Advanced Persistent Threat defense system using self-destructive mechanism for Cloud Security

Chandra, J. Vijaya; Challa, Narasimham; Pasupuleti, Sai Kiran

doi:10.1109/icetech.2016.7569181

Cited by 21 publications

(10 citation statements)

References 13 publications

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“…Based on the levels of privileges to access cloud database, the insiders are broadly classified as pure insiders, insider associate, insider affiliate and outside affiliate. A Secure Protocols based on Authentication and Authorization protocols are used for cloud data security [12]. SQL Injection attacker uses different commands to break the verification security credentials and log into the cloud environment, and even links to the SQL Databases, Authentication is the major security credential provided to the cloud and maintained as per the Global Standards, using Azure Active Directory, It protects the credentials of the employees in a company, once the authentication is successful, the employees can access to the specific company applications [13].…”

Section: S Nomentioning

confidence: 99%

Authentication and Authorization Mechanism for Cloud Security

2019

ijeat

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Cloud Computing is a most widespread and popular form of computing, promising high reliability for customers and providers both at the same point of time for many fields, where cloud storage security is based on Authentication and Authorization in cloud computing. Data is uploaded into a cloud and stored in a datacenter, Authentication and authorization are the major concerns to access the data stored in cloud by users from the data center. Security is a major issue; these are mainly deal with identity and access management, prevention of data loss and malware attack control management. In this paper we majorly concentrated on Authentication and Authorization to cloud access, we focused on identity management mechanism as cloud security solution that provides directory services for application access management. We discussed the protocols that support authorization and allows the communication across applications with the help of tokens instead of credentials. We even concentrated on the different mechanisms which plays a major role in designing a secured cloud computing architecture from malicious intrusions and attacks, it is a step to verify the presence and functioning of the cloud customers and cloud providers through security mechanisms to protect from different risks, threats and attacks. In this paper we discussed different security Algorithms and Authentication architecture along with the proposed algorithm, where analysis is done along with the computational evaluation with output.specific users [23]. VII. RESULT ANALYSISThe traditional model is designed for cloud security using Microsoft Azure Active Directory, OAuth, OpenID connect, Redirect URI. We concentrated on cloud security and build a secured model based on the parameters of Confidentiality,

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Section: S Nomentioning

confidence: 99%

Authentication and Authorization Mechanism for Cloud Security

2019

ijeat

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“…As we know that opinion mining is the responsible feature for the online marketing and e-business, we did experiment using the java eclipse programming language, where the posting opinion is done with input date and time which is collected automatically where the input of the product name is taken along with the rating with five options such as Excellent, very-good, good, not bad, poor and also a text box for memo is given for the information of the opinion. After giving opinion on the product the user will click on the option button, that is Add my opinion, where the opinions are stored in databases [14].…”

Section: Experimental Analysismentioning

confidence: 99%

Opinion Mining and Client Feedback Mining for Quality Improvement

Chandra,

Gyaderla,

Lakshmi

et al. 2019

IJEAT

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As E-Commerce growing rapidly, now a day’s customers reviews about product has become most crucial for development of the business. The opinion mining is most crucial in ecommerce websites, furthermore advantageous with client’s feedback. The current research work mainly focuses on the client engagement review analysis. In this paper we concentrated on mining reviews from clients who are seeking consulting services from the IT industries, which enables the companies to understand the data patterns and identify some Key Performance Indicators and develop accordingly. The Client feedback mining allows the user to allow Clients to convey what they think and feel about the services. This opinion or review about the product will help purchaser to get an idea regarding the product, and the seller regarding required improvements or updates, hence opinion mining plays a major role in ecommerce. We also concentrated on the sentimental analysis that means a reviewer can write about the product positively or negatively, it depends on many parameters such as emotions they want to express, opinion of the product they purchased, received time, package and condition they received the product. It clearly gives an idea to the seller and purchaser about demand, supply and quality improvement. Key Performance Indicator is measured based on metrics that business organizations track in order to measure their progress towards goal within marketing networks. We designed a mathematical model and executed for results. We discussed different algorithms based on opinion mining and we implemented cloud based practical implementation of a simulated model for understanding of results and given graphical analysis along with result analysis

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“…One of WEKA's major strengths is that it is easily extended with customized or new classifiers, clusters, attribute selection methods, and other components. Cloud computing provides convenient data and information storage systems, due to targeted cyber-attacks on cloud, Industrialists and Researchers all over the world concentrated on the cloud security, as cloud provides convenient data storage system for industry, government, researchers and academic users with cost-effective access to distributed services through internet, the main challenge is the data privacy and information security [5]. In 2015 Saranya Chandran et.al focused on the real-world problem that is advanced persistent threat and identification of an efficient classification model for detection of APT using different classifiers such as Random Forest, Naïve Bayes and J-48 [6].…”

Section: Related Workmentioning

confidence: 99%

Machine Learning Framework To Analyze Against Spear Phishing

Chandra¹,

Challa²,

Pasupuleti³

2019

IJITEE

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The objective of this paper is to design and implement machine learning based ensemble algorithm on dataset to fit into the models that can be understood and executed by machines. In this paper we discussed different algorithms and machine learning concepts that can be implemented on the datasets, we taken email spam filter dataset for experiment and analysis, as the Advanced persistent threat the latest threat is intruded using the emails and major intrusion is done through spam emails. Machine learning uses different datamining techniques and mechanisms and accepts the input-data and gives the output as the statistical analysis. We implemented different email classification algorithms on the datasets based on spam and ham emails where spear phishing methods are identified and implemented different classification and regression methods to get the accurate results. In this paper for the better results in spite of existing algorithms we introduced the ensemble methods such as boosting, bagging, stacking and voting for much accuracy and higher level of classification and combining different algorithm. This paper will measure different machine learning algorithms performance on spam email filtering on the huge datasets. The framework provides implementation of learning algorithms that you can apply to larger datasets. An obvious approach to making decisions more reliable is to combine the output of different models. We even compared the existing algorithms and proposed algorithm; comparison tables are drawn along with the statistical analysis, data and graphical analysis is given.

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Advanced Persistent Threat defense system using self-destructive mechanism for Cloud Security

Cited by 21 publications

References 13 publications

Authentication and Authorization Mechanism for Cloud Security

Authentication and Authorization Mechanism for Cloud Security

Opinion Mining and Client Feedback Mining for Quality Improvement

Machine Learning Framework To Analyze Against Spear Phishing

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