HOW MACHINE LEARNINGTECHNIQUE CAN HELPCLOUD DATABASE SYSTEM

An Academic presentation by Dr. Nancy Agens, Head, Technical Operations, Tutors India Group  www.tutorsindia.comEmail: info@tutorsindia.com

In BriefIntroductionWhy is Cloud PreferredThreats to Cloud ComputingData Security IssuesMachine LearningMachine Learning AlgorithmsConclusion

OUTLINE

Today's Discussion

In Brief

Cloud computation has been gaining popularity due to itsapplication for storing data. Existence of large volumes of data oncloud has grabbed the concern of industries towards maintaining

security and privacy of data. In order to secure the data there havebeen applied several approaches such as encryption, cryptography

etc. Recently machine learning algorithms have been applied tosecure the data on cloud.

Introduction

Cloud computing technique has been gaining popularitybecause of its different features such as on demandservice and scalability.

Cloud has been widely employed for storing data andother computation intensive applications due towhich issues such as data security and privacy havebecome of primary concern.

While data security is associated with dataconfidentiality, availability and integrity, data privacy isfor hiding the identity of data on cloud.

The security issues associated with data prevail on thecloud until the data is destroyed or removed from cloud.

The users associated with cloud avail different benefits in terms of accessing thedata, availability and confidentiality of data.

In addition since the data is stored on different severs on cloud the users are ableto access it from anywhere and anytime without requiring any physical devices.

The data shared over the network can be accessed by different clients.

Besides, the cloud also offers facilities such as recoveries from disaster, archivaland backup.

Why is Cloud Preferred?

Data loss

Data breach

Malicious insiders

Insecure interfaces and APIs

Account or service hijacking

Data location denial of service

Threatsto CloudComputing

The data security issues occur primarily because users and several organizations store their dataon cloud and thus it becomes necessary to prevent the data from being leaked during itstravelling over the network.

There are several methods used for securing data.

These methods are based on encryption of data and access control.

These methods enable preventing leakage of data.

Cryptographic algorithms have also been applied to cloud servers to resolve the security issues.

Data Security Issues

In machine learning the data classification approach is used for differentiatingbetween the unclassified and classified data sets.

The classifier used is build by developing a training set of data samples.

The servers offering such service undertake the processing of data and classify thedata samples of clients.

Besides classification, it is ensured that through this approach the data processedand categorized might not be leaked by the servers.

Machine Learning

A dataset is first created whichbelongs to different other classeswhich have a certain identity.

Machine Learning Algorithms

The classes employed are notspecifically characterized insteadinformation is arranged automatically.

Supervised Algorithm Unsupervised Algorithm

Non-sensitive attributes is classifiedas non-confidential.

Sensitive attributes aredesignated as confidential.

Sensitive Attributes Non-Sensitive Attributes

Undeniably, the security and distribution of data are of paramount significance in thepresent world.

There has been observed an increase in the risk of privacy of individuals due to increasein the attack on data stored when storing resources like cloud computing are used.

In order to protect the data stored on cloud it is necessary that different cloud computingtechniques should be employed.

Noticeably, with the increase in data storage devices there has been observedadvancements in the techniques used for maintaining privacy and security of data.

Conclusion

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