Sharing of log data is a valuable step towards the improvement of network security. However, logs often contain sensitive information and organizations are hesitant to share them. Anonymization methods are used for increasing protection, lowering the disclosure risk to a level considered safe. Accordingly, a metric for anonymity is necessary to quantitatively assess the risk before releasing lo...

In recent years the amount of digital data in the world has risen immensely. But, the more information exists, the greater is the possibility of its unwanted disclosure. Thus, the data privacy protection has become a pressing problem of the present time. The task of individual privacy-preserving is being thoroughly studied nowadays. At the same time, the problem of statistical disclosure contro...

Although Named Data Networking (NDN) architecture introduced security mechanisms and built the NDN basic service model, there are still privacy challenges such as consumer identity privacy, signer identity privacy, the disclosure of the ISP based on the identity privacy information, and the third party attack. Under the NDN basic service model, we analyze these privacy problems in detail and es...

Social networking sites (SNS) such as Facebook have created a new way for individuals to share personal data and interact with each other on the Internet. The disclosure of this personal data is directly tied to the existing relationships of individuals within an SNS. Individual privacy settings allow a selective disclosure of personal data to specific connected individuals. In this paper, we p...

Disclosure limitation involves the application of statistical tools to limit the identification of information on individuals (and enterprises) included as part of statistical data bases such as censuses and sample surveys. We outline the major issues involved in assessing disclosure risk and assuring the protection of confidentiality for data bases, especially those in the form of multi-way co...

This paper focuses on a combination of two disclosure limitation techniques, additive noise and multiplicative bias, and studies their efficacy in protecting confidentiality of continuous microdata. A Bayesian intruder model is extensively simulated in order to assess the performance of these disclosure limitation techniques as a function of key parameters like the variability amongst profiles ...

INTRODUCTION Publicly reported information on the environmental behavior of firms can increase the efficacy of private markets as a mechanism to control environmental malfeasance through liability for harm, consumer demand response, and shareholder reaction. Within the realm of environmental policy, examples exist of both mandatory information disclosure programs such as the EPA’s Toxics Releas...

Emotional disclosure by writing or talking about stressful life experiences improves health status in non-clinical populations, but its success in clinical populations, particularly rheumatoid arthritis (RA), has been mixed. In this randomized, controlled trial, we attempted to increase the efficacy of emotional disclosure by having a trained clinician help patients emotionally disclose and pro...

Several anonymization techniques, such as generalization and bucketization, have been designed for privacy preserving microdata publishing. Recent work has shown that generalization loses considerable amount of information, especially for high-dimensional data. Bucketization, on the other hand, does not prevent membership disclosure and does not apply for data that do not have a clear separatio...