Malte Möser, Kyle Soska, Ethan Heilman, Kevin Lee · 11 authors
Abstract Monero is a privacy-centric cryptocurrency that allows users to obscure their transactions by including chaff coins, called “mixins,” along with the actual coins they spend. In this paper, we empirically evaluate two weaknesses in Monero’s mixin sampling strategy. First, about 62% of transaction inputs with one or more mixins are vulnerable to “chain-reaction” analysis - that is, the real input can be deduced by elimination. Second, Monero mixins are sampled in such a way that they can be easily distinguished from the real coins by their age distribution; in short, the real input is usually the “newest” input. We estimate that this heuristic can be used to guess the real input with 80% accuracy over all transactions with 1 or more mixins. Next, we turn to the Monero ecosystem and study the importance of mining pools and the former anonymous marketplace AlphaBay on the transaction volume. We find that after removing mining pool activity, there remains a large amount of potentially privacy-sensitive transactions that are affected by these weaknesses. We propose and evaluate two countermeasures that can improve the privacy of future transactions.
In the Big Data era, personal metadata may will become a new type of corporate asset, however there have already been a growing public concern about user's privacy mined from metadata. In this paper we address the problem of implementing the self-sovereignty of personal metadata on the existing OpenPDS/SafeAnswers framework according to the Windhover Principle. In order to do that, we propose a new framework, called BlocakChain-based Personal Data Store (BCPDS), to realize two basic properties: notary and autonomy. This framework, firstly introduces the BlockChain as a notary, into OpenPDS/SafeAnswers for secure storage of personal meta-data instead of the original database. Next, we present an AutoNomybased Access Control (ANAC) to improve the SafeAnswers module, where ANAC is a new mechanism that enforces access based on the relationship among all authorized users and metadata's owner. In addition, we also propose General Access Structure (GAS) and threshold secret sharing scheme in BlockChain as an implementation method for our BC-PDS framework.
Towards the vision of building artificial intelligence systems that can assist with our everyday life, we introduce a proof of concept for a social media privacy "cyborg" which can locally and privately monitor a person's published content and offer advice or warnings when their privacy is at stake. The idea of a cyborg can be more general, as a separate local entity with its own computational resources, that can automatically perform several online tasks on our behalf. For this demonstration, we assume an attacker that can successfully infer user attributes, solely based on what the user has published (topic-based inference). We focus on Social Media privacy and specifically on the issue of exposing sensitive user-attributes, like location, or race, through published content. We built a privacy cyborg that can monitor a user's posted topics and automatically warn them in real time when a sensitive attribute is at risk of being exposed.
The blockchain has fueled one of the most enthusiastic bursts of activity in applied cryptography in years, but outstanding problems in security and privacy research must be solved for blockchain technologies to go beyond the hype and reach their full potential. At the first IEEE Privacy and Security on the Blockchain Workshop (IEEE S&B), we presented peer-reviewed papers bringing together academia and industry to analyze problems ranging from deploying newer cryptographic primitives on Bitcoin to enabling usecases like privacy-preserving file storage. We overview not only the larger problems the workshop has set out to tackle, but also outstanding unsolved issues that will require further cooperation between academia and the blockchain community.
Lin Chen, Lei Xu, Nolan Shah, Nour Diallo · 7 authors
User privacy is an important issue in a blockchain based transaction system. Bitcoin, being one of the most widely used blockchain based transaction system, fails to provide enough protection on users' privacy. Many subsequent studies focus on establishing a system that hides the linkage between the identities (pseudonyms) of users and the transactions they carry out in order to provide a high level of anonymity. Examples include Zerocoin, Zerocash and so on. It thus becomes an interesting question whether such new transaction systems do provide enough protection on users' privacy. In this paper, we propose a novel and effective approach for de-anonymizing these transaction systems by leveraging information in the system that is not directly related, including the number of transactions made by each identity and time stamp of sending and receiving. Combining probability studies with optimization tools, we establish a model which allows us to determine, among all possible ways of linking between transactions and identities, the one that is most likely to be true. Subsequent transaction graph analysis could then be carried out, leading to the de-anonymization of the system. To solve the model, we provide exact algorithms based on mixed integer linear programming. Our research also establishes interesting relationships between the de-anonymization problem and other problems studied in the literature of theoretical computer science, e.g., the graph matching problem and scheduling problem.
Bitcoin is a popular alternative to fiat money, widely used for its perceived anonymity properties. However, recent attacks on Bitcoin's peer-to-peer (P2P) network demonstrated that its gossip-based flooding protocols, which are used to ensure global network consistency, may enable user deanonymization---the linkage of a user's IP address with her pseudonym in the Bitcoin network. In 2015, the Bitcoin community responded to these attacks by changing the network's flooding mechanism to a different protocol, known as diffusion. However, no systematic justification was provided for the change, and it is unclear if diffusion actually improves the system's anonymity. In this paper, we model the Bitcoin networking stack and analyze its anonymity properties, both pre- and post-2015. In doing so, we consider new adversarial models and spreading mechanisms that have not been previously studied in the source-finding literature. We theoretically prove that Bitcoin's networking protocols (both pre- and post-2015) offer poor anonymity properties on networks with a regular-tree topology. We validate this claim in simulation on a 2015 snapshot of the real Bitcoin P2P network topology.
Aafaf Ouaddah, Anas Abou Elkalam, Abdellah Ait Ouahman
In this paper, we examine the possibility of using blockchain technology, mainly the second-generation of blockchain and smart contract, to create a new version of our decentralized pseudonymous & privacy preserving authorization management framework. Our framework relies on pseudonymous digital identity to ensure unlinkability, Smart contract to express access control policies and Blockchain technology to manage access control enforcement.
This paper presents Prio, a privacy-preserving system for the collection of aggregate statistics. Each Prio client holds a private data value (e.g., its current location), and a small set of servers compute statistical functions over the values of all clients (e.g., the most popular location). As long as at least one server is honest, the Prio servers learn nearly nothing about the clients' private data, except what they can infer from the aggregate statistics that the system computes. To protect functionality in the face of faulty or malicious clients, Prio uses secret-shared non-interactive proofs (SNIPs), a new cryptographic technique that yields a hundred-fold performance improvement over conventional zero-knowledge approaches. Prio extends classic private aggregation techniques to enable the collection of a large class of useful statistics. For example, Prio can perform a least-squares regression on high-dimensional client-provided data without ever seeing the data in the clear.
The latest Eurobarometer published in December 2016, reflecting the perceptions of the European citizens on privacy and security in telecommunications shows that, although people are not always informed on the privacy regulations or the implications of privacy breaches, they demand specific privacy protection. In particular, citizens want their data, their communications and the data that they give or outsource to online services to be well protected and not shared with unwanted parties. The demands of the public can be partly covered by the application of the privacy-by-design principle and the use of Privacy Enhancing Techniques (PETs) in commercial applications.
The privacy-by-design principle requires application designers to gather only the personal data that are essential to the correct operation of their applications. That is, applications following this principle should only ask the users to input those personal data that the specific application explicitly needs. Most applications in the market (and especially smartphone applications) clearly disregard this principle ---a look at the permissions they request is conclusive---: they collect contextual information too, even if it is not needed. The privacy policies of major service providers explain that all data may be used for commercial purposes.
Although major service providers collect more data than strictly necessary, the privacy-by-design principle demands that users be empowered with the decision about when to grant access to their data, when to modify them and when to delete them. While this is more or less being taken into account by service providers, sometimes the procedures to modify or delete personal data are not transparent enough or too cumbersome.
Privacy Enhancing Techniques (PET) are cryptographic and non-cryptographic tools that, when used appropriately, minimize the amount of personal data being handled by applications, and therefore help developers to more easily comply with regulations on personal data processing. Therefore, research on privacy enhancing techniques and on the practical deployment of the privacy-by-design principle is backed by the demands of the general population.
In this work we aim at demonstrating that, if appropriate techniques are used, privacy does not necessarily work against security and/or utility. We focus on three specific application cases described below:
- Group discounts are offered by vendors and public authorities to encourage a more sustainable (or profitable) way to access their services or use public resources. An example of this are high-occupancy vehicle (HOV) tolls in highways, which offer discounts for vehicles carrying more than a given number of passengers (2 or more, 3 or more, etc). There are several ways to ascertain the number of members of a group: employees at access points that count them, cameras that take photos and analyze them in toll booths, or registration procedures that require the names of all members of groups, among others.
We argue that automated mechanisms, such as cameras and registration procedures, take more information from the participants that is actually needed (thus violating the privacy-by-design principle), and that the only really necessary information is the size of the groups.
- Loyalty programs are marketing efforts implemented by vendors, especially retailers, that are aimed at establishing a lasting relationship with consumers. In a loyalty program, the vendor pursues two main goals: i) to encourage the consumer to make more purchases in the future (returning customer); ii) to allow the vendor to profile the consumer in view of conducting market research and segmentation (profiled customer). In order to lure consumers into a loyalty program, the vendor offers them rewards, typically loyalty points that consumers can later exchange for discounts, gifts or other benefits offered by the vendor.
Normally, enrollment to loyalty programs involves some kind of registration procedure, in which customers fill out a form with their personal information and are granted a loyalty card, be it a physical card (magnetic stripe or smartcard) or a smartphone application. Although loyalty programs have become widespread, they are experiencing a loss of active participants and they have been criticized by business experts and consumer associations. Criticism is mainly due to privacy issues, because it is not always clear whether the benefits offered by vendors in their loyalty programs are worth the loss of consumer privacy caused by profiling.
- Implicit authentication refers to a software system authenticating individuals based on the way they interact with their device, i.e. their behavior. In this context, the user's behavior can be determined by collecting a variety of features, such as keystroke patterns, browser history and configuration, IP addresses, location, visible antennas, etc. Implicit authentication can be viewed as a complement of the usual explicit authentication based on identifiers and credentials.
Note that a common trait in these three application cases is that users need to prove something about themselves or their context without revealing more than what is strictly necessary. We believe these cases can be used as an example for other applications in which the goal is similar.
The main contributions of this thesis are: 1. A group size accreditation method that preserves anonymity of the members of the groups. The anonymity provided by the scheme is congurable.
The method rests on two building blocks: (a) A new parameterized key management scheme for identity-based signatures that allows setting the anonymity level of users by providing them with multiple keys that are shared by many other users, but that are extracted from a unique identity.
(b) A novel IBDT signature scheme based on asymmetric bilinear pairings, that combines the properties of identity-based and threshold signature schemes. Signatures produced with this scheme reveal only the public keys of the group members, which are called identities, and the size of the signing group. The signature scheme is efficient, and the sizes of the signatures are constant.
2. A privacy-preserving loyalty program protocol suite, whereby vendors can issue and verify loyalty points, and customers can maintain their anonymity and con gure the level of generalization for their purchase receipts before submitting them for additional loyalty points. This allows vendors to still carry out client profiling in a privacy-aware way. This protocol suite combines the following techniques: (a) A new construction for anonymous (untransferable) tokens with controlled linkability based on partially blind signatures and zero-knowledge proofs. The construction allows issuing and verifying tokens, while the verifier cannot link tokens to a specific user or between concrete executions of the issuance and verification procedures, unless such a linkage is authorized by the user. Moreover, if a hardware based keystore is available, the tokens can be made untransferable, so that only users who originally received the tokens can submit them.
(b) Generalization techniques to select the level of anonymization of purchase receipts.
3. A mechanism to compute the distance between user profiles (expressed as feature sets of different data types) based on the size of the intersectionof the feature sets.
4. A privacy-preserving implicit authentication mechanism using the homomorphic properties of the Paillier cryptosystem, that protects the privacy of the sensitive data in the user's profile and ensures that the server does not learn anything about the user's behavior.
5. A second privacy-preserving implicit authentication with similar functionalities and higher speed compared to the previous one, based on the intersection of Bloom filters. While this mechanism provides slightly less protection than the previous one, its substantially better performance makes it ideal for implementation in existing authentication suites.
In recent years, volunteer service in China has made an unprecedented development, but the credibility and traceability of volunteer service time management are confronted with serious challenges. Since traditional time record systems cannot protect the related data security of the volunteers. In this paper, we study the volunteer time record system based on the blockchain technology which is the core technology of bitcoin, unlike bitcoin transaction in our system are not strictly financial - they are used to carry instructions, such as storing, querying, and sharing data. Volunteer service time and activity information recorded by sending the chain transaction. Effective time recognition is guaranteed by smart contract. It can ensure that the volunteer's time is independent of improper human interference, and the fairness of volunteer service, realizes the traceability and transparency of the entire time record process. Then we describe a specific case and use the system we proposed storing the volunteer service time, volunteers' service time can be certified effectively.
We propose a new secure online storage scheme based on an open P2P network without a central server. In the proposed scheme, attackers cannot detect target user data in the online storage because the user data is divided into some parts by the secret sharing, and they are distributed to P2P nodes via the anonymous communication. The proposed scheme can prevent the direct attack on the target user node because metadata for the reconstruction also hidden in the online storage, hence nothing remains in the user node. Even if the state of the P2P network varies over time between the storing and restoring operation, the proposed scheme ensures that the user can identify the target nodes which stored his metadata by utilizing the Blockchain technology with only memorable secure information for user authentication. Furthermore, a malicious node to attack on others can be detected and ruled out by the mutual monitoring among the nodes and the majority decision rule.
Ali Dorri, Salil S. Kanhere, Raja Jurdak, Praveen Gauravaram
Internet of Things (IoT) security and privacy remain a major challenge, mainly due to the massive scale and distributed nature of IoT networks. Blockchain-based approaches provide decentralized security and privacy, yet they involve significant energy, delay, and computational overhead that is not suitable for most resource-constrained IoT devices. In our previous work, we presented a lightweight instantiation of a BC particularly geared for use in IoT by eliminating the Proof of Work (POW) and the concept of coins. Our approach was exemplified in a smart home setting and consists of three main tiers namely: cloud storage, overlay, and smart home. In this paper we delve deeper and outline the various core components and functions of the smart home tier. Each smart home is equipped with an always online, high resource device, known as “miner” that is responsible for handling all communication within and external to the home. The miner also preserves a private and secure BC, used for controlling and auditing communications. We show that our proposed BC-based smart home framework is secure by thoroughly analysing its security with respect to the fundamental security goals of confidentiality, integrity, and availability. Finally, we present simulation results to highlight that the overheads (in terms of traffic, processing time and energy consumption) introduced by our approach are insignificant relative to its security and privacy gains.
Tyler Crain, Vincent Gramoli, Mikel Larrea, Michel Raynal
This paper introduces a deterministic Byzantine consensus algorithm that relies on a new weak coordinator. As opposed to previous algorithms that cannot terminate in the presence of a faulty or slow coordinator, our algorithm can terminate even when its coordinator is faulty, hence the name weak coordinator. The key idea is to allow processes to complete asynchronous rounds as soon as they receive a threshold of messages, instead of having to wait for a message from a coordinator that may be slow. The resulting algorithm assumes partial synchrony, is resilience optimal, time optimal and does not need signatures. Our presentation is didactic: we first present a simple safe binary Byzantine consensus algorithm, modify it to ensure termination, and finally present an optimized reduction from multivalue consensus to binary consensus that may terminate in 4 message delays. To evaluate our algorithm, we deployed it on 100 machines distributed in 5 datacenters across different continents and compared its performance against the randomized solution from Mostefaoui, Moumem and Raynal [PODC14] that terminates in O(1) rounds in expectation. Our algorithm always outperforms the latter even in the presence of Byzantine behaviors. Our algorithm has a subsecond average latency in most of our geo-distributed experiments, even when attacked by a well-engineered coalition of Byzantine processes.
Bitcoin and other cryptocurrencies have surged in popularity over the last decade. Although Bitcoin does not claim to provide anonymity for its users, it enjoys a public perception of being a `privacy-preserving' financial system. In reality, cryptocurrencies publish users' entire transaction histories in plaintext, albeit under a pseudonym; this is required for transaction validation. Therefore, if a user's pseudonym can be linked to their human identity, the privacy fallout can be significant. Recently, researchers have demonstrated deanonymization attacks that exploit weaknesses in the Bitcoin network's peer-to-peer (P2P) networking protocols. In particular, the P2P network currently forwards content in a structured way that allows observers to deanonymize users. In this work, we redesign the P2P network from first principles with the goal of providing strong, provable anonymity guarantees. We propose a simple networking policy called Dandelion, which achieves nearly-optimal anonymity guarantees at minimal cost to the network's utility. We also provide a practical implementation of Dandelion.
Mathieu Chanson, Alexander Bogner, Felix Wortmann, Elgar Fleisch
Giving people ownership of the data they produce becomes more and more important in times of ever-growing capabilities to collect and analyze data of individuals. In light of this challenge, we show how blockchain technology can enable privacy by presenting an odometer fraud prevention system. It records mileage and GPS data of cars and secures that on the blockchain, which strongly hinders odometer fraud. Our users own and control their data while at the same time data integrity is ensured. This facilitates the certification of that data. We discuss the advantages of this approach compared to current systems and also highlight limitations of our architecture and the use of blockchain technology.
In this paper a novel feedback controller and stability analysis of a blockchain implementation is developed by using a control engineering perspective. The controller output equals the difficulty adjustment in the mining process while the feedback variable is the average block time over a certain time period. The computational power (hash rate) of the miners is considered a disturbance in the model. The developed controller is tested against a simulation model with constant disturbance, step and ramp responses as well as with a high-frequency sinusoidal disturbance. Stability and a fast response is demonstrated in all these cases with a controller which adjusts it's output at every new block. Finally the performance of the controller is implemented and demonstrated on a testnet with a constant hash rate as well as on the mainnet of a public open source blockchain project.
Secure multiparty protocols are useful tools for parties wishing to jointly compute a function while keeping their input data secret. The millionaires’ problem is the first secure two-party computation problem, where the goal is to securely compare two private numbers without a trusted third-party. There have been several solutions to the problem, including Yao’s protocol [Yao, 1982] and Mix and Match [Jakobsson and Juels, 2000]. However, Yao’s Protocol is not secure in the malicious model and Mix and Match unnecessarily releases theoretically breakable encryptions of information about the data that is not needed for the comparison. In addition, neither protocol has any verification of the validity of the inputs before they are used. In this thesis, we introduce Variance, a privacy-preserving two-party protocol for solving the Yao’s millionaires’ problem in a Bitcoin setting, in which each party controls several Bitcoin accounts (public Bitcoin addresses) and they want to find out who owns more bitcoins without revealing (1) how many accounts they own and the balance of each account, (2) the addresses associated with their accounts, and (3) their total wealth of bitcoins while assuring the other party that they are not claiming more bitcoin than they possess. We utilize commitments, encryptions, zero knowledge proofs, and homomorphisms as the major computational tools to provide a solution to the problem, and subsequently prove that the solution is secure against active adversaries in the malicious model.
Low-power Ad Hoc systems are the most challenging aspect for secured Ad Hoc systems. The resource constrained devices were easily tampered due to the limited operated environment. Over the past decade, the usage rate of Ad Hoc systems are rapidly increased in modern communication systems. However, the security is still a research factor for Lowpower Ad Hoc systems. Offering Security and Anonymity is an important research issue in Low-power Mobile Ad Hoc Networks (LPMANET). Various anonymous routing protocols presented to maintain anonymity in adverse environment, these protocols proven significant results in Ad Hoc systems but failure to improved the anonymity efficiency in Low-power Ad hoc networks. In this paper, a Lightweight Energy Efficient Anonymous Routing (LEEAR) protocol is proposed to offer energy efficient anonymity and security in an adverse environment by combining modified zero knowledge proof, bloom filter and cryptography techniques. We designed the LEEAR protocol to determine the efficiency in-terms security and energy against routing level and traffic level attacks. We simulated the experiment in NS2 simulator the determine the results and ensure importance of the proposed LEEAR protocol in accomplishing energy efficiency and anonymity.
Within the phenomenon known as the Internet of Things (IoT), an enormous growth is taking place. IoT systems exist in different ways, ranging from industrial applications to user focused systems. A specific subset of a user-focused IoT system is found as Smart Home environments. At Smart Homes, themultiple Smart Objects or Smart Devices are working together, frequently based on sensor input, to increase the comfort and user experience of the home inhabitant(s) and guest(s). Smart Objects can have automated tasks, home security enabling functions or efficiency improving functionality. Apart from great applications of Smart Home devices, threats from a cyber security perspective are present: cyber risks arise due to a variety of threats on such IoT systems. We show that in the development of new Smart Home products or systems, vendors fail to meet requirements for security and privacy are not met. Comparing the current state of the market, the four most used Smart Home ecosystems (Samsung Smartthings, Apple Homekit, Amazon Echo and IFTTT) are surveyed based on three key focus areas: 1. The regulatory compliance of the systems according to the upcoming General Data Protection Regulation (GDPR). 2. The commercial threats due to data profiling. 3. The risk of data leaks due to insufficient security. This analysis results in four key observations: 1. Security- and Privacy-By-Design is usually not in place due to the fact that the focus lies on launching a product as soon as possible, e.g. due to market competition; 2. Vendors process (meta)data on the vendors locations resulting in data profiling, which can compromise user privacy; 3. Smart Home ecosystems are not ready for the GDPR; 4. A trade off between privacy, security and utility usually results to the detriment of the first two and favors the latter. We propose a new design for a Smart Home ecosystem. In this design, the focus lies at the privacy of the end-user. We design a network for device-fitting encrypted communication between Smart Devices and User Devices and the Privacy Enforcing Arbiter (or Peter). Peter functions like a hub in the network, managing among others all traffic, user privileges and key distribution. With Peter, the centralized cloud party (vendor) for data storage and data analysis is replaced with a decentralized personal storage and computation entity at home. With our network design, we facilitate the use of IoT devices in home in a privacy-friendly way. Within the network, devices are authenticated using PhysicallyUnclonable Function technology and users are authenticated with a Zero Knowledge Proof. We analyze the privacy and security of our proposed network, based on a series of possible cyber attacks and the upcoming GDPR. Furthermore, we analyze the computational complexity and scalability of the network, based on market conform device power.