Preservation of privacy in data mining by using PCA based perturbation technique

Gokulnath, C.; Kumar, Priyan Malarvizhi; Balan, E. Vishnu; Prabha, K.P. Rama; Jeyanthi, R.

doi:10.1109/icstm.2015.7225414

Cited by 29 publications

(10 citation statements)

References 8 publications

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“…Ansgar et al (2015) discussed the impact of functional safety and development of intelligent transportation systems using service-oriented architectures. The outcome of this approach emphasizes process capability standards and functional safety for reliable transportation but lags in security and visibility of the system [24].…”

Section: Related Workmentioning

confidence: 99%

RETRACTED ARTICLE: Internet of Things Based Intelligent Transportation of Food Products During COVID

Alluhaidan

Alluhaidan²,

Basheer

2021

Wireless Pers Commun

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Section: Related Workmentioning

confidence: 99%

RETRACTED ARTICLE: Internet of Things Based Intelligent Transportation of Food Products During COVID

Alluhaidan

Alluhaidan²,

Basheer

2021

Wireless Pers Commun

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“…The particular tweets are analyzed and classified using text analytics and natural language processing, because the dataset contains a vast amount of data with various words and slangs. In the second step, those collected tweets are analyzed to clean the non-textual emoticons, contents, numerical values and important information are extracted [23]. The emotions are detected from the extracted tweets in the third step then, the opinions and its reviews are inspected.…”

Section: Proposed Methodologymentioning

confidence: 99%

Twitter Sentiment Analysis using Aspect-based Bidirectional Gated Recurrent Unit with Self-Attention Mechanism

Venkataramaiah¹,

Achar²

2020

IJIES

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Nowadays, social media sites and applications such as Twitter, YouTube, Facebook and blogs gained much attention, because organizations use this huge information to monitor the user opinions. Therefore, the researchers focused on sentiment analysis to help organizations for better production. But, the existing studies concentrated only on document-level in the analysis, where the details of the sentiments are not considered. In order to perform a finegrained analysis, this research study uses the aspect-based sentiment analysis on Twitter data for finding the opinions of users. In general, a raw tweet contains stop words, Uniform Resource Locator (URL), emoji that are reduced in the stage of pre-processing. The polarities of pre-processed tweets are identified, then two important feature extraction techniques are used to extract the useful information. The specific sentiments with various aspects of services are extracted by using aspect-based feature extraction, which are given as an input for Bi-directional Gated Recurrent Unit (BGRU) for classification. The learning rate of BGRU is further improved by incorporating the self-attention layers. To test the efficiency of the proposed method, the experiments are conducted on real-time collected tweets in terms of accuracy, precision, recall and f-score. The results showed that the developed method achieved 80.4% accuracy, 81% precision, 80% of recall and f-score for 1000 dataset length when compared with traditional techniques: Long-short term Memory (LSTM) and standard GRU.

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“…In the work [20][21][22], a security framework based on Zero-knowledge evidence provides anonymous authentication for new consumers. But, the major limitation of the model is the communication overhead.…”

Section: Introductionmentioning

confidence: 99%

Towards Developing Privacy-Preserved Data Security Approach (PP-DSA) in Cloud Computing Environment

Kirubakaran¹,

Arunachalam²,

Karthik³

et al. 2023

Computer Systems Science and Engineering

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In the present scenario of rapid growth in cloud computing models, several companies and users started to share their data on cloud servers. However, when the model is not completely trusted, the data owners face several security-related problems, such as user privacy breaches, data disclosure, data corruption, and so on, during the process of data outsourcing. For addressing and handling the security-related issues on Cloud, several models were proposed. With that concern, this paper develops a Privacy-Preserved Data Security Approach (PP-DSA) to provide the data security and data integrity for the outsourcing data in Cloud Environment. Privacy preservation is ensured in this work with the Efficient Authentication Technique (EAT) using the Group Signature method that is applied with Third-Party Auditor (TPA). The role of the auditor is to secure the data and guarantee shared data integrity. Additionally, the Cloud Service Provider (CSP) and Data User (DU) can also be the attackers that are to be handled with the EAT. Here, the major objective of the work is to enhance cloud security and thereby, increase Quality of Service (QoS). The results are evaluated based on the model effectiveness, security, and reliability and show that the proposed model provides better results than existing works.

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Preservation of privacy in data mining by using PCA based perturbation technique

Cited by 29 publications

References 8 publications

RETRACTED ARTICLE: Internet of Things Based Intelligent Transportation of Food Products During COVID

RETRACTED ARTICLE: Internet of Things Based Intelligent Transportation of Food Products During COVID

Twitter Sentiment Analysis using Aspect-based Bidirectional Gated Recurrent Unit with Self-Attention Mechanism

Towards Developing Privacy-Preserved Data Security Approach (PP-DSA) in Cloud Computing Environment

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