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Cloud computing technique has been gaining popularity because of its different features such as on demand service and scalability (Gonzales et al., 2015). Cloud has been widely employed for storing data and other computation intensive applications due to which issues such as data security and privacy have become of primary concern (Andrew et al., 2019). While data security is associated with data confidentiality, availability and integrity, data privacy is for hiding the identity of data on cloud (Chen & Zhao, 2012). The security issues associated with data prevail on the cloud until the data is destroyed or removed from cloud.<br>Threats to Cloud Computing<br>Some of the most common threats or challenges associated with cloud computing are as follows (Aldossary & Allen, 2016):<br>u2022 Data loss<br>u2022 Data breach<br>u2022 Malicious insiders<br>u2022 Insecure interfaces and APIs<br>u2022 Account or service hijacking<br>u2022 Data location denial of service<br>The machine learning algorithms used for data security on cloud are classified into two categories: supervised and unsupervised. In case of supervised algorithms, a dataset is first created which belongs to different other classes which have a certain identity. On the contrary, in unsupervised learning the classes employed are not specifically characterized instead information is arranged automatically. To get the latest updates visit: https://www.tutorsindia.com/blog/<br>Contact:<br>Website: www.tutorsindia.com<br>Email: info@tutorsindia.com<br>United Kingdom: 44-1143520021<br>India: 91-4448137070<br>Whatsapp Number: 91-8754446690<br>
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HOW MACHINE LEARNING TECHNIQUE CAN HELP CLOUD DATABASESYSTEM An Academic presentationby Dr. Nancy Agens, Head, Technical Operations,TutorsIndia Group www.tutorsindia.com Email:info@tutorsindia.com
Today'sDiscussion OUTLINE In Brief Introduction Why is Cloud Preferred Threats to Cloud Computing Data Security Issues MachineLearning Machine Learning Algorithms Conclusion
InBrief Cloud computation has been gaining popularity due to its application for storing data. Existence of large volumes of data on cloud has grabbed the concern of industries towards maintaining security and privacy of data. In order to secure the data there have been applied several approaches such as encryption, cryptography etc. Recently machine learning algorithms have been applied to secure the data oncloud.
Cloud computing techniquehas been gainingpopularity because of its different features such as on demand service and scalability. Cloud has been widely employed for storing data and other computation intensive applications due to which issues such as data security and privacy have become of primaryconcern. Introduction While data security is associated with data confidentiality, availability and integrity, data privacy is for hiding the identity of data oncloud. The security issues associated with data prevail on the cloud until the data is destroyed or removed fromcloud.
Why is CloudPreferred? The users associated with cloud avail different benefits in terms of accessing the data, availability and confidentiality ofdata. In addition since the data is stored on different severs on cloud the users are able to access it from anywhere and anytime without requiring any physicaldevices. The data shared over the network can be accessed by differentclients. Besides, the cloud also offers facilities such as recoveries from disaster,archival andbackup.
Dataloss Databreach Threats toCloud Computing Maliciousinsiders Insecure interfaces andAPIs Account or servicehijacking Data location denial ofservice
Data SecurityIssues The data securityissuesoccur primarily because users and several organizations store their data on cloud and thus it becomes necessary to prevent the data from being leaked during its travelling over thenetwork. There are several methods used for securingdata. These methods are based on encryption of data and access control. These methods enable preventing leakage ofdata. Cryptographic algorithms have also been applied to cloud servers to resolve the securityissues.
MachineLearning In machine learning the data classification approach is used for differentiating between the unclassified and classified datasets. The classifier used is build by developing a training set of datasamples. The servers offering such service undertake the processing of data and classify the data samples of clients. Besides classification, it is ensured that through this approach the data processed and categorized might not be leaked by theservers.
Machine LearningAlgorithms Unsupervised Algorithm SupervisedAlgorithm A dataset is first created which belongs to different other classes which have a certainidentity. The classes employed are not specifically characterized instead information is arrangedautomatically. Non-SensitiveAttributes SensitiveAttributes Sensitive attributes are designated asconfidential. Non-sensitive attributes is classified as non-confidential.
Conclusion Undeniably, the security and distribution of data are of paramount significance in the presentworld. There has been observed an increase in the risk of privacy of individuals due to increase in the attack on data stored when storing resources like cloud computing areused. In order to protect the data stored on cloud it is necessary that different cloudcomputing techniques should be employed. Noticeably, with the increase in data storage devices there has been observed advancements in the techniques used for maintaining privacy and security ofdata.
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