A Secured Framework to Protect Association Rules in the Big Data Environment Using Fuzzy Logic

Madhu, Sake; Midde, Ranjit Reddy; Ramu, Gandikota; Jayanthi, Appawala; Somasekar, J.; Ramesh, G.; Reddy, P Chandrashaker

doi:10.18280/isi.240511

Cited by 5 publications

(4 citation statements)

References 28 publications

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“…• Golnar Assadat and Afzali,Shahriar Mohammadi. (2019) [22], in addition to its advantages in revealing ambiguous linkages between data, ARM will violate privacy. To prevent sensitive association rules from being found, association rule hiding could be helpful.…”

Section: • Almukahel Et Al (2018) [19] a Novel Version Of Mapreduce W...mentioning

confidence: 99%

A Hybrid Integrated Model for Big Data Applications Based on Association Rules and Fuzzy Logic: A Review

raad

Hamad

2023

ijcsm

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There is a real increasing in the generating of data from different sources. Data mining (DM) is a useful method to elicit valuable information. Association rule mining (ARM) can assist in finding patterns and trends in big data. Also fuzzy logic plays a main role as assistance technique in handling big data issues. This review paper produces recent literature on hybridization regarding the association rule mining or other DM methods such as classification and clustering and fuzzy logic techniques in big data. Whereas a hybrid model of association rule and fuzzy logic is suggested to get a valuable knowledge for big data applications at good accuracy and less time, with the aid of distributed framework for big data handling (Hadoop, Spark and MapReduce). Different techniques and algorithms were used in these works and evaluated according to accuracy, sensitivity, recall and run time with a various result as Specificity = 86%, Sensitivity = 80% and F-measure = 2.5, or achieving high accuracy and shorter runtime compared to other methods and 98.5accuraccy of fitness function in pruning redundant rules. At the end of the paper we present the most used and prominent techniques that assist in providing a useful and valuable knowledge in different domains from a huge, unstructured and even heterogeneous data. The paper will be beneficial to the researches who interesting in the field of mining big data.

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Section: • Almukahel Et Al (2018) [19] a Novel Version Of Mapreduce W...mentioning

confidence: 99%

A Hybrid Integrated Model for Big Data Applications Based on Association Rules and Fuzzy Logic: A Review

raad

Hamad

2023

ijcsm

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“…The fuzzy expert system (FES) algorithm is simple and involves only IF-THEN rules. Previous studies have reported the FES in detail [24][25][26][27][28][29][30][31][32][33] and is modeled to determine fault locations [34]. The FES was provided for location determination by considering the impedance values as inputs [35].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Location Algorithm for Cross-Country and Evolving Faults in EHV Transmission Line

Kumar,

Chakravarthy,

Kumar

et al. 2023

IJFIS

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Fault protection is an important issue as it adversely affects the performance of conventional relays, particularly for cross-country and evolving faults in transmission lines. In this paper, a novel fault location algorithm for cross-country and evolving faults in extra high voltage transmission (EHVT) line using the fuzzy expert system (FES) is presented. The algorithm is based on the impedance values of relaying terminal fundamental component. In addition, the proposed FES is independent of communication links. It was designed using input variables via the IF-THEN rules and developed with the fuzzy MAMDANI structure. A triangular membership function was used to estimate the degree of inputs. MATLAB software was used to evaluate the error in the fault location for a 100-km, 400-kV, 50-Hz EHVT line. The FES algorithm yielded precise values. The test results were independent of the fault inception time, location, and type. The experimental results illustrate that the FES performed better than the other algorithms.

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“…The relationship between forestry production and forestry ecological development exists as a mutual constraint and mutual promotion.Mohammed Amine Yagoub, through the relationship between forestry production and forestry ecological construction, has gradually elaborated how to better achieve sustainable development and promote forestry ecological construction on the path of scientific and social development, and has analyzed the sustainable development problems between the two accordingly [7]. Sake Madhu analyzed the necessity of building forestry ecosystems in Heilongjiang province in the new historical period and put forward some feasible and reasonable opinions on how to better build forestry ecosystems [8]. Therefore, it is important to propose a set of construction concepts and methods for the construction of forestry ecology in China in order to improve the quality of forestry ecology construction in China rapidly and as a whole [9].…”

Section: Introductionmentioning

confidence: 99%

Nature Conservation Environment Based on Forestry Ecology in the Context of Internet+

2022

NEP

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With the continuous crossover and integration of information technology and ecological station construction, forestry ecological stations have been improved in monitoring technology and instrumentation, laying a solid foundation for ecological benefit assessment, ecological early warning and ecological strategic decision analysis, which are of great importance for accelerating long-term positioning research and building green ecology. The purpose of this paper is to study the nature protection environment of forestry ecology based on Internet+. Based on some forestry ecological station data, the system is designed and implemented to help ecological station staff improve the efficiency of statistical analysis and visual display of monitoring data, historical data query and real-time understanding of changes in station conditions, etc. The forest area algorithm is proposed to achieve image compression and loading, and the experimental results show that the "Internet+ ecological station "management system can effectively realize the natural protection environment of forestry ecology.

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A Secured Framework to Protect Association Rules in the Big Data Environment Using Fuzzy Logic

Cited by 5 publications

References 28 publications

A Hybrid Integrated Model for Big Data Applications Based on Association Rules and Fuzzy Logic: A Review

A Hybrid Integrated Model for Big Data Applications Based on Association Rules and Fuzzy Logic: A Review

Fuzzy Location Algorithm for Cross-Country and Evolving Faults in EHV Transmission Line

Nature Conservation Environment Based on Forestry Ecology in the Context of Internet+

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