| An empirical investigation of the relationship between change in corporate social performance and financial performance: A stakeholder theory perspective BM Ruf, K Muralidhar, RM Brown, JJ Janney, K Paul Journal of business ethics 32, 143-156, 2001 | 1731 | 2001 |
| The development of a systematic, aggregate measure of corporate social performance BM Ruf, K Muralidhar, K Paul Journal of management 24 (1), 119-133, 1998 | 368 | 1998 |
| A general additive data perturbation method for database security K Muralidhar, R Parsa, R Sarathy management science 45 (10), 1399-1415, 1999 | 248 | 1999 |
| Data shuffling—A new masking approach for numerical data K Muralidhar, R Sarathy Management Science 52 (5), 658-670, 2006 | 213 | 2006 |
| Evaluating Laplace noise addition to satisfy differential privacy for numeric data. R Sarathy, K Muralidhar Trans. Data Priv. 4 (1), 1-17, 2011 | 208 | 2011 |
| Using the analytic hierarchy process for information system project selection K Muralidhar, R Santhanam, RL Wilson Information & Management 18 (2), 87-95, 1990 | 203 | 1990 |
| Fool's gold: an illustrated critique of differential privacy J Bambauer, K Muralidhar, R Sarathy Vand. J. Ent. & Tech. L. 16, 701, 2013 | 113 | 2013 |
| Security of random data perturbation methods K Muralidhar, R Sarathy ACM Transactions on Database Systems (TODS) 24 (4), 487-493, 1999 | 109 | 1999 |
| Accessibility, security, and accuracy in statistical databases: The case for the multiplicative fixed data perturbation approach K Muralidhar, D Batra, PJ Kirs Management Science 41 (9), 1549-1564, 1995 | 96 | 1995 |
| A theoretical basis for perturbation methods K Muralidhar, R Sarathy Statistics and Computing 13, 329-335, 2003 | 76 | 2003 |
| The security of confidential numerical data in databases R Sarathy, K Muralidhar information systems research 13 (4), 389-403, 2002 | 73 | 2002 |
| A zero-one goal programming approach for information system project selection R Santhanam, K Muralidhar, M Schniederjans Omega 17 (6), 583-593, 1989 | 67 | 1989 |
| A Critical Review on the Use (and Misuse) of Differential Privacy in Machine Learning KM Alberto Blanco-Justicia , David Sánchez , Josep Domingo-Ferrer ACM Computing Surveys 55 (8), 1-16, 2022 | 65 | 2022 |
| New directions in anonymization: permutation paradigm, verifiability by subjects and intruders, transparency to users J Domingo-Ferrer, K Muralidhar Information Sciences 337, 11-24, 2016 | 63 | 2016 |
| Perturbing nonnormal confidential attributes: The copula approach R Sarathy, K Muralidhar, R Parsa Management Science 48 (12), 1613-1627, 2002 | 62 | 2002 |
| Secure and useful data sharing R Sarathy, K Muralidhar Decision Support Systems 42 (1), 204-220, 2006 | 58 | 2006 |
| Eight Dimensions of Corporate Social Performance: Determination of Relative Importance Using the Analytic Hierarchy Process. B Ruf, K Muralidhar, K Paul Academy of Management proceedings 1993 (1), 326-330, 1993 | 58 | 1993 |
| Describing processing time when simulating JIT environments K Muralidhar, SR SWENSETHJ, RL Wilson THE INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 30 (1), 1-11, 1992 | 57 | 1992 |
| Privacy in statistical databases J Domingo-Ferrer, Y Saygin Springer, 2008 | 51 | 2008 |
| Some additional insights on applying differential privacy for numeric data R Sarathy, K Muralidhar Privacy in Statistical Databases: UNESCO Chair in Data Privacy …, 2010 | 49 | 2010 |
Rathindra SarathyProfessor of Information Systems, Oklahoma State UniversityEmail verificata su okstate.edu
