Privacy Protection of Class Association Rules produced by medical datasets

2019 ◽  
Author(s):  
Priyanka Garach ◽  
Darshana Patel
Keyword(s):  
Association Rules ◽  
Privacy Protection

scholarly journals Efficient Association Rules Hiding Using Genetic Algorithms

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 576 ◽  
Author(s):  
Naadiya Khuda Bux ◽  
Mingming Lu ◽  
Jianxin Wang ◽  
Saajid Hussain ◽  
Yazan Aljeroudi
Keyword(s):  
Association Rules ◽  
Privacy Protection ◽  
Search Behavior ◽  
Sensitive Information ◽  
Parallel Search ◽  
Local Minima ◽  
Important Goal ◽  
Genetic Encoding ◽  
Benchmark Datasets ◽  
Recursive Computation

In today’s world, millions of transactions are connected to online businesses, and the main challenging task is ensuring the privacy of sensitive information. Sensitive association rules hiding (SARH) is an important goal of privacy protection algorithms. Various approaches and algorithms have been developed for sensitive association rules hiding, differentiated according to their hiding performance through utility preservation, prevention of ghost rules, and computational complexity. A meta-heuristic algorithm is a good candidate to solve the problem of SARH due to its selective and parallel search behavior, avoiding local minima capability. This paper proposes simple genetic encoding for SARH. The proposed algorithm formulates an objective function that estimates the effect on nonsensitive rules and offers recursive computation to reduce them. Three benchmark datasets were used for evaluation. The results show an improvement of 81% in execution time, 23% in utility, and 5% in accuracy.

A Sub Chunk-Confusion Based Privacy Protection Mechanism for Association Rules in Cloud Services

2016 ◽  
Vol 26 (04) ◽  
pp. 539-562 ◽  
Author(s):  
Yuliang Shi ◽  
Zhongmin Zhou ◽  
Lizhen Cui ◽  
Shijun Liu
Keyword(s):  
Association Rules ◽  
Privacy Protection ◽  
Data Privacy ◽  
Cloud Services ◽  
Protection Mechanism ◽  
Security Issues ◽  
Computing Services ◽  
Real World Applications ◽  
Protection Technology ◽  
Cloud Computing Services

In cloud computing services, according to the customized privacy protection policy by the tenant and the sub chunk-confusion based on privacy protection technology, we can partition the tenant’s data into many chunks and confuse the relationships among chunks, which makes the attacker cannot infer tenant’s information by simply combining attributes. But it still has security issues. For example, with the amount of data growing, there may be a few hidden association rules among some attributes of the data chunks. Through these rules, it is possible to get some of the privacy information of the tenant. To address this issue, the paper proposes a privacy protection mechanism based on chunk-confusion privacy protection technology for association rules. The mechanism can detect unidimensional and multidimensional attributes association rules, hide them by adding fake data, re-chunking and re-grouping, and then ensure the privacy of tenant’s data. In addition, this mechanism also provides evaluation formulas. They filter detected association rules, remove the invalid and improve system performance. They also evaluate the effect of privacy protection. The experimental evaluation proves that the mechanism proposed in this paper can better protect the data privacy of tenant and has feasibility and practicality in real world applications.

scholarly journals Privacy Protection Method for Multiple Sensitive Attributes Based on Strong Rule

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Tong Yi ◽  
Minyong Shi
Keyword(s):  
Association Rules ◽  
Privacy Protection ◽  
Background Knowledge ◽  
Data Publishing ◽  
High Quality ◽  
New Model ◽  
Attack Model ◽  
Protection Method ◽  
Sensitive Attribute ◽  
Almost All

At present, most studies on data publishing only considered single sensitive attribute, and the works on multiple sensitive attributes are still few. And almost all the existing studies on multiple sensitive attributes had not taken the inherent relationship between sensitive attributes into account, so that adversary can use the background knowledge about this relationship to attack the privacy of users. This paper presents an attack model with the association rules between the sensitive attributes and, accordingly, presents a data publication for multiple sensitive attributes. Through proof and analysis, the new model can prevent adversary from using the background knowledge about association rules to attack privacy, and it is able to get high-quality released information. At last, this paper verifies the above conclusion with experiments.

Privacy Protection in Association Rule Mining

2011 ◽  
pp. 925-929
Author(s):  
Neha Jha ◽  
Shamik Sural
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Privacy Protection ◽  
Association Rule Mining ◽  
Rule Mining ◽  
Important Data ◽  
Mining Technology ◽  
Large Sets ◽  
Future Data ◽  
Prediction Techniques

Data mining technology has emerged as a means for identifying patterns and trends from large sets of data. Mining encompasses various algorithms, such as discovery of association rules, clustering, classification and prediction. While classification and prediction techniques are used to extract models describing important data classes or to predict future data trends, clustering is the process of grouping a set of physical or abstract objects into classes of similar objects.

Proposal Tightens Privacy Protection

2010 ◽  
Vol 43 (13) ◽  
pp. 77
Author(s):  
MARY ELLEN SCHNEIDER
Keyword(s):  
Privacy Protection

How Useful Can Be Data Mining For A Continuos Speech Therapist’s Education?

2014 ◽  
Vol 1 (1) ◽  
pp. 339-342
Author(s):  
Mirela Danubianu ◽  
Dragos Mircea Danubianu
Keyword(s):  
Data Mining ◽  
Information And Communication Technology ◽  
Association Rules ◽  
Communication Technology ◽  
Speech Therapy ◽  
Proper Treatment ◽  
Speech Impairments ◽  
Information And Communication ◽  
Specific Education

AbstractSpeech therapy can be viewed as a business in logopaedic area that aims to offer services for correcting language. A proper treatment of speech impairments ensures improved efficiency of therapy, so, in order to do that, a therapist must continuously learn how to adjust its therapy methods to patient's characteristics. Using Information and Communication Technology in this area allowed collecting a lot of data regarding various aspects of treatment. These data can be used for a data mining process in order to find useful and usable patterns and models which help therapists to improve its specific education. Clustering, classification or association rules can provide unexpected information which help to complete therapist's knowledge and to adapt the therapy to patient's needs.

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