Data Leakage Detection and Security Using Cloud Computing (original) (raw)
Related papers
DROPS: Division and Replication of Data in Cloud for Optimal Performance and Security
IEEE Transactions on Cloud Computing, 2018
Outsourcing data to a third-party administrative control, as is done in cloud computing, gives rise to security concerns. The data compromise may occur due to attacks by other users and nodes within the cloud. Therefore, high security measures are required to protect data within the cloud. However, the employed security strategy must also take into account the optimization of the data retrieval time. In this paper, we propose Division and Replication of Data in the Cloud for Optimal Performance and Security (DROPS) that collectively approaches the security and performance issues. In the DROPS methodology, we divide a file into fragments, and replicate the fragmented data over the cloud nodes. Each of the nodes stores only a single fragment of a particular data file that ensures that even in case of a successful attack, no meaningful information is revealed to the attacker. Moreover, the nodes storing the fragments, are separated with certain distance by means of graph T-coloring to prohibit an attacker of guessing the locations of the fragments. Furthermore, the DROPS methodology does not rely on the traditional cryptographic techniques for the data security; thereby relieving the system of computationally expensive methodologies. We show that the probability to locate and compromise all of the nodes storing the fragments of a single file is extremely low. We also compare the performance of the DROPS methodology with ten other schemes. The higher level of security with slight performance overhead was observed.
International Journal of Advanced Research in Computer Science, 2018
Cloud computing is an information technology paradigm model which offers clients access to shared pool of resources. Replication and division of data takes into consideration the performance and security issues. A given file is divided into fragments and then replicated. They are placed over the nodes (servers) and every node stores a single fragment of data in order to improve security. The nodes that store the replicas and fragments are not adjacent to each other by applying T-coloring method hence preventing the attacker from gaining access to useful information. The user can download the file from anywhere but has to specify the exact location as well as the time and date in order to get maximum security as compared to other systems. The likelihood of finding andcompromising the nodes that store the fragments of a file is very low.
Optimal Performance and Security in Cloud Using Division and Replication of Data
– Outsourcing data to a third-party managerial control, as is done in cloud compute, gives rise to security concerns. The data compromise may occur due to attacks by other users and nodes within the cloud. Therefore, high security measures are required to protect data within the cloud. However, the employed security strategy must also take into account the optimization of the data retrieval time. In this paper, we propose Division and Replication of Data in the Cloud for Optimal Performance and Security (DROPS) that collectively approaches the security and presentation issues. In the DROPS methodology, we divide a file into fragments, and replicate the fragmented data over the cloud nodes. Each of the nodes stores only a single fragment of a particular data file that ensures that even in case of a successful attack, no meaningful information is revealed to the attacker. Moreover, the nodes storing the fragments, are separated with certain distance by means of graph T-coloring to prohibit an attacker of guessing the locations of the fragments. Furthermore, the DROPS methodology does not rely on the traditional cryptographic techniques for the data security; thereby relieving the system of computationally expensive methodologies. We show that the probability to locate and compromise all of the nodes storing the fragments of a single file is extremely low. We also compare the performance of the DROPS methodology with ten other schemes. The higher level of security with slight performance overhead was observed.
DROPS: Division and Replication of Data in the Cloud for Optimal Performance and Security
IEEE Transactions on Cloud Computing, 2015
Outsourcing data to a third-party administrative control, as is done in cloud computing, gives rise to security concerns. The data compromise may occur due to attacks by other users and nodes within the cloud. Therefore, high security measures are required to protect data within the cloud. However, the employed security strategy must also take into account the optimization of the data retrieval time. In this paper, we propose division and replication of data in the cloud for optimal performance and security (DROPS) that collectively approaches the security and performance issues. In the DROPS methodology, we divide a file into fragments, and replicate the fragmented data over the cloud nodes. Each of the nodes stores only a single fragment of a particular data file that ensures that even in case of a successful attack, no meaningful information is revealed to the attacker. Moreover, the nodes storing the fragments, are separated with certain distance by means of graph T-coloring to prohibit an attacker of guessing the locations of the fragments. Furthermore, the DROPS methodology does not rely on the traditional cryptographic techniques for the data security; thereby relieving the system of computationally expensive methodologies. We show that the probability to locate and compromise all of the nodes storing the fragments of a single file is extremely low. We also compare the performance of the DROPS methodology with 10 other schemes. The higher level of security with slight performance overhead was observed.
Security Enhancement Of Data In Cloud Using Fragmentation And Replication(492-497)
IJEMR, 2016
Cloud computing technology, since its emergence, has found many applications in various fields. In cloud storage system, client stores data in cloud server and can work with the data anytime with ease. Due to availability of services with minimum cost and easy scalability, many organizations and enterprises make use of this cloud technology to reduce the maintenance cost and also to increase the reliability of data. But this technology has many security issues because data is outsourced to a third party administrative authority. Data leakage may occur due to attacks by other users and nodes. Therefore some security measures must be employed to take care of this security issues and this security measure or strategy must also take into account the performance of the system in terms of time required to retrieve the data. In this paper, we propose a system i. e. Fragmentation and Replication of data in cloud (FRDC) which addresses these issues related to security and performance. In this methodology, file uploaded by the client is first encrypted, and then this file is divided into fragments. Afterwards replications of these fragments over the cloud nodes take place. This process of fragmentation and replication is done in such a way that only a single fragment is stored on each node. Due to this process, even in case of successful intrusion of a node by an attacker, no significant information is revealed to the attacker. To further increase the security, T-coloring graph method is used. Due to this T-coloring graph method, it becomes difficult for an attacker to breach the security.
Survey on Division and Replication of Data in Cloud for Optimal Performance and Security
Outsourcing information to an outsider authoritative control, as is done in distributed computing, offers ascend to security concerns. The information trade off may happen because of assaults by different clients and hubs inside of the cloud. Hence, high efforts to establish safety are required to secure information inside of the cloud. On the other hand, the utilized security procedure should likewise consider the advancement of the information recovery time. In this paper, we propose Division and Replication of Data in the Cloud for Optimal Performance and Security (DROPS) that all in all methodologies the security and execution issues. In the DROPS procedure, we partition a record into sections, and reproduce the divided information over the cloud hubs. Each of the hubs stores just a itary part of a specific information record that guarantees that even in the event of a fruitful assault, no important data is uncovered to the assailant. Additionally, the hubs putting away the sections are isolated with certain separation by method for diagram T-shading to restrict an assailant of speculating the areas of the sections. Moreover, the DROPS procedure does not depend on the customary cryptographic procedures for the information security; in this way alleviating the arrangement of computationally costly approaches. We demonstrate that the likelihood to find and bargain the greater part of the hubs putting away the sections of a solitary record is to a great degree low. We likewise analyze the execution of the DROPS system with ten different plans. The more elevated amount of security with slight execution overhead was watched.
Optimal Performance of Security by Fragmentation and Replication of Data in Cloud
International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2022
Outsourcing data to a third-party administrative control, as is done in cloud computing, gives rise to security concerns. The data compromise may occur due to attacks by other users and nodes within the cloud. Therefore, high security measures are required to protect data within the cloud. However, the employed security strategy must also take into account the optimization of the data retrieval time. In this paper, we propose Division and Replication of Data in the Cloud for Optimal Performance and Security (DROPS) that collectively approaches the security and performance issues. In the DROPS methodology, we divide a file into fragments, and replicate the fragmented data over the cloud nodes. Each of the nodes stores only a single fragment of a particular data file that ensures that even in case of a successful attack, no meaningful information is revealed to the attacker. I.
2016
These days, more ventures and associations are facilitating their information into the cloud, so as to lessen the IT support cost and upgrade the information dependability. The general existing conditions is that clients as a rule put their information into a solitary cloud (which is liable to the seller lock-in danger) and after that just trust to luckiness. Outsourcing information to an outsider managerial control, as is done in distributed computing, offers ascend to security concerns. The information trade off might happen because of assaults by different clients and hubs inside of the cloud. Subsequently, high efforts to establish safety are required to ensure information inside of the cloud. Nonetheless, the utilized security technique should likewise consider the improvement of the information recovery time. In this approach, we separate a document into sections, and reproduce the divided information over the cloud hubs. Each of the hubs stores just a solitary piece of a specific information record that guarantees that even if there should be an occurrence of an effective assault, no important data is uncovered to the assailant. In addition, the hubs putting away the parts are isolated with certain separation by method for diagram T-shading to restrict an assailant of speculating the areas of the pieces. We additionally propose an open evaluating plan for the recovering code-based distributed storage. To take care of the recovery issue of fizzled authenticators without information proprietors, we present an intermediary, which is advantaged to recover the authenticators, into the conventional open inspecting framework model. Consequently, our plan can totally discharge information proprietors from online weight.
Division and Replication of Data in Cloud
Since Outsourcing data to a third-party administrative control, as is done in cloud computing, gives rise to security concerns. The data compromise may occur due to attacks by other users and nodes within the cloud. Therefore, high-security measures are required to protect data within the cloud. In this project, we propose Division and Replication of Data in the Cloud for Optimal Performance and Security that collectively approaches the security and performance issues. In this project methodology, we divide a file into fragments and replicate the fragmented data over the cloud nodes. Each of the nodes stores only a single fragment of a particular data file that ensures that even in case of a successful attack, no meaningful information is revealed to the attacker.
Fragmentation of Data in Large-Scale System For Ideal Performance and Security
International Journal of Computer Applications Technology and Research, 2016
Cloud computing is becoming prominent trend which offers the number of significant advantages. One of the ground laying advantage of the cloud computing is the pay-as-per-use, where according to the use of the services, the customer has to pay. At present, user's storage availability improves the data generation. There is requiring farming out such large amount of data. There is indefinite large number of Cloud Service Providers (CSP). The Cloud Service Providers is increasing trend for many number of organizations and as well as for the customers that decreases the burden of the maintenance and local data storage. In cloud computing transferring data to the third party administrator control will give rise to security concerns. Within the cloud, compromisation of data may occur due to attacks by the unauthorized users and nodes. So, in order to protect the data in cloud the higher security measures are required and also to provide security for the optimization of the data retrieval time. The proposed system will approach the issues of security and performance. Initially in the DROPS methodology, the division of the files into fragments is done and replication of those fragmented data over the cloud node is performed. Single fragment of particular file can be stored on each of the nodes which ensure that no meaningful information is shown to an attacker on a successful attack. The separation of the nodes is done by T-Coloring in order to prohibit an attacker to guess the fragment's location. The complete data security is ensured by DROPS methodology.