(τ, m)-slicedBucket privacy model for sequential anonymization for improving privacy and utility

Khan，Razaullah1; Tao，Xiaofeng1; Anjum，Adeel2,3; Malik，Saifur Rehman4; Yu，Shui5; Khan，Abid6; Rahman，Waheedur7; Malik，Hassan8

2020

10.1002/ett.4130

Transactions on Emerging Telecommunications Technologies   影响因子和分区

2161-5748

2161-3915

In a real-world scenario for privacy-preserving data publishing, the original data are anonymized and released periodically. Each release may vary in number of records due to insert, update, and delete operations. An intruder can combine, that is, correlate different releases to compromise the privacy of the individual records. Most of the literature, such as τ-safety, τ-safe (l, k)-diversity, have an inconsistency in record signatures and adds counterfeit tuples with high generalization that causes privacy breach and information loss. In this paper, we propose an improved privacy model (τ, m)-slicedBucket, having a novel idea of “Cache” table to address these limitations. We indicate that a collusion attack can be performed for breaching the privacy of τ-safe (l, k)-diversity privacy model, and demonstrate it through formal modeling. The objective of the proposed (τ, m)-slicedBucket privacy model is to set a tradeoff between strong privacy and enhanced utility. Furthermore, we formally model and analyze the proposed model to show that the collusion attack is no longer applicable. Extensive experiments reveal that the proposed approach outperforms the existing models.

SCI ; EI

英语

其他

Telecommunications

Telecommunications

WOS:000580524100001

WILEY

20204309387542

Computer Software, Data Handling and Applications:723

2-s2.0-85092942019

Scopus

1.National Engineering Laboratory for Mobile Network Technologies,Beijing University of Posts and Telecommunications,Beijing,China
2.Department of Computer Science and Engineering,Southern University of Science and Technology,Shenzhen,China
3.Department of Computer Science,COMSATS University Islamabad,Islamabad,Pakistan
4.Cybernetica AS Estonia,Tallinn,Estonia
5.Faculty of Engineering and Information Technology,School of Software,University of Technology Sydney,Ultimo,Australia
6.Department of Computer Science,Aberystwyth University,Aberystwyth,United Kingdom
7.Department of Computer Science,University of Peshawar,Peshawar,Pakistan
8.Department of Computer Science,Edge Hill University,Ormskirk,United Kingdom

Khan，Razaullah,Tao，Xiaofeng,Anjum，Adeel,et al. (τ, m)-slicedBucket privacy model for sequential anonymization for improving privacy and utility[J]. Transactions on Emerging Telecommunications Technologies,2020,33.

Khan，Razaullah.,Tao，Xiaofeng.,Anjum，Adeel.,Malik，Saifur Rehman.,Yu，Shui.,...&Malik，Hassan.(2020).(τ, m)-slicedBucket privacy model for sequential anonymization for improving privacy and utility.Transactions on Emerging Telecommunications Technologies,33.

Khan，Razaullah,et al."(τ, m)-slicedBucket privacy model for sequential anonymization for improving privacy and utility".Transactions on Emerging Telecommunications Technologies 33(2020).