Smartphone-based contact-tracing applications are at the epicenter of the global fight against the Covid-19 pandemic. While governments and healthcare agencies are eager to mandate the deployment of such applications en-masse, they face increasing scrutiny from the popular press, security companies, and human rights watch agencies that fear the exploitation of these technologies as surveillance tools. Finding the optimal balance between community safety and privacy has been a challenge, and strategies to address these concerns have varied among countries. This paper describes two important attacks that affect a broad swath of contact-tracing applications. The first, referred to as contact-isolation attack, is a user-privacy attack that can be used to identify potentially infected patients in your neighborhood. The second is a contact-pollution attack that affects the integrity of contact tracing applications by causing them to produce a high volume of false-positive alerts. We developed prototype implementations and evaluated both attacks in the context of the DP-3T application framework, but these vulnerabilities affect a much broader class of applications. We found that both attacks are feasible and realizable with a minimal attacker work factor. We further conducted an impact assessment of these attacks by using a simulation study and measurements from the SafeGraph database. Our results indicate that attacks launched from a modest number (on the order of 10,000) of monitoring points can effectively decloak between 5-40\% of infected users in a major metropolis, such as Houston.
Contact tracing in the COVID-19 pandemic is key to prevent the further spread of COVID-19. Countries and regions around the world have developed and deployed or are considering adopting contact-tracing software or mobile apps. While contact tracing apps and software play an important role in the pandemic, red flags have been raised regarding the privacy risk associated with contact tracing. In this short paper, we provide an overview on the GPS and Bluetooth based contact-tracing apps in the framework of both centralized and decentralized models, examine the associated privacy risk and the eff…
Several contact tracing solutions have been proposed and implemented all around the globe to combat the spread of COVID-19 pandemic. But, most of these solutions endanger the privacy rights of the individuals and hinder their widespread adoption. We propose a privacy-preserving contact tracing protocol for the efficient tracing of the spread of the global pandemic. It is based on the private set intersection (PSI) protocol and utilizes the homomorphic properties to preserve the privacy at the individual level. A hierarchical model for the representation of landscapes and rate-limiting factor o…
With the onset of COVID-19, governments worldwide planned to develop and deploy contact tracing (CT) apps to help speed up the contact tracing process. However, experts raised concerns about the long-term privacy and security implications of using these apps. Consequently, several proposals were made to design privacy-preserving CT apps. To this end, Google and Apple developed the Google/Apple Exposure Notification (GAEN) framework to help public health authorities develop privacy-preserving CT apps. In the United States, 26 states used the GAEN framework to develop their CT apps. In this pape…
How to contain the spread of the COVID-19 virus is a major concern for most countries. As the situation continues to change, various countries are making efforts to reopen their economies by lifting some restrictions and enforcing new measures to prevent the spread. In this work, we review some approaches that have been adopted to contain the COVID-19 virus such as contact tracing, clusters identification, movement restrictions, and status validation. Specifically, we classify available techniques based on some characteristics such as technology, architecture, trade-offs (privacy vs utility), …
The world is under an ongoing pandemic, COVID-19, of a scale last seen a century ago. Contact tracing is one of the most critical and highly effective tools for containing and breaking the chain of infections especially in the case of infectious respiratory diseases like COVID-19. Thanks to the technological progress in our times, we now have digital mobile applications like the Corona-Warn-App for digital contact tracing. However, due to the invasive nature of contact tracing, it is very important to preserve the privacy of the users. Privacy preservation is important for increasing trust in …
During a pandemic, contact tracing is an essential tool to drive down the infection rate within a population. To accelerate the laborious manual contact tracing process, digital contact tracing (DCT) tools can track contact events transparently and privately by using the sensing and signaling capabilities of the ubiquitous cell phone. However, an effective DCT must not only preserve user privacy but also augment the existing manual contact tracing process. Indeed, not every member of a population may own a cell phone or have a DCT app installed and enabled. We present KHOVID to fulfill the com…
Coronavirus disease 2019, i.e. COVID-19 has imposed the public health measure of keeping social distancing for preventing mass transmission of COVID-19. For monitoring the social distancing and keeping the trace of transmission, we are obligated to develop various types of digital surveillance systems, which include contact tracing systems and drone-based monitoring systems. Due to the inconvenience of manual labor, traditional contact tracing systems are gradually replaced by the efficient automated contact tracing applications that are developed for smartphones. However, the commencement of …
We respond to a recent short paper by de Motjoye et el. on privacy issues with Covid-19 tracking. Their paper, which we discuss here, is structured around three "toy protocols" for the design of an app which can maximise the utility of contact tracing information while minimising the more general risk to privacy. On this basis, the paper proceeds to introduce eight questions against which they should be assessed. The questions raised and the protocols proposed effectively amount to the creation of a game with different categories of players able to make different moves. It is therefore possibl…
To fight against infectious diseases (e.g., SARS, COVID-19, Ebola, etc.), government agencies, technology companies and health institutes have launched various contact tracing approaches to identify and notify the people exposed to infection sources. However, existing tracing approaches can lead to severe privacy and security concerns, thereby preventing their secure and widespread use among communities. To tackle these problems, this paper proposes CoAvoid, a decentralized, privacy-preserved contact tracing system that features good dependability and usability. CoAvoid leverages the Google/Ap…
Contact tracing is the techno-choice of reference to address the COVID-19 pandemic. Many of the current approaches have severe privacy and security issues and fail to offer a sustainable contact tracing infrastructure. We address these issues introducing an innovative, privacy-preserving, sustainable, and experimentally tested architecture that leverages batteryless BLE beacons.
In the current COVID-19 pandemic, manual contact tracing has been proven very helpful to reach close contacts of infected users and slow down virus spreading. To improve its scalability, a number of automated contact tracing (ACT) solutions have proposed and some of them have been deployed. Despite the dedicated efforts, security and privacy issues of these solutions are still open and under intensive debate. In this paper, we examine the ACT concept from a broader perspective, by focusing on not only security and privacy issues but also functional issues such as interface, usability and cover…
Google and Apple have jointly provided an API for exposure notification in order to implement decentralized contract tracing apps using Bluetooth Low Energy, the so-called "Google/Apple Proposal", which we abbreviate by "GAP". We demonstrate that in real-world scenarios the current GAP design is vulnerable to (i) profiling and possibly de-anonymizing infected persons, and (ii) relay-based wormhole attacks that basically can generate fake contacts with the potential of affecting the accuracy of an app-based contact tracing system. For both types of attack, we have built tools that can easily be…
Governments, Healthcare, and Private Organizations in the global scale have been using digital tracking to keep COVID-19 outbreaks under control. Although this method could limit pandemic contagion, it raises significant concerns about user privacy. Known as ~"Contact Tracing Apps", these mobile applications are facilitated by Cellphone Service Providers (CSPs), who enable the spatial and temporal real-time user tracking. Accordingly, it might be speculated that CSPs collect information violating the privacy policies such as GDPR, CCPA, and others. To further clarify, we conducted an in-depth …
The coronavirus disease 2019 (COVID-19) pandemic has caused an unprecedented health crisis for the global. Digital contact tracing, as a transmission intervention measure, has shown its effectiveness on pandemic control. Despite intensive research on digital contact tracing, existing solutions can hardly meet users' requirements on privacy and convenience. In this paper, we propose BU-Trace, a novel permissionless mobile system for privacy-preserving intelligent contact tracing based on QR code and NFC technologies. First, a user study is conducted to investigate and quantify the user acceptan…
We present Tracer Tokens, a hardware token of privacy-preserving contact tracing utilizing Exposure Notification \cite{GAEN} protocol. Through subnetworks, we show that any disease spread by proximity can be traced such as seasonal flu, cold, regional strains of COVID-19, or Tuberculosis. Further, we show this protocol to notify $n^n$ users in parallel, providing a speed of information unmatched by current contact tracing methods.
Privacy by design will become a legal obligation in the European Community if the Data Protection Regulation eventually gets adopted. However, taking into account privacy requirements in the design of a system is a challenging task. We propose an approach based on the specification of privacy architectures and focus on a key aspect of privacy, data minimisation, and its tension with integrity requirements. We illustrate our formal framework through a smart metering case study.
Governments around the world have become increasingly frustrated with tech giants dictating public health policy. The software created by Apple and Google enables individuals to track their own potential exposure through collated exposure notifications. However, the same software prohibits location tracking, denying key information needed by public health officials for robust contract tracing. This information is needed to treat and isolate COVID-19 positive people, identify transmission hotspots, and protect against continued spread of infection. In this article, we present two simple ideas: …
Smartphone location-based methods have been proposed and implemented as an effective alternative to traditional labor intensive contact tracing methods. However, there are serious privacy and security concerns that may impede wide-spread adoption in many societies. Furthermore, these methods rely solely on proximity to patients, based on Bluetooth or GPS signal for example, ignoring lingering effects of virus, including COVID-19, present in the environment. This results in inaccurate risk assessment and incomplete contact tracing. A new system concept, called PrivyTRAC, preserves user privacy,…
Contact tracing has been proven an effective approach to control the virus spread in pandemics like COVID-19 pandemic. As an emerging powerful decentralized technique, blockchain has been explored to ensure data privacy and security in contact tracing processes. However, existing works are mostly high-level designs with no sufficient demonstration and treat blockchain as separate storage system assisting third-party central servers, ignoring the importance and capability of consensus mechanism and incentive mechanism. In this paper, we propose a light-weight and fully third-party free Blockcha…
Contact tracing is an important method to control the spread of an infectious disease such as COVID-19. However, existing contact tracing methods alone cannot provide sufficient coverage and do not successfully address privacy concerns of the participating entities. Current solutions do not utilize the huge volume of data stored in business databases and individual digital devices. This information is typically stored in data silos and cannot be used due to regulations in place. To successfully unlock the potential of contact tracing, we need to consider both data utilization from multiple sou…
The 2019 Coronavirus disease (COVID-19) pandemic, caused by a quick dissemination of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has had a deep impact worldwide, both in terms of the loss of human life and the economic and social disruption. The use of digital technologies has been seen as an important effort to combat the pandemic and one of such technologies is contact tracing applications. These applications were successfully employed to face other infectious diseases, thus they have been used during the current pandemic. However, the use of contact tracing poses sever…
Digital contact tracing is one of the actions useful, in combination with other measures, to manage an epidemic diffusion of an infection disease in an after-lock-down phase. This is a very timely issue, due to the pandemic of COVID-19 we are unfortunately living. Apps for contact tracing aim to detect proximity of users and to evaluate the related risk in terms of possible contagious. Existing approaches leverage Bluetooth or GPS, or their combination, even though the prevailing approach is Bluetooth-based and relies on a decentralized model requiring the mutual exchange of ephemeral identifi…
With the COVID-19 pandemic, quarantines took place across the globe. In the aim of stopping or slowing the progression of the COVID-19 contamination, many countries have deployed a contact tracing system to notify persons that be in contact with a COVID-positive person. The contact tracing system is implemented in a mobile application and leverages technologies such as Bluetooth to trace interactions between persons. This paper discusses different smart-phone applications based on contact tracing system from privacy point of view.
In the digital era, users share their personal data with service providers to obtain some utility, e.g., access to high-quality services. Yet, the induced information flows raise privacy and integrity concerns. Consequently, cautious users may want to protect their privacy by minimizing the amount of information they disclose to curious service providers. Service providers are interested in verifying the integrity of the users' data to improve their services and obtain useful knowledge for their business. In this work, we present a generic solution to the trade-off between privacy, integrity, …
Contact tracing is an important measure to counter the COVID-19 pandemic. In the early phase, many countries employed manual contact tracing to contain the rate of disease spread, however it has many issues. The manual approach is cumbersome, time consuming and also requires active participation of a large number of people to realize it. In order to overcome these drawbacks, digital contact tracing has been proposed that typically involves deploying a contact tracing application on people's mobile devices which can track their movements and close social interactions. While studies suggest that…
Privacy and security-related concerns are growing as machine learning reaches diverse application domains. The data holders want to train with private data while exploiting accelerators, such as GPUs, that are hosted in the cloud. However, Cloud systems are vulnerable to attackers that compromise the privacy of data and integrity of computations. This work presents DarKnight, a framework for large DNN training while protecting input privacy and computation integrity. DarKnight relies on cooperative execution between trusted execution environments (TEE) and accelerators, where the TEE provides …
TCS Research（塔塔咨询服务研究院）；MIT Media Lab（麻省理工学院媒体实验室）
Contact tracing is a very powerful method to implement and enforce social distancing to avoid spreading of infectious diseases. The traditional approach of contact tracing is time consuming, manpower intensive, dangerous and prone to error due to fatigue or lack of skill. Due to this there is an emergence of mobile based applications for contact tracing. These applications primarily utilize a combination of GPS based absolute location and Bluetooth based relative location remitted from user's smartphone to infer various insights. These applications have eased the task of contact tracing; howev…
The COVID-19 pandemic has posed a unique challenge for the world to find solutions, ranging from vaccines to ICT solutions to slow down the virus spreading. Due to the highly contagious nature of the virus, social distancing is one fundamental measure which has already adopted by many countries. At the technical level, this prioritises contact tracing solutions, which can alert the users who have been in close contact with the infected persons and meanwhile allow heath authorities to take proper actions. In this paper, we examine several existing privacy-aware contact tracing solutions and ana…
The infection rate of COVID-19 and lack of an approved vaccine has forced governments and health authorities to adopt lockdowns, increased testing, and contact tracing to reduce the spread of the virus. Digital contact tracing has become a supplement to the traditional manual contact tracing process. However, although there have been a number of digital contact tracing apps proposed and deployed, these have not been widely adopted owing to apprehensions surrounding privacy and security. In this paper, we propose a blockchain-based privacy-preserving contact tracing protocol, "Did I Meet You" (…
Contact tracing is being widely employed to combat the spread of COVID-19. Many apps have been developed that allow for tracing to be done automatically based off location and interaction data generated by users. There are concerns, however, regarding the privacy and security of users data when using these apps. These concerns are paramount for users who contract the virus, as they are generally required to release all their data. Motivated by the need to protect users privacy we propose two solutions to this problem. Our first solution builds on current "message based" methods and our second …
There is growing interest in technology-enabled contact tracing, the process of identifying potentially infected COVID-19 patients by notifying all recent contacts of an infected person. Governments, technology companies, and research groups alike recognize the potential for smartphones, IoT devices, and wearable technology to automatically track "close contacts" and identify prior contacts in the event of an individual's positive test. However, there is currently significant public discussion about the tensions between effective technology-based contact tracing and the privacy of individuals.…
Contact tracing is an essential tool for public health officials and local communities to fight the spread of novel diseases, such as for the COVID-19 pandemic. The Singaporean government just released a mobile phone app, TraceTogether, that is designed to assist health officials in tracking down exposures after an infected individual is identified. However, there are important privacy implications of the existence of such tracking apps. Here, we analyze some of those implications and discuss ways of ameliorating the privacy concerns without decreasing usefulness to public health. We hope in w…
With the wide application of cloud storage, cloud security has become a crucial concern. Related works have addressed security issues such as data confidentiality and integrity, which ensure that the remotely stored data are well maintained by the cloud. However, how to define zero-knowledge proof algorithms for stored data integrity check has not been formally defined and investigated. We believe that it is important that the cloud server is unable to reveal any useful information about the stored data. In this paper, we introduce a novel definition of data privacy for integrity checks, which…
There is growing use of technology-enabled contact tracing, the process of identifying potentially infected COVID-19 patients by notifying all recent contacts of an infected person. Governments, technology companies, and research groups alike have been working towards releasing smartphone apps, using IoT devices, and distributing wearable technology to automatically track "close contacts" and identify prior contacts in the event an individual tests positive. However, there has been significant public discussion about the tensions between effective technology-based contact tracing and the priva…
Privacy and security-related concerns are growing as machine learning reaches diverse application domains. The data holders want to train or infer with private data while exploiting accelerators, such as GPUs, that are hosted in the cloud. Cloud systems are vulnerable to attackers that compromise the privacy of data and integrity of computations. Tackling such a challenge requires unifying theoretical privacy algorithms with hardware security capabilities. This paper presents DarKnight, a framework for large DNN training while protecting input privacy and computation integrity. DarKnight relie…
The outbreak of COVID-19 pandemic has exposed an urgent need for effective contact tracing solutions through mobile phone applications to prevent the infection from spreading further. However, due to the nature of contact tracing, public concern on privacy issues has been a bottleneck to the existing solutions, which is significantly affecting the uptake of contact tracing applications across the globe. In this paper, we present a blockchain-enabled privacy-preserving contact tracing scheme: BeepTrace, where we propose to adopt blockchain bridging the user/patient and the authorized solvers to…
In Advanced Metering Infrastructure (AMI) networks, smart meters should send fine-grained power consumption readings to electric utilities to perform real-time monitoring and energy management. However, these readings can leak sensitive information about consumers' activities. Various privacy-preserving schemes for collecting fine-grained readings have been proposed for AMI networks. These schemes aggregate individual readings and send an aggregated reading to the utility, but they extensively use asymmetric-key cryptography which involves large computation/communication overhead. Furthermore,…
Digital contact tracing has been proposed to support the health authorities in fighting the current Covid-19 pandemic. In this paper we propose two centralised protocols for digital contact tracing that, contrary to the common hypothesis that this is an inherent risk, do not allow (retroactive) tracking of the location of a device over time. The first protocol does not rely on synchronised clocks. The second protocol does not require a handshake between two devices, at the expense of relying on real-time communication with a central server. We stress that digital contact tracing is a form of t…
Since the global spread of Covid-19 began to overwhelm the attempts of governments to conduct manual contact-tracing, there has been much interest in using the power of mobile phones to automate the contact-tracing process through the development of exposure notification applications. The rough idea is simple: use Bluetooth or other data-exchange technologies to record contacts between users, enable users to report positive diagnoses, and alert users who have been exposed to sick users. Of course, there are many privacy concerns associated with this idea. Much of the work in this area has been…
Governments and researchers around the world are implementing digital contact tracing solutions to stem the spread of infectious disease, namely COVID-19. Many of these solutions threaten individual rights and privacy. Our goal is to break past the false dichotomy of effective versus privacy-preserving contact tracing. We offer an alternative approach to assess and communicate users' risk of exposure to an infectious disease while preserving individual privacy. Our proposal uses recent GPS location histories, which are transformed and encrypted, and a private set intersection protocol to inter…
The recent SARS-CoV-2 pandemic gave rise to management approaches using mobile apps for contact tracing. The corresponding apps track individuals and their interactions, to facilitate alerting users of potential infections well before they become infectious themselves. Naive implementation obviously jeopardizes the privacy of health conditions, location, activities, and social interaction of its users. A number of protocol designs for colocation tracking have already been developed, most of which claim to function in a privacy preserving manner. However, despite claims such as "GDPR compliance…
Today's smartphones are equipped with a large number of powerful value-added sensors and features such as a low power Bluetooth sensor, powerful embedded sensors such as the digital compass, accelerometer, GPS sensors, Wi-Fi capabilities, microphone, humidity sensors, health tracking sensors, and a camera, etc. These value-added sensors have revolutionized the lives of the human being in many ways such, as tracking the health of the patients and movement of doctors, tracking employees movement in large manufacturing units, and monitoring the environment, etc. These embedded sensors could also …
Contact Tracing has been used to identify people who were in close proximity to those infected with SARS-Cov2 coronavirus. A number of digital contract tracing applications have been introduced to facilitate or complement physical contact tracing. However, there are a number of privacy issues in the implementation of contract tracing applications, which make people reluctant to install or update their infection status on these applications. In this concept paper, we present ideas from Graph Neural Networks and explainability, that could improve trust in these applications, and encourage adopti…
A plethora of contact tracing apps have been developed and deployed in several countries around the world in the battle against Covid-19. However, people are rightfully concerned about the security and privacy risks of such applications. To this end, the contribution of this work is twofold. First, we present an in-depth analysis of the security and privacy characteristics of the most prominent contact tracing protocols, under both passive and active adversaries. The results of our study indicate that all protocols are vulnerable to a variety of attacks, mainly due to the deterministic nature …
Pandemic and epidemic diseases such as CoVID-19, SARS-CoV2, and Ebola have spread to multiple countries and infected thousands of people. Such diseases spread mainly through person-to-person contacts. Health care authorities recommend contact tracing procedures to prevent the spread to a vast population. Although several mobile applications have been developed to trace contacts, they typically require collection of privacy-intrusive information such as GPS locations, and the logging of privacy-sensitive data on a third party server, or require additional infrastructure such as WiFi APs with kn…
The outbreak of viruses have necessitated contact tracing and infection tracking methods. Despite various efforts, there is currently no standard scheme for the tracing and tracking. Many nations of the world have therefore, developed their own ways where carriers of disease could be tracked and their contacts traced. These are generalized methods developed either in a distributed manner giving citizens control of their identity or in a centralised manner where a health authority gathers data on those who are carriers. This paper outlines some of the most significant approaches that have been …
Contact tracing is an essential tool in containing infectious diseases such as COVID-19. Many countries and research groups have launched or announced mobile apps to facilitate contact tracing by recording contacts between users with some privacy considerations. Most of the focus has been on using random tokens, which are exchanged during encounters and stored locally on users' phones. Prior systems allow users to search over released tokens in order to learn if they have recently been in the proximity of a user that has since been diagnosed with the disease. However, prior approaches do not p…
Wireless Contact tracing has emerged as an important tool for managing the COVID19 pandemic and relies on continuous broadcasting of a person's presence using Bluetooth Low Energy beacons. The limitation of current contact tracing systems in that a reception of a single beacon is sufficient to reveal the user identity, potentially exposing users to malicious trackers installed along the roads, passageways, and other infrastructure. In this paper, we propose a method based on Shamir secret sharing algorithm, which lets mobile nodes reveal their identity only after a certain predefined contact d…
Contact tracing apps have become one of the main approaches to control and slow down the spread of COVID-19 and ease up lockdown measures. While these apps can be very effective in stopping the transmission chain and saving lives, their adoption remains under the expected critical mass. The public debate about contact tracing apps emphasizes general privacy reservations and is conducted at an expert level, but lacks the user perspective related to actual designs. To address this gap, we explore user preferences for contact tracing apps using market research techniques, and specifically conjoin…
Johns Hopkins University（约翰斯·霍普金斯大学）；Microsoft Research（微软研究院）；University of Zurich（苏黎世大学）
A growing number of contact tracing apps are being developed to complement manual contact tracing. A key question is whether users will be willing to adopt these contact tracing apps. In this work, we survey over 4,500 Americans to evaluate (1) the effect of both accuracy and privacy concerns on reported willingness to install COVID19 contact tracing apps and (2) how different groups of users weight accuracy vs. privacy. Drawing on our findings from these first two research questions, we (3) quantitatively model how the amount of public health benefit (reduction in infection rate), amount of i…
The global health threat from COVID-19 has been controlled in a number of instances by large-scale testing and contact tracing efforts. We created this document to suggest three functionalities on how we might best harness computing technologies to supporting the goals of public health organizations in minimizing morbidity and mortality associated with the spread of COVID-19, while protecting the civil liberties of individuals. In particular, this work advocates for a third-party free approach to assisted mobile contact tracing, because such an approach mitigates the security and privacy risks…
