has been used as a public utility in extracting knowledge from databases during recen... more Data mining has been used as a public utility in extracting knowledge from databases during recent years. Developments in data mining and availability of data and private information are the biggest challenge in this regard. Privacy preserving data mining is a response to this big challenge. The main purpose of techniques and algorithms in privacy preserving data mining is non-disclosure of sensitive and private data with minimum changes in databases so that it would not have adverse effects on the rest of data. The present paper intends to present a brief review of methods and techniques regarding privacy of data mining in association rules, their classification and finally, classification of hiding algorithms of association rules followed by a comparison between a numbers of these algorithms.

Security and Communication Networks

In social networks, preserving privacy and preserving correlation among sensitive labels are a ma... more In social networks, preserving privacy and preserving correlation among sensitive labels are a matter of trade-off. This paper presents a supervised anonymization technique, SNI (social network immunization), to publish social networks having multiple sensitive labels with correlation. SNI publishes all sensitive labels without distorting them. It publishes sensitive labels along with innovative labels named “partial sensitive labels” in an immune graph and multiple supplementary trees. These graph and trees, by itself or with the combination of other objects, supply correlation among sensitive labels for membership analysis. We present a framework along with an algorithm for extracting the immune graph and supplementary trees. These graph and trees minimize the membership error rate for membership analysis. The practical evaluation of the cancer code label of individuals also indicates the effectiveness of the SNI method.

Expert Systems with Applications

Abstract Privacy preserving data mining has been a major research subject in recent years. The mo... more Abstract Privacy preserving data mining has been a major research subject in recent years. The most important goal of this area is to protect personal information and prevent disclosure of this information during the data mining process. There are various techniques in the field of privacy preserving data mining. One of these techniques is association rules mining. The main purpose of association rules mining is to hide sensitive association rules. So far, various algorithms have been presented to this field in order to reach the purpose of sensitive association rules hiding. Each algorithm has its own specific functions and methods. To hide sensitive association rules, this paper presents an electromagnetic field optimization algorithm (EFO4ARH). This algorithm utilizes the data distortion technique to hide the sensitive association rules. In this algorithm, two fitness functions are used to reach the solution with the least side effects. Also, in this algorithm, the runtime has been reduced. This algorithm consists of a technique for exiting from local optima point and moving toward global optimal points. The performance of the proposed algorithm is evaluated by doing experiments on both real-world and synthetic datasets. Compared to four reference algorithms, the proposed algorithm shows a reduction in the side effects and better preservation of data quality. The performance of EFO4ARH is tested by standard deviation and mean Friedman ranks of error for standard functions (CEC benchmarks). In addition, hiding experiments show that our proposed algorithm outperforms existing hiding algorithms.

Expert Systems with Applications

Abstract Social networks provide an attractive environment in order to have low cost and easy com... more Abstract Social networks provide an attractive environment in order to have low cost and easy communication; however, analyzing huge amounts of produced data can considerably affect the user's privacy. In other words, an efficient algorithm should intelligently take the user's privacy into account while extracting data for useful information. In recent years, many studies have been conducted on social network privacy preservation for data publishing. However, the current algorithms are not one-time scan; that is, for every level of anonymization, the data set must be scanned again and this is a time-consuming operation. In order to address the above mentioned issue, the present research introduces a time-saving k-degree anonymization method in social network (TSRAM) that anonymizes the social network graph without having to rescan the data set for different levels of anonymity. First, it produces a tree from the data set. Then, the anonymized degree sequence of the graph is computed based on the tree. The proposed method employs an efficient approach to partition the node degrees. It takes advantage of partitioning the graph bottom-up nodes based on the anonymization levels. Moreover, it uses two effective criteria to increase the utility of the anonymized graph. Comparing to other similar techniques, the results show that TSRAM is effective, not only to make the degree sequence anonymization of the graph one-time scan, but also to preserve the utility of the anonymized graph.

Intelligent Systems, IS, International IEEE Conference, 2006

Recent studies in data mining have proposed a new classification approach, called associative cla... more Recent studies in data mining have proposed a new classification approach, called associative classification, which, according to several reports, such as Liu, B. et al (1998), achieves higher classification accuracy than traditional classification approaches such as C4.S However, the approach also suffers from two major deficiencies: (1) it generates a very large number of association rules, which leads to high

Privacy preserving data mining is a continues way for to use data mining, without disclosing priv... more Privacy preserving data mining is a continues way for to use data mining, without disclosing private information. To prevent disclosure of sensitive information by data mining techniques, it is necessary to make changes to the data base. Association rules are important and efficient data mining technique. In order to achieve this algorithm is proposed, that as well as hiding sensitive association rules, having the lowest side effects on the original data set. Proposed algorithm by removing selective item, among items of antecedent sensitive rule (L.H.S.), causes to decrease confidence of sensitive rule below less them threshold and hide the sensitive rule. Also keeps sensitive rules until the end of securing process is reduce the failure hiding, and because the internal clustering, hiding sensitive rules performed synchronic takes insensitive rules to reduce the loss. This algorithm is compared with basic algorithm, on dense and sparse data base. The results with criteria of hiding ...

Advances in Computer Science : an International Journal, 2015

By developing information technology and production methods and collecting data, a great amount o... more By developing information technology and production methods and collecting data, a great amount of data is daily being collected in commercial, medical databases. Some of this information is important with respect to competition concept in organizations and individual misuses. Nowadays in order to mine knowledge among a great amount of data, data mining tools are used. In order to protect information, fast processing and preventing from revealing private data to keep privacy is presented in data mining. In this article, some techniques in preserving privacy of association rule mining are introduced and some hiding algorithms of association rules are evaluated.

Enterprise Architecture is an approach for understanding, engineering, and managing all enterpris... more Enterprise Architecture is an approach for understanding, engineering, and managing all enterprise elements and their relationships. In order to better explain the concepts defined in the quality attributes in enterprise architecture and their relationships, the quality scenarios are used. Because of the breadth and variety of enterprise architecture quality scenarios, the cost of implementation scenarios is high. Therefore, prioritization and selection of optimal scenarios, in terms of quality attributes satisfaction, before implementation, is very important. Due to the diversity of stakeholders, large number of scenarios and possible selections, prioritization scenarios involves searching a large state space and considering all of the possible selections which is not precise. Genetic Algorithm is the intelligent algorithm that solves the problems based on metaheuristic search. This paper presents an innovative method for prioritizing quality scenarios, based on the knowledge and e...

Expert Systems with Applications

Advances in Computer Science : an International Journal, 2015

Association rule mining is one of the most important techniques of data mining that are used to e... more Association rule mining is one of the most important techniques of data mining that are used to extract the association patterns from large databases. Association rules are one of the most important assets of any organization that can be used for business development and profitability increase. Association rules contain sensitive information that threatens the privacy of its publication and they should be hidden before publishing the database. The aim of hiding association rules is to delete sensitive association rules from the published database so that possible side effects are reduced. In this paper, we present a heuristic algorithm DCR to hide sensitive association rules. In the proposed algorithm, two clustering operations are performed on the sensitive association rules and finally, a bunch of smaller clusters is chosen to hide. A selection of a smaller bunch of clusters reduces the changes in the database and side effects. The results of performing experiments on real databas...

Advances in Computer Science : an International Journal, 2014

Nowadays, data mining is a useful, yet dangerous technology through which useful information and ... more Nowadays, data mining is a useful, yet dangerous technology through which useful information and the relationships between items in a database are detected. Today, companies and users need to share information with others for their progress and they should somehow manage this information sharing for preserving sensitive information. Privacy preserving in data mining was introduced for managing information sharing. This paper presents a hybrid algorithm with distortion technique with both support-based and confidence-based approaches for privacy preserving. The proposed algorithm tries to maintain useful association rules and hide sensitive rules from the perspective of the database owner. It also has no limit on the number of items in the left-hand side and the right-hand side of rules. This paper also compares the proposed algorithm with MDSRRC algorithm and 1.b algorithm. The proposed algorithm has less lost rules compared with the MDSRRC and 1.b algorithms and its CPU usage is le...

Glaucoma is an eye disease that can lead to vision loss by damaging the optic nerve. Although thi... more Glaucoma is an eye disease that can lead to vision loss by damaging the optic nerve. Although this disease can often be prevented with early glaucoma detection, lack of discernible early symptoms makes the diagnosis difficult. Measuring the cup-to-disc ratio (CDR) is a common approach for glaucoma detection. Glaucoma can be specified by thinning the rim area that identifies the CDR value. Clustering and image segmentation can simply divide fundus images into distinct areas to estimate the optic disc (OD) and the optic cup (OC). This paper is based on a robust method, using the improved chaotic imperialistic competition algorithm (ICICA) for determining the position of the OD and OC on color fundus images for glaucoma detection. The predicted OD and OC boundaries are then used to estimate the CDR for glaucoma diagnosis. The performance of the proposed method was evaluated by using the publicly available RIGA dataset. It was found that some of the common problems of K-means clustering...

Privacy on social networks is one of the most important and well-known issues. Various algorithms... more Privacy on social networks is one of the most important and well-known issues. Various algorithms have been proposed to preserve the privacy of social network, all of which try to change the graph structure such that the utility of the graph is maintained. Although these algorithms have been successful in protecting the privacy and the utility of social networks, they are not suitable for anonymizing big data, because of the high cost of processing. Some of these algorithms have a high runtime. In addition, they should be improved from the aspect of preserving graph utility. In this paper, an effective algorithm has been introduced to increase the anonymization speed, as well as improving the graph utility. This algorithm uses number factorization to remove the best edges from the graph in the graph modification step of the algorithm. Since the appropriate edges are selected just through one scan of the edges, the runtime is reduced. In order to add edges to the graph, all the appro...

privacy preserving social network

— Enterprise Architecture is an approach for understanding, engineering, and managing all enterpr... more — Enterprise Architecture is an approach for understanding, engineering, and managing all enterprise elements and their relationships. In order to better explain the concepts defined in the quality attributes in enterprise architecture and their relationships, the quality scenarios are used. Because of the breadth and variety of enterprise architecture quality scenarios, the cost of implementation scenarios is high. Therefore, prioritization and selection of optimal scenarios, in terms of quality attributes satisfaction, before implementation, is very important. Due to the diversity of stakeholders, large number of scenarios and possible selections, prioritization scenarios involves searching a large state space and considering all of the possible selections which is not precise. Genetic Algorithm is the intelligent algorithm that solves the problems based on metaheuristic search. This paper presents an innovative method for prioritizing quality scenarios, based on the knowledge and...

By developing information technology and production methods and collecting data, a great amount o... more By developing information technology and production methods and collecting data, a great amount of data is daily being collected in commercial, medical databases. Some of this information is important with respect to competition concept in organizations and individual misuses. Nowadays in order to mine knowledge among a great amount of data, data mining tools are used. In order to protect information, fast processing and preventing from revealing private data to keep privacy is presented in data mining. In this article, some techniques in preserving privacy of association rule mining are introduced and some hiding algorithms of association rules are evaluated.

AbstractThis paper focuses on hiding sensitive association rule which is an important research pr... more AbstractThis paper focuses on hiding sensitive association rule which is an important research problem in privacy preserving data mining. For this, we present an algorithm that decreases confidence of sensitive rules to below minimum threshold by removing selective item among items of consequent sensitive rule (R.H.S) for each selective transaction. Finally, we qualitatively compare the efficiency of the proposed algorithm with that of already published algorithms in hiding association rules. *Author for correspondence

Association rule mining is one of the most important techniques of data mining that are used to e... more Association rule mining is one of the most important techniques of data mining that are used to extract the association patterns from large databases. Association rules are one of the most important assets of any organization that can be used for business development and profitability increase. Association rules contain sensitive information that threatens the privacy of its publication and they should be hidden before publishing the database. The aim of hiding association rules is to delete sensitive association rules from the published database so that possible side effects are reduced. In this paper, we present a heuristic algorithm DCR to hide sensitive association rules. In the proposed algorithm, two clustering operations are performed on the sensitive association rules and finally, a bunch of smaller clusters is chosen to hide. A selection of a smaller bunch of clusters reduces the changes in the database and side effects. The results of performing experiments on real databas...

Abstract—Text summarization is a process that reduces the size of the text document and extracts ... more Abstract—Text summarization is a process that reduces the size of the text document and extracts significant sentences from a text document. We present a novel technique for text summarization. The originality of technique lies on exploiting local and global properties of words and identifying significant words. The local property of word can be considered as the sum of normalized term frequency multiplied by its weight and normalized number of sentences containing that word multiplied by its weight. If local score of a word is less than local score threshold, we remove that word. Global property can be thought of as maximum semantic similarity between a word and title words. Also we introduce an iterative algorithm to identify significant words. This algorithm converges to the fixed number of significant words after some iterations and the number of iterations strongly depends on the text document. We used a two-layered backpropagation neural network with three neurons in the hidde...

Advances in Computer Science : an International Journal, 2015

Increasing use of data mining process and extracting of association rules caused the introduction... more Increasing use of data mining process and extracting of association rules caused the introduction of privacy preserving in data mining. A complete publication of the database is inconsistent with security policies and it would result in disclosure of some sensitive data after performing data mining. Individuals and organizations should secure the database before the publication, because if they neglect this issue they will be harmed. The owners of database consider factors such as database size, precision in immunization and velocity in choosing the right approach in order to hide the association rules. Besides the large volume of data and precision in immunization, we should optimize the time of operation and this is one of the issues that has received a little attention. In this paper, FHA algorithm is introduced for hiding sensitive patterns. In this algorithm, it is being tried to reduce the overload of ordering transactions by decreasing database scans. Also, we have reduced th...

Majlesi Journal of Electrical Engineering, 2016

Data mining has been used as a public utility in extracting knowledge from databases during recen... more Data mining has been used as a public utility in extracting knowledge from databases during recent years. Developments in data mining and availability of data and private information are the biggest challenge in this regard. Privacy preserving data mining is a response to this big challenge. The main purpose of techniques and algorithms in privacy preserving data mining is non-disclosure of sensitive and private data with minimum changes in databases so that it would not have adverse effects on the rest of data. The present paper intends to present a brief review of methods and techniques regarding privacy of data mining in association rules, their classification and finally, classification of hiding algorithms of association rules followed by a comparison between a numbers of these algorithms.

Security and Communication Networks

In social networks, preserving privacy and preserving correlation among sensitive labels are a ma... more In social networks, preserving privacy and preserving correlation among sensitive labels are a matter of trade-off. This paper presents a supervised anonymization technique, SNI (social network immunization), to publish social networks having multiple sensitive labels with correlation. SNI publishes all sensitive labels without distorting them. It publishes sensitive labels along with innovative labels named “partial sensitive labels” in an immune graph and multiple supplementary trees. These graph and trees, by itself or with the combination of other objects, supply correlation among sensitive labels for membership analysis. We present a framework along with an algorithm for extracting the immune graph and supplementary trees. These graph and trees minimize the membership error rate for membership analysis. The practical evaluation of the cancer code label of individuals also indicates the effectiveness of the SNI method.

Expert Systems with Applications

Abstract Privacy preserving data mining has been a major research subject in recent years. The mo... more Abstract Privacy preserving data mining has been a major research subject in recent years. The most important goal of this area is to protect personal information and prevent disclosure of this information during the data mining process. There are various techniques in the field of privacy preserving data mining. One of these techniques is association rules mining. The main purpose of association rules mining is to hide sensitive association rules. So far, various algorithms have been presented to this field in order to reach the purpose of sensitive association rules hiding. Each algorithm has its own specific functions and methods. To hide sensitive association rules, this paper presents an electromagnetic field optimization algorithm (EFO4ARH). This algorithm utilizes the data distortion technique to hide the sensitive association rules. In this algorithm, two fitness functions are used to reach the solution with the least side effects. Also, in this algorithm, the runtime has been reduced. This algorithm consists of a technique for exiting from local optima point and moving toward global optimal points. The performance of the proposed algorithm is evaluated by doing experiments on both real-world and synthetic datasets. Compared to four reference algorithms, the proposed algorithm shows a reduction in the side effects and better preservation of data quality. The performance of EFO4ARH is tested by standard deviation and mean Friedman ranks of error for standard functions (CEC benchmarks). In addition, hiding experiments show that our proposed algorithm outperforms existing hiding algorithms.

Expert Systems with Applications

Abstract Social networks provide an attractive environment in order to have low cost and easy com... more Abstract Social networks provide an attractive environment in order to have low cost and easy communication; however, analyzing huge amounts of produced data can considerably affect the user's privacy. In other words, an efficient algorithm should intelligently take the user's privacy into account while extracting data for useful information. In recent years, many studies have been conducted on social network privacy preservation for data publishing. However, the current algorithms are not one-time scan; that is, for every level of anonymization, the data set must be scanned again and this is a time-consuming operation. In order to address the above mentioned issue, the present research introduces a time-saving k-degree anonymization method in social network (TSRAM) that anonymizes the social network graph without having to rescan the data set for different levels of anonymity. First, it produces a tree from the data set. Then, the anonymized degree sequence of the graph is computed based on the tree. The proposed method employs an efficient approach to partition the node degrees. It takes advantage of partitioning the graph bottom-up nodes based on the anonymization levels. Moreover, it uses two effective criteria to increase the utility of the anonymized graph. Comparing to other similar techniques, the results show that TSRAM is effective, not only to make the degree sequence anonymization of the graph one-time scan, but also to preserve the utility of the anonymized graph.

Intelligent Systems, IS, International IEEE Conference, 2006

Recent studies in data mining have proposed a new classification approach, called associative cla... more Recent studies in data mining have proposed a new classification approach, called associative classification, which, according to several reports, such as Liu, B. et al (1998), achieves higher classification accuracy than traditional classification approaches such as C4.S However, the approach also suffers from two major deficiencies: (1) it generates a very large number of association rules, which leads to high

Privacy preserving data mining is a continues way for to use data mining, without disclosing priv... more Privacy preserving data mining is a continues way for to use data mining, without disclosing private information. To prevent disclosure of sensitive information by data mining techniques, it is necessary to make changes to the data base. Association rules are important and efficient data mining technique. In order to achieve this algorithm is proposed, that as well as hiding sensitive association rules, having the lowest side effects on the original data set. Proposed algorithm by removing selective item, among items of antecedent sensitive rule (L.H.S.), causes to decrease confidence of sensitive rule below less them threshold and hide the sensitive rule. Also keeps sensitive rules until the end of securing process is reduce the failure hiding, and because the internal clustering, hiding sensitive rules performed synchronic takes insensitive rules to reduce the loss. This algorithm is compared with basic algorithm, on dense and sparse data base. The results with criteria of hiding ...

Advances in Computer Science : an International Journal, 2015

By developing information technology and production methods and collecting data, a great amount o... more By developing information technology and production methods and collecting data, a great amount of data is daily being collected in commercial, medical databases. Some of this information is important with respect to competition concept in organizations and individual misuses. Nowadays in order to mine knowledge among a great amount of data, data mining tools are used. In order to protect information, fast processing and preventing from revealing private data to keep privacy is presented in data mining. In this article, some techniques in preserving privacy of association rule mining are introduced and some hiding algorithms of association rules are evaluated.

Enterprise Architecture is an approach for understanding, engineering, and managing all enterpris... more Enterprise Architecture is an approach for understanding, engineering, and managing all enterprise elements and their relationships. In order to better explain the concepts defined in the quality attributes in enterprise architecture and their relationships, the quality scenarios are used. Because of the breadth and variety of enterprise architecture quality scenarios, the cost of implementation scenarios is high. Therefore, prioritization and selection of optimal scenarios, in terms of quality attributes satisfaction, before implementation, is very important. Due to the diversity of stakeholders, large number of scenarios and possible selections, prioritization scenarios involves searching a large state space and considering all of the possible selections which is not precise. Genetic Algorithm is the intelligent algorithm that solves the problems based on metaheuristic search. This paper presents an innovative method for prioritizing quality scenarios, based on the knowledge and e...

Expert Systems with Applications

Advances in Computer Science : an International Journal, 2015

Association rule mining is one of the most important techniques of data mining that are used to e... more Association rule mining is one of the most important techniques of data mining that are used to extract the association patterns from large databases. Association rules are one of the most important assets of any organization that can be used for business development and profitability increase. Association rules contain sensitive information that threatens the privacy of its publication and they should be hidden before publishing the database. The aim of hiding association rules is to delete sensitive association rules from the published database so that possible side effects are reduced. In this paper, we present a heuristic algorithm DCR to hide sensitive association rules. In the proposed algorithm, two clustering operations are performed on the sensitive association rules and finally, a bunch of smaller clusters is chosen to hide. A selection of a smaller bunch of clusters reduces the changes in the database and side effects. The results of performing experiments on real databas...

Advances in Computer Science : an International Journal, 2014

Nowadays, data mining is a useful, yet dangerous technology through which useful information and ... more Nowadays, data mining is a useful, yet dangerous technology through which useful information and the relationships between items in a database are detected. Today, companies and users need to share information with others for their progress and they should somehow manage this information sharing for preserving sensitive information. Privacy preserving in data mining was introduced for managing information sharing. This paper presents a hybrid algorithm with distortion technique with both support-based and confidence-based approaches for privacy preserving. The proposed algorithm tries to maintain useful association rules and hide sensitive rules from the perspective of the database owner. It also has no limit on the number of items in the left-hand side and the right-hand side of rules. This paper also compares the proposed algorithm with MDSRRC algorithm and 1.b algorithm. The proposed algorithm has less lost rules compared with the MDSRRC and 1.b algorithms and its CPU usage is le...

Glaucoma is an eye disease that can lead to vision loss by damaging the optic nerve. Although thi... more Glaucoma is an eye disease that can lead to vision loss by damaging the optic nerve. Although this disease can often be prevented with early glaucoma detection, lack of discernible early symptoms makes the diagnosis difficult. Measuring the cup-to-disc ratio (CDR) is a common approach for glaucoma detection. Glaucoma can be specified by thinning the rim area that identifies the CDR value. Clustering and image segmentation can simply divide fundus images into distinct areas to estimate the optic disc (OD) and the optic cup (OC). This paper is based on a robust method, using the improved chaotic imperialistic competition algorithm (ICICA) for determining the position of the OD and OC on color fundus images for glaucoma detection. The predicted OD and OC boundaries are then used to estimate the CDR for glaucoma diagnosis. The performance of the proposed method was evaluated by using the publicly available RIGA dataset. It was found that some of the common problems of K-means clustering...

Privacy on social networks is one of the most important and well-known issues. Various algorithms... more Privacy on social networks is one of the most important and well-known issues. Various algorithms have been proposed to preserve the privacy of social network, all of which try to change the graph structure such that the utility of the graph is maintained. Although these algorithms have been successful in protecting the privacy and the utility of social networks, they are not suitable for anonymizing big data, because of the high cost of processing. Some of these algorithms have a high runtime. In addition, they should be improved from the aspect of preserving graph utility. In this paper, an effective algorithm has been introduced to increase the anonymization speed, as well as improving the graph utility. This algorithm uses number factorization to remove the best edges from the graph in the graph modification step of the algorithm. Since the appropriate edges are selected just through one scan of the edges, the runtime is reduced. In order to add edges to the graph, all the appro...