Detection and Prevention of Sensitive Data From Data Leak Using Shingling and Rabin Filter

Gaikwad, Sushma Vishwanath; Chougule, Shilpa; Charhate, Shrikant

doi:10.18517/ijaseit.6.5.997

Cited by 5 publications

(4 citation statements)

References 9 publications

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“…The first introduction of RIDIT was to classify borderline cases in a behavioural science study of a categorical dataset [16]. The reference group is a random data taken from large sample observations [23]. The evolution of RIDIT then continued by other researchers.…”

Section: Methodsmentioning

confidence: 99%

Credit Card Detection System Based on Ridit Approach

Tukiman¹,

Ahmad²,

Saad³

et al. 2017

International Journal on Advanced Science, Engineering and Information Technology

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Fraud detection is one of the important agendas in financial and insurance institutions to protect the institutions from fraudsters and loss. The losses to the financial institutions are huge, and the need to detect the fraud at an early stage is critical to the institutions. If the numbers of fraud are not properly managed, the impact may lead to the closure of the institutions. Many predictive analytic systems or models have been proposed to identify and detect the frauds. Hence, this paper examines the effect of different response variables of credit card history as the reference group which used an unsupervised scoring method namely an Identified Distribution (RIDIT) based on a statistically significant test. We illustrate the method using German Credit card dataset retrieved from UCI Machine Learning Data System. The result generates scores and significant value of chi-square test that reflect response variables being classified as reference group or comparison groups, which more or less affected by the response credit card history in fraud detection.

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Section: Methodsmentioning

confidence: 99%

Credit Card Detection System Based on Ridit Approach

Tukiman¹,

Ahmad²,

Saad³

et al. 2017

International Journal on Advanced Science, Engineering and Information Technology

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“…A contiguous subsequence contained in D is called a shingle [9,10]. Given a document D, we can associate to it, its w-shingling defined as the bag (multiset) of all shingles of size w contained in D. So for instance the 4-shingling of(a,rose,is,a,rose,is,a,rose) is the bag{(a,rose,is,a); (rose,is,a,rose); (is,a,rose,is);(a,rose,is,a); (rose,is,a,rose)}.…”

Section: K-shinglementioning

confidence: 99%

Chinese Data Feature Extraction Optimization in Data Detection

Zhang¹,

Jin²,

Mu³

et al. 2017

dtetr

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While microblog is developing rapidly in China, microblog messages are also flooded with a large amount of repetitive information. Simhash algorithm has better precision and efficiency in the existing algorithms of similarity computation. In this paper, according to the actual scene of microblog, the deep optimization of traditional simhash is proposed through the segmentation optimization algorithm (Combined-Analyzer) and weight optimization algorithm (FFBOT-FID). To a certain extent, Combined-Analyzer solved the problem which real scene existed the massive internet words in microblog's short text and FFBOT-FID helped us solve the problem of calculating weight which was caused by short text and timeliness. The experimental results use in microblog de-duplication and show that the optimization has a higher precision and recall rate than the traditional segmentation algorithm.

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“…Therefore this system implemented to enables the data owner to detect and prevent data leak. The results show that approach can provide accurate detection with a small number of false alarm [19]. Suggest a step to reshape the policy in order to develop a data protection that leads to creating better confidence for the user, therefore adopted a survey questionnaire methodology by clients [20].…”

Section: Introductionmentioning

confidence: 99%

A Novel DNA Sequence Approach for Network Intrusion Detection System Based on Cryptography Encoding Method

Othman¹,

Zainudin²

2017

International Journal on Advanced Science, Engineering and Information Technology

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A novel method for Network Intrusion Detection System (NIDS) has been proposed, based on the concept of how DNA sequence detects disease as both domains have similar conceptual method of detection. Three important steps have been proposed to apply DNA sequence for NIDS: convert the network traffic data into a form of DNA sequence using Cryptography encoding method; discover patterns of Short Tandem Repeats (STR) sequence for each network traffic attack using Teiresias algorithm; and conduct classification process depends upon STR sequence based on Horspool algorithm. 10% KDD Cup 1999 data set is used for training phase. Correct KDD Cup 1999 data set is used for testing phase to evaluate the proposed method. The current experiment results show that the proposed system has obtained good results and these results are equal to 86.36%, 49.69%, and 77.65% for detection rate, false alarm rate, and accuracy respectively. These results are considered as a better result when it is compared with the other previous basic algorithms. It is possible to conclude that DNA sequence has the potential for NIDS solution and it has potential improvement using a better encoding method.

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Detection and Prevention of Sensitive Data From Data Leak Using Shingling and Rabin Filter

Cited by 5 publications

References 9 publications

Credit Card Detection System Based on Ridit Approach

Credit Card Detection System Based on Ridit Approach

Chinese Data Feature Extraction Optimization in Data Detection

A Novel DNA Sequence Approach for Network Intrusion Detection System Based on Cryptography Encoding Method

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