Abstract
Nowadays, extensively obtainable personal data has made Privacy-Preserving Data Mining (PPDM) issues a significant one. PPDM handles securing the privacy of sensitive knowledge or personal data without leaking the utility of the data. Several techniques have been introduced with the concern of privacy, yet there exist certain limitations in PPDM in achieving the feasible standards. Hence, this paper intends to develop a sanitization and restoration model by concerning objective functions like, Hiding Failure rate, Information Preservation rate, False Rules generation rate, Degree of Modification, Compression Ratio, tampering and Low Pass Filter for better preservation of privacy data. In sanitization and restoration, a key is generated optimally using Hybrid model named Genetic Algorithm with Crow Search Algorithm (GA-CSA). Moreover, the sensitive data is restored efficiently by the authorized user at the receiving end. Finally, the proposed GA-CSA approach is compared over conventional schemes such as Firefly (FF), Self-Adaptive FF Genetic Algorithm, Particle Swarm Optimization, and Differential Evolution approach and the enhanced outcomes are obtained.
Similar content being viewed by others
References
Giannotti F, Lakshmanan LVS, Monreale A, Pedreschi D, Wang H (2013) Privacy-preserving mining of association rules from outsourced transaction databases. IEEE Syst J 7(3):385–395
Fouad MR, Elbassioni K, Bertino E (2014) A supermodularity-based differential privacy preserving algorithm for data anonymization. IEEE Trans Knowl Data Eng 26(7):1591–1601
Li Y, Yang J, Ji W (2016) Local learning-based feature weighting with privacy preservation. Neurocomputing 174:1107–1115
Sui P, Li X (2017) A privacy-preserving approach for multimodal transaction data integrated analysis. Neurocomputing 253:56–64
Prakash M, Singaravel G (2015) An approach for prevention of privacy breach and information leakage in sensitive data mining. Comput Electr Eng 45:134–140
Bhat TP, Karthik C, Chandrasekaran K (2015) A privacy preserved data mining approach based on k-partite graph theory. Proced Comput Sci 54:422–430
Ferrag MA, Maglaras LA, Janicke H, Jiang J, Shu L (2018) A systematic review of data protection and privacy preservation schemes for smart grid communications. Sustain Cities Soc 38:806–835
Madhuri B, Aniruddha G, Rahul R (2013) Identification and classification of flood prone areas using AHP, GIS and GPS. Disaster Adv 6(11):120–131
Kong Q, Lu R, Ma M, Bao H (2019) A privacy-preserving sensory data sharing scheme in Internet of Vehicles. Future Gener Comput Syst 92:644–655
Wei R, Tian H, Shen H (2018) Improving k-anonymity based privacy preservation for collaborative filtering. Comput Electr Eng 67:509–519
Diyanat A, Khonsari A, Shafiei H (2017) Preservation of temporal privacy in body sensor networks. J Netw Comput Appl 96:62–71
Romanou A (2018) The necessity of the implementation of Privacy by Design in sectors where data protection concerns arise. Comput Law Secur Rev 34(1):99–110
Sánchez D, Batet M (2017) Privacy-preserving data outsourcing in the cloud via semantic data splitting. Comput Commun 110:187–201
Liu C, Shang Z, Tang YY (2016) An image classification method that considers privacy-preservation. Neurocomputing 208:80–98
Jayaraman PP, Yang X, Yavari A, Georgakopoulos D, Yi X (2017) Privacy preserving Internet of Things: from privacy techniques to a blueprint architecture and efficient implementation. Fut Gener Comput Syst 76:540–549
Waqar A, Raza A, Abbas H, Khan MK (2013) A framework for preservation of cloud users’ data privacy using dynamic reconstruction of metadata. J Netw Comput Appl 36(1):235–248
Zhang K, Liang X, Baura M, Lu R, Shen XS (2014) PHDA: A priority based health data aggregation with privacy preservation for cloud assisted WBANs. Inf Sci 284:130–141
Wang N, Zhao X (2017) 2D vector map data hiding with directional relations preservation between points. AEU Int J Electron Commun 71:118–124
Luo H, Yu FX, Chen H, Huang ZL, Li H, Wang PH (2011) Reversible data hiding based on block median preservation. Inf Sci 181(2):308–328
Upadhyay S, Sharma C, Sharma P, Bharadwaj P, Seeja KR (2018) Privacy preserving data mining with 3-D rotation transformation. J King Saud Univ Comput Inf Sci 30(4):524–530
KumarTripathi K (2016) Discrimination prevention with classification and privacy preservation in data mining. Proced Comput Sci 79:244–253
Verykios VS, Elmagarmid AK, Bertino E, Saygin Y, Dasseni E (2004) Association rule hiding. IEEE Trans Knowl Data Eng 16(4):434–447
Cheng P, Lee I, Lin C-W, Pan J-S (2016) Association rule hiding based on evolutionary multi-objective optimization. Intell Data Anal 20(3):495–514
Cheng P, Lee I, Pan JS, Lin CW, Roddick JF (2015) Hide association rules with fewer side effects. IEICE Trans Inf Syst 98(10):1788–1798
Menaga D, Revathi S (2018) Least lion optimisation algorithm (LLOA) based secret key generation for privacy preserving association rule hiding. IET Inf Secur 12(4):332–340
Verykios VS, Pontikakis ED, Theodoridis Y, Chang L (2007) Efficient algorithms for distortion and blocking techniques in association rule hiding. Distrib Parallel Databases 22(1):85–104
Sun X, Yu PS (2005) A border-based approach for hiding sensitive frequent itemsets. In: Proceedings of the Fifth IEEE international conference on data mining (ICDM), pp 426–433
Saygin Y, Verykios VS, Clifton C (2001) Using unknowns to prevent discovery of association rules. ACM SIGMOD Record 30(4):45–54
Peng M, Chen M, Zhou H, Wan Q, Chen L (2018) Hybrid PAPR reduction scheme with Huffman coding and DFT-spread technique for direct-detection optical OFDM systems. Opt Fiber Technol 40:1–7
Qin C, Ma X, Hua T, Zhao J, Yu H, Zhang J (2017) Golay sequences coded coherent optical OFDM for long-haul transmission. Opt Commun 399:52–55
Kondo Y, Numada M, Koshimizu H, Kamiya K, Yoshid I (2016) The filtering method to calculate the transmission characteristics of the low-pass filters using actual measurement data. Precis Eng 44:55–61
Vrionis TD, Koutiva XI, Vovos NA (2013) A genetic algorithm-based low voltage ride-through control strategy for grid connected doubly fed induction wind generators. IEEE Trans Power Syst 29(3):1325–1334
Fernández JR, López-Campos JA, Segade A, Vilán JA (2018) A genetic algorithm for the characterization of hyperelastic materials. Appl Math Comput 329:239–250
Askarzadeh A (2016) A novel metaheuristic method for solving constrained engineering optimization problems: crow search algorithm. Comput Struct 169:1–12
Navale GS, Mali SN. Self–adaptive optimization for improved data sanitization and restoration. Int J Uncertainty Fuzziness Knowl-Based Syst (accepted)
Navale GS, Mali SN (2018) Lossless and robust privacy preservation of association rules in data sanitization. Clust Comput 22(1):1415–1428
Zhang J, Xia P (2017) An improved PSO algorithm for parameter identification of nonlinear dynamic hysteretic models. J Sound Vib 389:153–167
Wu G, Shen X, Li H, Chen H, Lin A, Suganthan PN (2018) Ensemble of differential evolution variants. Inf Sci 423:172–186
Lu L, Chen S (2013) A compress slide attack on the full GOST block cipher. Inf Process Lett 113(17):634–639
Lin D, Jie G (2012) Related key chosen IV attacks on Decim v2 and Decim-128. Math Comput Model 55:123–133
Zhang LY, Liu Y, Wang C, Zhou J, Zhang Y, Chen G (2018) Improved known-plaintext attack to permutation-only multimedia ciphers. Inf Sci 430:228–239
Wu J, Liu W, Liu Z, Liu S (2015) Correlated-imaging-based chosen plaintext attack on general cryptosystems composed of linear canonical transforms and phase encodings. Opt Commun 338:164–167
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Navale, G.S., Mali, S.N. A multi-analysis on privacy preservation of association rules using hybridized approach. Evol. Intel. 15, 1051–1065 (2022). https://doi.org/10.1007/s12065-019-00277-8
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12065-019-00277-8