Abstract
Protection of sensitive information is a primary issue in data mining. Association rule hiding is a popular technique to stop exposure of sensitive information while mining the desired data from data repositories. It preserves the confidentiality of rules as per certain interestingness criteria. Many techniques and algorithms are available for hiding sensitive rules in order to keep sensitive information hidden. Increase support left (ISL) and decrease support right (DSR) are popular and widely used algorithms to implement association rule hiding during data mining. As an advancement of the existing algorithms, a novel algorithm selective flip bit was developed. It is used to generate better results in terms of lost rules, false rules, and ghost rules as compared to algorithms in the same field. In this paper, the avalanche effect has been calculated of rule hiding algorithms in order to evaluate their performances. A database of supermarket store was taken to evaluate performance in the real market domain. Results indicated that selective flip bit algorithm returns the least avalanche effect which makes it better than other algorithms in the same field.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Agarwal S (2000) Privacy-preserving data mining. In: ACM SIGMOD, pp 439–450
Charu CA, Philip SY (2008) Privacy-preserving data mining models and algorithms, vol 34. Springer Science Business Media, New York
Modi CN, Rao UP, Patel DR (2010) Maintaining privacy and data quality in privacy preserving association rule mining. In: Seventh international conference on machine learning and applications, vol 2. Springer International, Switzerland, pp 1–6
Zala K (2012) Comparison of ISL, DSR, and new variable hiding counter algorithm of association rule hiding. Int J Sci Eng Res: IEEE 3(5)
Shah K, Thakkar A, Ganatra A (2012) Association rule hiding by heuristic approach to reduce side effects & hide multiple R.H.S. items. Int J Comput Appl 45
Natarajan R, Sugumar R, Mahendran M, Anbazhagan K (2012) Design and implement an association rule hiding algorithm for privacy preserving data mining. Int J Adv Res Comput Commun Eng: IEEE 1
Maja D, Tanja K (2013) Association rules for improving website effectiveness: case analysis. Online J Appl Knowl Manage 1(2)
Jadav K, Vania J (2013) A survey on association rule hiding methods. Int J Comput Appl. ISSN: 0975-8887, vol 82
Vijayarani S., Tamilarasi A (2014) An efficient technique for hiding association rules in privacy preserving data mining, vol 12. Shodhganga, India, pp 141–163
Yewale A, Rajput Y, Shirapure S, Patel H (2014) Privacy preserving association rule mining in retail industries. Int J Adv Res Comput Commun Eng
Kaur K, Bansal M. A review on various techniques of hiding Association rules in privacy preservation data mining. IJECS 4(6):12947–12951
Upadhyay N, Tripathi K, Mishra A (2015) A survey of association rule hiding approaches. Int J Comput Sci Inf Technol Security 5(1). ISSN: 2249-9555
Bhatt N, Patel M (2015) Updated hybrid ISL and DSR based technique for protecting sensitive information. Int J Innov Res Technol 2(6)
Singh G, Jassi S (2017) A review paper: a comparative analysis on association rule mining algorithms. Int J Recent Technol Eng 6(2):2277–3878
Kulkarni AR, Shivaji D, Mundhe SD (2017) Data mining technique: an implementation of association rule mining in healthcare. Int Adv Res J Sci Eng Technol 4(7)
Pathak K, Silkari S, Chaudhari NS (2017) Privacy preserving informative association rule mining. Int J Appl Inf Syst 12. ISSN 2249-0868
Surendra H, Mohan HS (2018) Distortion-based privacy-preserved association rules mining without side effects using closed itemsets. In: Emerging technologies in data mining and information security. vol 813. Springer, Berlin, pp 591–601
Sulova S (2018) Association rule mining for improvement of IT Project management. TEM J 7(4):717–722
Kholod M (2018) Market basket analysis of convenience store POS data. In: Science reports. Tohoku University. vol 71, pp 61–82
Ameta G, Bhatnagar D (2019) Development of an association rule hiding algorithm for privacy preserving in market basket databases. Int J Innov Technol Exploring Eng 8(6S)
Acknowledgements
We thank all the researchers and the author of the research papers referred for this study which helped to understand and experiment the techniques in a very effective way. Also, special thanks to Pacific University, CSE, Udaipur, for providing the required laboratory facilities and well-qualified guide Prashant Sharma who gave me valuable knowledge and direction in this research.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Audichya, D., Sharma, P., Vaishnav, P.K. (2022). Determination of Avalanche Effect to Compute the Efficiency of Association Rule Hiding Algorithms. In: Pandit, M., Gaur, M.K., Rana, P.S., Tiwari, A. (eds) Artificial Intelligence and Sustainable Computing. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-19-1653-3_55
Download citation
DOI: https://doi.org/10.1007/978-981-19-1653-3_55
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-1652-6
Online ISBN: 978-981-19-1653-3
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)