Physical Sciences and Mathematics Commons^™

Architectural Design Of A Blockchain-Enabled, Federated Learning Platform For Algorithmic Fairness In Predictive Health Care: Design Science Study, Xueping Liang, Juan Zhao, Yan Chen, Eranga Bandara, Sachin Shetty

VMASC Publications

Background: Developing effective and generalizable predictive models is critical for disease prediction and clinical decision-making, often requiring diverse samples to mitigate population bias and address algorithmic fairness. However, a major challenge is to retrieve learning models across multiple institutions without bringing in local biases and inequity, while preserving individual patients' privacy at each site.

Objective: This study aims to understand the issues of bias and fairness in the machine learning process used in the predictive health care domain. We proposed a software architecture that integrates federated learning and blockchain to improve fairness, while maintaining acceptable prediction accuracy and minimizing overhead …

A Novel Qkd Approach To Enhance Iiot Privacy And Computational Knacks, Kranthi Kumar Singamaneni, Gaurav Dhiman, Sapna Juneja, Ghulam Muhammad, Salman A Alqahtani, John Zaki

Journal Articles

The industry-based internet of things (IIoT) describes how IIoT devices enhance and extend their capabilities for production amenities, security, and efficacy. IIoT establishes an enterprise-to-enterprise setup that means industries have several factories and manufacturing units that are dependent on other sectors for their services and products. In this context, individual industries need to share their information with other external sectors in a shared environment which may not be secure. The capability to examine and inspect such large-scale information and perform analytical protection over the large volumes of personal and organizational information demands authentication and confidentiality so that the total data …

Assessing The Reidentification Risks Posed By Deep Learning Algorithms Applied To Ecg Data, Arin Ghazarian, Jianwei Zheng, Daniele Struppa, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

ECG (Electrocardiogram) data analysis is one of the most widely used and important tools in cardiology diagnostics. In recent years the development of advanced deep learning techniques and GPU hardware have made it possible to train neural network models that attain exceptionally high levels of accuracy in complex tasks such as heart disease diagnoses and treatments. We investigate the use of ECGs as biometrics in human identification systems by implementing state-of-the-art deep learning models. We train convolutional neural network models on approximately 81k patients from the US, Germany and China. Currently, this is the largest research project on ECG identification. …

Thaw Publications, Carl Landwehr, David Kotz

Computer Science Technical Reports

In 2013, the National Science Foundation's Secure and Trustworthy Cyberspace program awarded a Frontier grant to a consortium of four institutions, led by Dartmouth College, to enable trustworthy cybersystems for health and wellness. As of this writing, the Trustworthy Health and Wellness (THaW) project's bibliography includes more than 130 significant publications produced with support from the THaW grant; these publications document the progress made on many fronts by the THaW research team. The collection includes dissertations, theses, journal papers, conference papers, workshop contributions and more. The bibliography is organized as a Zotero library, which provides ready access to citation materials …

Lightweight And Privacy-Aware Fine-Grained Access Control For Iot-Oriented Smart Health, Jianfei Sun, Hu Xiong, Ximeng Liu, Yinghui Zhang, Xuyun Nie, Robert H. Deng

Research Collection School Of Computing and Information Systems

With the booming of Internet of Things (IoT), smart health (s-health) is becoming an emerging and attractive paradigm. It can provide an accurate prediction of various diseases and improve the quality of healthcare. Nevertheless, data security and user privacy concerns still remain issues to be addressed. As a high potential and prospective solution to secure IoT-oriented s-health applications, ciphertext policy attribute-based encryption (CP-ABE) schemes raise challenges, such as heavy overhead and attribute privacy of the end users. To resolve these drawbacks, an optimized vector transformation approach is first proposed to efficiently transform the access policy and user attribute set into …

On Privacy-Aware Escience Workflows, Khalid Belhajjame, Noura Faci, Zakaria Maamar, Vanilson Burégio, Edvan Soares, Mahmoud Barhamgi

All Works

© 2020, Springer-Verlag GmbH Austria, part of Springer Nature. Computing-intensive experiments in modern sciences have become increasingly data-driven illustrating perfectly the Big-Data era. These experiments are usually specified and enacted in the form of workflows that would need to manage (i.e., read, write, store, and retrieve) highly-sensitive data like persons’ medical records. We assume for this work that the operations that constitute a workflow are 1-to-1 operations, in the sense that for each input data record they produce a single data record. While there is an active research body on how to protect sensitive data by, for instance, anonymizing datasets, …

Secure Smart Health With Privacy-Aware Aggregate Authentication And Access Control In Internet Of Things, Yinghui Zhang, Robert H. Deng, Gang Han, Dong Zheng

Research Collection School Of Computing and Information Systems

With the rapid technological advancements in the Internet of Things (IoT), wireless communication and cloud computing, smart health is expected to enable comprehensive and qualified healthcare services. It is important to ensure security and efficiency in smart health. However, existing smart health systems still have challenging issues, such as aggregate authentication, fine-grained access control and privacy protection. In this paper, we address these issues by introducing SSH, a Secure Smart Health system with privacy-aware aggregate authentication and access control in IoT. In SSH, privacy-aware aggregate authentication is enabled by an anonymous certificateless aggregate signature scheme, in which users' identity information …

Workshop On Emerging Technology And Data Analytics For Behavioral Health, David Kotz, Sarah E. Lord, A. James O'Malley, Luke Stark, Lisa Marsch

Dartmouth Scholarship

Wearable and portable digital devices can support self-monitoring for patients with chronic medical conditions, individuals seeking to reduce stress, and people seeking to modify health-related behaviors such as substance use or overeating. The resulting data may be used directly by a consumer, or shared with a clinician for treatment, a caregiver for assistance, or a health coach for support. The data can also be used by researchers to develop and evaluate just-in-time interventions that leverage mobile technology to help individuals manage their symptoms and behavior in real time and as needed. Such wearable systems have huge potential for promoting delivery …

Exploring Security, Privacy, And Reliability Strategies To Enable The Adoption Of Iot, Daud Alyas Kamin

Walden Dissertations and Doctoral Studies

The Internet of things (IoT) is a technology that will enable machine-to-machine communication and eventually set the stage for self-driving cars, smart cities, and remote care for patients. However, some barriers that organizations face prevent them from the adoption of IoT. The purpose of this qualitative exploratory case study was to explore strategies that organization information technology (IT) leaders use for security, privacy, and reliability to enable the adoption of IoT devices. The study population included organization IT leaders who had knowledge or perceptions of security, privacy, and reliability strategies to adopt IoT at an organization in the eastern region …

Privacy Protection And Aggregate Health Data: A Review Of Tabular Cell Suppression Methods (Not) Employed In Public Health Data Systems, Gregory J. Matthews, Ofer Harel, Robert H. Aseltine Jr.

Mathematics and Statistics: Faculty Publications and Other Works

Public health research often relies on individuals’ confidential medical data. Therefore, data collecting entities, such as states, seek to disseminate this medical data as widely as possible while still maintaining the privacy of the individual for legal and ethical reasons. One common way in which this medical data is released is through the use of Web-based Data Query Systems (WDQS). In this article, we examined WDQS listed in the National Association for Public Health Statistics and Information Systems (NAPHSIS) specifically reviewing them for how they prevent statistical disclosure in queries that produce a tabular response. One of the most common …

Privacy And Security In Mobile Health – A Research Agenda, David Kotz, Carl A. Gunter, Santosh Kumar, Jonathan P. Weiner

Dartmouth Scholarship

Mobile health technology has great potential to increase healthcare quality, expand access to services, reduce costs, and improve personal wellness and public health. However, mHealth also raises significant privacy and security challenges.

Privacy And Accountability In Black-Box Medicine, Roger Allan Ford, W. Nicholson Price Ii

Law Faculty Scholarship

Black-box medicine—the use of big data and sophisticated machine learning techniques for health-care applications—could be the future of personalized medicine. Black-box medicine promises to make it easier to diagnose rare diseases and conditions, identify the most promising treatments, and allocate scarce resources among different patients. But to succeed, it must overcome two separate, but related, problems: patient privacy and algorithmic accountability. Privacy is a problem because researchers need access to huge amounts of patient health information to generate useful medical predictions. And accountability is a problem because black-box algorithms must be verified by outsiders to ensure they are accurate and …

Privacy And Security Issues In Iot Healthcare Applications For The Disabled Users A Survey, Wassnaa Al-Mawee

Masters Theses

Aging of the population resulted in new challenges for the society and healthcare systems. Ambient Assisted Living (AAL) that depends on Internet of Things (IoT) provides assistance to the disabled people and supports their vital daily life activities. Affordability of and accessibility to AAL and the usage of IoT starts revolutionizing healthcare services. This Thesis is a survey of the privacy and security issues in IoT healthcare applications for the disabled users. Introduction includes definitions of privacy and security terms, and discusses their relationship. Then, it presents an overview of the IoT, including its architecture and components. Next, the Thesis …

Privacy In Mobile Technology For Personal Healthcare, Sasikanth Avancha, Amit Baxi, David Kotz

Dartmouth Scholarship

Information technology can improve the quality, efficiency, and cost of healthcare. In this survey, we examine the privacy requirements of \emphmobile\/ computing technologies that have the potential to transform healthcare. Such \emphmHealth\/ technology enables physicians to remotely monitor patients' health, and enables individuals to manage their own health more easily. Despite these advantages, privacy is essential for any personal monitoring technology. Through an extensive survey of the literature, we develop a conceptual privacy framework for mHealth, itemize the privacy properties needed in mHealth systems, and discuss the technologies that could support privacy-sensitive mHealth systems. We end with a list of …

Understanding Sharing Preferences And Behavior For Mhealth Devices, Aarathi Prasad, Jacob Sorber, Timothy Stablein, Denis Anthony, David Kotz

Dartmouth Scholarship

mHealth devices offer many potential benefits to patients, health providers and others involved in the patients' healthcare. If patients are not in control of the collection and sharing of their personal health information, they will have privacy concerns even while enjoying the benefits of the devices. We investigated patients' willingness to share their personal health information, collected using mHealth devices, with their family, friends, third parties and the public. Our findings are based on a user study conducted with 41 participants. The best way to understand people's privacy concerns is to give them the opportunity to use the device and …

Passive Biometrics For Pervasive Wearable Devices (Poster Paper), Cory Cornelius, Zachary Marois, Jacob Sorber, Ron Peterson, Shrirang Mare, David Kotz

Dartmouth Scholarship

Wearable devices – like the FitBit, MOTOACTV, and Jawbone UP – are increasingly becoming more pervasive whether for monitoring health and fitness, personal assistance, or home automation. While pervasive wearable devices have long been researched, we are now beginning to see the fruits of this research in the form of commercial offerings. Today, many of these commercial wearable devices are closed systems that do not interoperate with other devices a person might carry. We believe, however, these commercial offerings signal the coming of wireless body-area networks that will connect these pervasive wearable devices and leverage existing devices a user already …

An Amulet For Trustworthy Wearable Mhealth, Jacob Sorber, Minho Shin, Ronald Peterson, Cory Cornelius, Shrirang Mare, Aarathi Prasad, Zachary Marois, Emma N. Smithayer, David Kotz

Dartmouth Scholarship

Mobile technology has significant potential to help revolutionize personal wellness and the delivery of healthcare. Mobile phones, wearable sensors, and home-based tele-medicine devices can help caregivers and individuals themselves better monitor and manage their health. While the potential benefits of this “mHealth” technology include better health, more effective healthcare, and reduced cost, this technology also poses significant security and privacy challenges. In this paper we propose \emphAmulet, an mHealth architecture that provides strong security and privacy guarantees while remaining easy to use, and outline the research and engineering challenges required to realize the Amulet vision.

Adapt-Lite: Privacy-Aware, Secure, And Efficient Mhealth Sensing, Shrirang Mare, Jacob Sorber, Minho Shin, Cory Cornelius, David Kotz

Dartmouth Scholarship

As healthcare in many countries faces an aging population and rising costs, mobile sensing technologies promise a new opportunity. Using mobile health (mHealth) sensing, which uses medical sensors to collect data about the patients, and mobile phones to act as a gateway between sensors and electronic health record systems, caregivers can continuously monitor the patients and deliver better care. Although some work on mHealth sensing has addressed security, achieving strong security and privacy for low-power sensors remains a challenge. \par We make three contributions. First, we propose Adapt-lite, a set of two techniques that can be applied to existing wireless …

Adaptive Security And Privacy For Mhealth Sensing, Shrirang Mare, Jacob Sorber, Minho Shin, Cory Cornelius, David Kotz

Dartmouth Scholarship

As healthcare in many countries faces an aging population and rising costs, mobile Health (mHealth) sensing technologies promise a new opportunity. However, the privacy concerns associated with mHealth sensing are a limiting factor for their widespread adoption. The use of wireless body area networks pose a particular challenge. Although there exist protocols that provide a secure and private communication channel between two devices, the large transmission overhead associated with these protocols limit their application to low-power mHealth sensing devices. We propose an adaptive security model that enables use of privacy-preserving protocols in low-power mHealth sensing by reducing the network overhead …

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 …

A Threat Taxonomy For Mhealth Privacy, David Kotz

Dartmouth Scholarship

Networked mobile devices have great potential to enable individuals (and their physicians) to better monitor their health and to manage medical conditions. In this paper, we examine the privacy-related threats to these so-called \emphmHealth\/ technologies. We develop a taxonomy of the privacy-related threats, and discuss some of the technologies that could support privacy-sensitive mHealth systems. We conclude with a brief summary of research challenges.

Privacy-Preserving Assessment Of Location Data Trustworthiness, Chenyun Dai, Fang-Yu Rao, Gabriel Ghinita, Elisa Bertino

Cyber Center Publications

Assessing the trustworthiness of location data corresponding to individuals is essential in several applications, such as forensic science and epidemic control. To obtain accurate and trustworthy location data, analysts must often gather and correlate information from several independent sources, e.g., physical observation, witness testimony, surveillance footage, etc. However, such information may be fraudulent, its accuracy may be low, and its vol-
ume may be insufficient to ensure highly trustworthy data. On the other hand, recent advancements in mobile computing and positioning systems, e.g., GPS-enabled cell phones, highway sensors, etc., bring new and effective technological means to track the location of …

Is Bluetooth The Right Technology For Mhealth?, Shrirang Mare, David Kotz

Dartmouth Scholarship

Many people believe mobile healthcare (mHealth) would help alleviate the rising cost of healthcare and improve the quality of service. Bluetooth, which is the most popular wireless technology for personal medical devices, is used for most of the mHealth sensing applications. In this paper we raise the question – Is Bluetooth the right technology for mHealth? To instigate the discussion we discuss some shortcomings of Bluetooth and also point out an alternative solution.

Can I Access Your Data? Privacy Management In Mhealth, Aarathi Prasad, David Kotz

Dartmouth Scholarship

Mobile health (mHealth) has become important in the field of healthcare information technology, as patients begin to use mobile medical sensors to record their daily activities and vital signs. Since their medical data is collected by their sensors, the patients may wish to control data collection and distribution, so as to protect their data and share it only when the need arises. It must be possible for patients to grant or deny access to the data on the storage unit (mobile phones or personal health records (PHR)). Thus, an efficient framework is required for managing patient consent electronically, i.e.to allow …

Privometer: Privacy Protection In Social Networks, Nilothpal Talukder, Mourad Ouzzani, Ahmed Elmagarmid, Hazem Elmeleegy

Cyber Center Publications

The increasing popularity of social networks, such as Facebook and Orkut, has raised several privacy concerns. Traditional ways of safeguarding privacy of personal information by hiding sensitive attributes are no longer adequate. Research shows that probabilistic classification techniques can effectively infer such private information. The disclosed sensitive information of friends, group affiliations and even participation in activities, such as tagging and commenting, are considered background knowledge in this process. In this paper, we present a privacy protection tool, called Privometer, that measures the amount of sensitive information leakage in a user profile and suggests selfsanitization actions to regulate the amount …

A Privacy Framework For Mobile Health And Home-Care Systems, David Kotz, Sasikanth Avancha, Amit Baxi

Dartmouth Scholarship

In this paper, we consider the challenge of preserving patient privacy in the context of mobile healthcare and home-care systems, that is, the use of mobile computing and communications technologies in the delivery of healthcare or the provision of at-home medical care and assisted living. This paper makes three primary contributions. First, we compare existing privacy frameworks, identifying key differences and shortcomings. Second, we identify a privacy framework for mobile healthcare and home-care systems. Third, we extract a set of privacy properties intended for use by those who design systems and applications for mobile healthcare and home-care systems, linking them …

Beyond K-Anonymity: A Decision Theoretic Framework For Assessing Privacy Risk, Guy Lebanon, Monica Scannapieco, Mohamed Fouad, Elisa Bertino

Cyber Center Publications

An important issue any organization or individual has to face when managing data containing sensitive information, is the risk that can be incurred when releasing such data. Even though data may be sanitized before being released, it is still possible for an adversary to reconstruct the original data using additional information thus resulting in privacy violations. To date, however, a systematic approach to quantify such risks is not available. In this paper we develop a framework, based on statistical decision theory, that assesses the relationship between the disclosed data and the resulting privacy risk. We model the problem of deciding …

Private Queries And Trajectory Anonymization: A Dual Perspective On Location Privacy, Gabriel Ghinita

Cyber Center Publications

The emergence of mobile devices with Internet connectivity (e.g., Wi-Fi) and global positioning capabilities (e.g., GPS) have triggered the widespread development of location-based applications. For instance, users are able to ask queries about points of interest in their proximity. Furthermore, users can act as mobile sensors to monitor traffic flow, or levels of air pollution. However, such applications require users to disclose their locations, which raises serious privacy concerns. With knowledge of user locations, a malicious attacker can infer sensitive information, such as alternative lifestyles or political affiliations. Preserving location privacy is an essential requirement towards the successful deployment of …

Location Privacy In Moving-Object Environments, Dan Lin, Elisa Bertino, Reynold Cheng, Sunil Prabhakar

Cyber Center Publications

The expanding use of location-based services has profound implications on the privacy of personal information. If no adequate protection is adopted, information about movements of specific individuals could be disclosed to unauthorized subjects or organizations, thus resulting in privacy breaches. In this paper, we propose a framework for preserving location privacy in moving-object environments. Our approach is based on the idea of sending to the service provider suitably modified location information. Such modifications, that include transformations like scaling, are performed by agents interposed between users and service providers. Agents execute data transformation and the service provider directly processes the transformed …