Information Security Commons^™

Biometrics Based Privacy-Preserving Authentication And Mobile Template Protection, Wencheng Yang, Jiankun Hu, Song Wang, Qianhong Wu

Research outputs 2014 to 2021

Smart mobile devices are playing a more and more important role in our daily life. Cancelable biometrics is a promising mechanism to provide authentication to mobile devices and protect biometric templates by applying a noninvertible transformation to raw biometric data. However, the negative effect of nonlinear distortion will usually degrade the matching performance significantly, which is a nontrivial factor when designing a cancelable template. Moreover, the attacks via record multiplicity (ARM) present a threat to the existing cancelable biometrics, which is still a challenging open issue. To address these problems, in this paper, we propose a new cancelable fingerprint template …

An Efficient Privacy-Preserving Outsourced Computation Over Public Data, Ximeng Liu, Baodong Qin, Robert H. Deng, Yingjiu Li

Research Collection School Of Computing and Information Systems

In this paper, we propose a new efficient privacy preserving outsourced computation framework over public data, called EPOC. EPOC allows a user to outsource the computation of a function over multi-dimensional public data to the cloud while protecting the privacy of the function and its output. Specifically, we introduce three types of EPOC in order to tradeoff different levels of privacy protection and performance. We present a new cryptosystem called Switchable Homomorphic Encryption with Partial Decryption (SHED) as the core cryptographic primitive for EPOC.We introduce two coding techniques, called message pre-coding and message extending and coding respectively, for messages encrypted …

Dynamic Information Flow Analysis In Ruby, Vigneshwari Chandrasekaran

Master's Projects

With the rapid increase in usage of the internet and online applications, there is a huge demand for applications to handle data privacy and integrity. Applications are already complex with business logic; adding the data safety logic would make them more complicated. The more complex the code becomes, the more possibilities it opens for security-critical bugs. To solve this conundrum, we can push this data safety handling feature to the language level rather than the application level. With a secure language, developers can write their application without having to worry about data security.

This project introduces dynamic information flow analysis …

Dpweka: Achieving Differential Privacy In Weka, Srinidhi Katla

Graduate Theses and Dissertations

Organizations belonging to the government, commercial, and non-profit industries collect and store large amounts of sensitive data, which include medical, financial, and personal information. They use data mining methods to formulate business strategies that yield high long-term and short-term financial benefits. While analyzing such data, the private information of the individuals present in the data must be protected for moral and legal reasons. Current practices such as redacting sensitive attributes, releasing only the aggregate values, and query auditing do not provide sufficient protection against an adversary armed with auxiliary information. In the presence of additional background information, the privacy protection …

The Rise Of Cybersecurity And Its Impact On Data Protection, Fred H. Cate, Christopher Kuner, Dan Jerker B. Svantesson, Orla Lynskey, Christopher Millard

Articles by Maurer Faculty

No abstract provided.

Data Protection And Humanitarian Emergencies, Fred H. Cate, Christopher Kuner, Dan Jerker B. Svantesson, Orla Lynskey, Christopher Millard

Articles by Maurer Faculty

No abstract provided.

Developing An Abac-Based Grant Proposal Workflow Management System, Milson Munakami

Boise State University Theses and Dissertations

In the advent of the digital transformation, online business processes need to be automated and modeled as workflows. A workflow typically involves a sequence of coordinated tasks and shared data that need to be secured and protected from unauthorized access. In other words, a workflow can be described simply as the movement of documents and activities through a business process among different users. Such connected flow of information among various users with different permission level offers many benefits along with new challenges. Cyber threats are becoming more sophisticated as skilled and motivated attackers both insiders and outsiders are equipped with …

Privacy-Preserving Outsourced Calculation On Floating Point Numbers, Ximeng Liu, Robert H. Deng, Wenxiu Ding, Rongxing Lu

Research Collection School Of Computing and Information Systems

In this paper, we propose a framework for privacy-preserving outsourced calculation on floating point numbers (POCF). Using POCF, a user can securely outsource the storing and processing of floating point numbers to a cloud server without compromising on the security of the (original) data and the computed results. In particular, we first present privacy-preserving integer processing protocols for common integer operations. We then present an approach to outsourcing floating point numbers for storage in a privacy-preserving way, and securely processing commonly used floating point number operations on-the-fly. We prove that the proposed POCF achieves the goal of floating point number …

Privacy-Preserving And Verifiable Data Aggregation, Ngoc Hieu Tran, Robert H. Deng, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

There are several recent research studies on privacy-preserving aggregation of time series data, where an aggregator computes an aggregation of multiple users' data without learning each individual's private input value. However, none of the existing schemes allows the aggregation result to be verified for integrity. In this paper, we present a new data aggregation scheme that protects user privacy as well as integrity of the aggregation. Towards this end, we first propose an aggregate signature scheme in a multi-user setting without using bilinear maps. We then extend the aggregate signature scheme into a solution for privacy-preserving and verifiable data aggregation. …

On Indistinguishability In Remote Data Integrity Checking, Xinyu Fan, Guomin Yang, Yi Mu, Yong Yu

Research Collection School Of Computing and Information Systems

With a rapid growth of data storage in the cloud, data integrity checking in a remote data storage system has become an important issue. A number of protocols, which allow remote integrity checking by a third party, have been proposed. Although those protocols are provably secure, the data privacy issues in those protocols have not been considered. We believe that these issues are equally important since the communication flows of integrity proofs from the cloud server should not reveal any useful information of the stored data. In this paper, we introduce a new definition of data privacy called ‘INDPrivacy’ by …

Reconstruction Privacy: Enabling Statistical Learning, Ke Wang, Chao Han, Ada Waichee Fu, Raymond C. Wong, Philip S. Yu

Research Collection School Of Computing and Information Systems

Non-independent reasoning (NIR) allows the information about one record in the data to be learnt from the information of other records in the data. Most posterior/prior based privacy criteria consider NIR as a privacy violation and require to smooth the distribution of published data to avoid sensitive NIR. The drawback of this approach is that it limits the utility of learning statistical relationships. The differential privacy criterion considers NIR as a non-privacy violation, therefore, enables learning statistical relationships, but at the cost of potential disclosures through NIR. A question is whether it is possible to (1) allow learning statistical relationships, …

The Data Protection Credibility Crisis, Fred H. Cate, Christopher Kuner, Christopher Millard, Dan Jerker B. Svantesson, Orla Lynskey

Articles by Maurer Faculty

No abstract provided.

Taking Stock After Four Years, Fred H. Cate, Christopher Kuner, Christopher Millard, Dan Jerker B. Svantesson

Articles by Maurer Faculty

No abstract provided.

Is Your Online Data Really Private?, Nathan Pitchaikani

A with Honors Projects

In the present age everyone depends on technology. At least once per day someone uses a machine to help them accomplish their tasks. For example, imagine not using a cell phone for a whole day. These days, machines contain personal information or data about their owner. In most cases this isn’t an issue. However, with technology becoming more advanced day by day, there has become a reason to worry. People are able to illegally enter other people’s computers and steal information. Leading to the point that being able to protect one’s personal data is crucial. Learning how to safeguard one’s …

The (Data Privacy) Law Hasn't Even Checked In When Technology Takes Off, Fred H. Cate, Christopher Kuner, Christopher Millard, Dan Jerker B. Svantesson

Articles by Maurer Faculty

No abstract provided.

Systematic Government Access To Private-Sector Data Redux, Fred H. Cate, Christopher Kuner, Christopher Millard, Dan Jerker B. Svantesson

Articles by Maurer Faculty

No abstract provided.

Prism And Privacy: Will This Change Everything?, Fred H. Cate, Christopher Kuner, Christopher Millard, Dan Jerker B. Svantesson

Articles by Maurer Faculty

No abstract provided.

The Extraterritoriality Of Data Privacy Laws -- An Explosive Issue Yet To Detonate, Fred H. Cate, Christopher Kuner, Christopher Millard, Dan Jerker B. Svantesson

Articles by Maurer Faculty

No abstract provided.

The Business Of Privacy, Fred H. Cate, Christopher Kuner, Christopher Millard, Dan Jerker B. Svantesson

Articles by Maurer Faculty

No abstract provided.

Face-To-Data -- Another Developing Privacy Threat?, Fred H. Cate, Christopher Kuner, Christopher Millard, Dan Jerker B. Svantesson

Articles by Maurer Faculty

No abstract provided.

The Intricacies Of Independence, Fred H. Cate, Christopher Kuner, Christopher Millard, Dan Jerker B. Svantession

Articles by Maurer Faculty

No abstract provided.

The Challenge Of "Big Data" For Data Protection, Fred H. Cate, Christopher Kuner, Christopher Millard, Dan Jerker B. Svantesson

Articles by Maurer Faculty

No abstract provided.

Systematic Government Access To Private-Sector Data, Fred H. Cate, James X. Dempsey, Ira S. Rubenstein

Articles by Maurer Faculty

No abstract provided.

The End Of The Beginning, Fred H. Cate, Christopher Kuner, Christopher Millard, Dan Jerker B. Svantesson

Articles by Maurer Faculty

No abstract provided.

Network Security: Privacy-Preserving Data Publication: A Review On “Updates” In Continuous Data Publication, Adeel Anjum, Guillaume Raschia

International Conference on Information and Communication Technologies

Preserving the privacy of individuals while publishing their relevant data has been an important problem. Most of previous works in privacy preserving data publication focus on one time, static release of datasets. In multiple publications however, where data is published multiple times, these techniques are unable to ensure privacy of the concerned individuals as just joining either of the releases could result in identity disclosure. In this work, we tried to investigate the major findings in the scenario of continuous data publication, in which the data is not only published multiple times but also modified with INSERTS, UPDATES and DELETE …

Database Access Pattern Protection Without Full-Shuffles, Xuhua Ding, Yanjiang Yang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Privacy protection is one of the fundamental security requirements for database outsourcing. A major threat is information leakage from database access patterns generated by query executions. The standard private information retrieval (PIR) schemes, which are widely regarded as theoretical solutions, entail O(n) computational overhead per query for a database with items. Recent works propose to protect access patterns by introducing a trusted component with constant storage size. The resulting privacy assurance is as strong as PIR, though with O(1) online computation cost, they still have O(n) amortized cost per query due to periodically full database shuffles. In this paper, we …

Let's Not Kill All The Privacy Laws (And Lawyers), Fred H. Cate, Christopher Kuner, Christopher Millard, Dan Jerker B. Svantesson

Articles by Maurer Faculty

No abstract provided.

Privacy -- An Elusive Concept, Fred H. Cate, Christopher Kuner, Christopher Millard, Dan Jerker B. Svantesson

Articles by Maurer Faculty

No abstract provided.

Editorial, Fred H. Cate, Christopher Kuner, Christopher Millard, Dan Jerker B. Svantesson

Articles by Maurer Faculty

No abstract provided.

Moving Forward Together, Fred H. Cate, Christopher Kuner, Christopher Millard, Dan Jerker B. Svantesson

Articles by Maurer Faculty

No abstract provided.