An Approach to Guide Users Towards Less Revealing Internet Browsers

When browsing the Internet, HTTP headers enable both clients and servers send extra data in their requests or responses such as the User-Agent string. This string contains information related to the sender’s device, browser, and operating system. Previous research has shown that there are numerous privacy and security risks result from exposing sensitive information in the User-Agent string. For example, it enables device and browser fingerprinting and user tracking and identification. Our large analysis of thousands of User-Agent strings shows that browsers differ tremendously in the amount of information they include in their User-Agent strings. As such, our work aims at guiding users towards using less exposing browsers. In doing so, we propose to assign an exposure score to browsers based on the information they expose and vulnerability records. Thus, our contribution in this work is as follows: first, provide a full implementation that is ready to be deployed and used by users. Second, conduct a user study to identify the effectiveness and limitations of our proposed approach. Our implementation is based on using more than 52 thousand unique browsers. Our performance and validation analysis show that our solution is accurate and efficient. The source code and data set are publicly available and the solution has been deployed

Critical Perspectives on Provable Security: Fifteen Years of Another Look Papers

We give an overview of our critiques of “proofs” of security and a guide to our papers on the subject that have appeared over the past decade and a half. We also provide numerous additional examples and a few updates and errata

A publicly verifiable quantum signature scheme based on asymmetric quantum cryptography

In 2018, Shi et al. \u27s showed that Kaushik et al.\u27s quantum signature scheme is defective. It suffers from the forgery attack. They further proposed an improvement, trying to avoid the attack. However, after examining we found their improved quantum signature is deniable, because the verifier can impersonate the signer to sign a message. After that, when a dispute occurs, he can argue that the signature was not signed by him. It was from the signer. To overcome the drawback, in this paper, we raise an improvement to make it publicly verifiable and hence more suitable to be applied in real life. After cryptanalysis, we confirm that our improvement not only resist the forgery attack but also is undeniable

CONSTRUCTION OF EFFICIENT AUTHENTICATION SCHEMES USING TRAPDOOR HASH FUNCTIONS

In large-scale distributed systems, where adversarial attacks can have widespread impact, authentication provides protection from threats involving impersonation of entities and tampering of data. Practical solutions to authentication problems in distributed systems must meet specific constraints of the target system, and provide a reasonable balance between security and cost. The goal of this dissertation is to address the problem of building practical and efficient authentication mechanisms to secure distributed applications. This dissertation presents techniques to construct efficient digital signature schemes using trapdoor hash functions for various distributed applications. Trapdoor hash functions are collision-resistant hash functions associated with a secret trapdoor key that allows the key-holder to find collisions between hashes of different messages. The main contributions of this dissertation are as follows: 1. A common problem with conventional trapdoor hash functions is that revealing a collision producing message pair allows an entity to compute additional collisions without knowledge of the trapdoor key. To overcome this problem, we design an efficient trapdoor hash function that prevents all entities except the trapdoor key-holder from computing collisions regardless of whether collision producing message pairs are revealed by the key-holder. 2. We design a technique to construct efficient proxy signatures using trapdoor hash functions to authenticate and authorize agents acting on behalf of users in agent-based computing systems. Our technique provides agent authentication, assurance of agreement between delegator and agent, security without relying on secure communication channels and control over an agent’s capabilities. 3. We develop a trapdoor hash-based signature amortization technique for authenticating real-time, delay-sensitive streams. Our technique provides independent verifiability of blocks comprising a stream, minimizes sender-side and receiver-side delays, minimizes communication overhead, and avoids transmission of redundant information. 4. We demonstrate the practical efficacy of our trapdoor hash-based techniques for signature amortization and proxy signature construction by presenting discrete log-based instantiations of the generic techniques that are efficient to compute, and produce short signatures. Our detailed performance analyses demonstrate that the proposed schemes outperform existing schemes in computation cost and signature size. We also present proofs for security of the proposed discrete-log based instantiations against forgery attacks under the discrete-log assumption

Security and Privacy Preservation in Mobile Crowdsensing

Mobile crowdsensing (MCS) is a compelling paradigm that enables a crowd of individuals to cooperatively collect and share data to measure phenomena or record events of common interest using their mobile devices. Pairing with inherent mobility and intelligence, mobile users can collect, produce and upload large amounts of data to service providers based on crowdsensing tasks released by customers, ranging from general information, such as temperature, air quality and traffic condition, to more specialized data, such as recommended places, health condition and voting intentions. Compared with traditional sensor networks, MCS can support large-scale sensing applications, improve sensing data trustworthiness and reduce the cost on deploying expensive hardware or software to acquire high-quality data. Despite the appealing benefits, however, MCS is also confronted with a variety of security and privacy threats, which would impede its rapid development. Due to their own incentives and vulnerabilities of service providers, data security and user privacy are being put at risk. The corruption of sensing reports may directly affect crowdsensing results, and thereby mislead customers to make irrational decisions. Moreover, the content of crowdsensing tasks may expose the intention of customers, and the sensing reports might inadvertently reveal sensitive information about mobile users. Data encryption and anonymization techniques can provide straightforward solutions for data security and user privacy, but there are several issues, which are of significantly importance to make MCS practical. First of all, to enhance data trustworthiness, service providers need to recruit mobile users based on their personal information, such as preferences, mobility pattern and reputation, resulting in the privacy exposure to service providers. Secondly, it is inevitable to have replicate data in crowdsensing reports, which may possess large communication bandwidth, but traditional data encryption makes replicate data detection and deletion challenging. Thirdly, crowdsensed data analysis is essential to generate crowdsensing reports in MCS, but the correctness of crowdsensing results in the absence of malicious mobile users and service providers become a huge concern for customers. Finally yet importantly, even if user privacy is preserved during task allocation and data collection, it may still be exposed during reward distribution. It further discourage mobile users from task participation. In this thesis, we explore the approaches to resolve these challenges in MCS. Based on the architecture of MCS, we conduct our research with the focus on security and privacy protection without sacrificing data quality and users' enthusiasm. Specifically, the main contributions are, i) to enable privacy preservation and task allocation, we propose SPOON, a strong privacy-preserving mobile crowdsensing scheme supporting accurate task allocation. In SPOON, the service provider recruits mobile users based on their locations, and selects proper sensing reports according to their trust levels without invading user privacy. By utilizing the blind signature, sensing tasks are protected and reports are anonymized. In addition, a privacy-preserving credit management mechanism is introduced to achieve decentralized trust management and secure credit proof for mobile users; ii) to improve communication efficiency while guaranteeing data confidentiality, we propose a fog-assisted secure data deduplication scheme, in which a BLS-oblivious pseudo-random function is developed to enable fog nodes to detect and delete replicate data in sensing reports without exposing the content of reports. Considering the privacy leakages of mobile users who report the same data, the blind signature is utilized to hide users' identities, and chameleon hash function is leveraged to achieve contribution claim and reward retrieval for anonymous greedy mobile users; iii) to achieve data statistics with privacy preservation, we propose a privacy-preserving data statistics scheme to achieve end-to-end security and integrity protection, while enabling the aggregation of the collected data from multiple sources. The correctness verification is supported to prevent the corruption of the aggregate results during data transmission based on the homomorphic authenticator and the proxy re-signature. A privacy-preserving verifiable linear statistics mechanism is developed to realize the linear aggregation of multiple crowdsensed data from a same device and the verification on the correctness of aggregate results; and iv) to encourage mobile users to participating in sensing tasks, we propose a dual-anonymous reward distribution scheme to offer the incentive for mobile users and privacy protection for both customers and mobile users in MCS. Based on the dividable cash, a new reward sharing incentive mechanism is developed to encourage mobile users to participating in sensing tasks, and the randomization technique is leveraged to protect the identities of customers and mobile users during reward claim, distribution and deposit

Cryptography with anonymity in mind

Advances in information technologies gave a rise to powerful ubiquitous com- puting devices, and digital networks have enabled new ways of fast communication, which immediately found tons of applications and resulted in large amounts of data being transmitted. For decades, cryptographic schemes and privacy-preserving protocols have been studied and researched in order to offer end users privacy of their data and implement useful functionalities at the same time, often trading security properties for cryptographic assumptions and efficiency. In this plethora of cryptographic constructions, anonymity properties play a special role, as they are important in many real-life scenarios. However, many useful cryptographic primitives lack anonymity properties or imply prohibitive costs to achieve them. In this thesis, we expand the territory of cryptographic primitives with anonymity in mind. First, we define Anonymous RAM, a generalization of a single- user Oblivious RAM to multiple mistrusted users, and present two constructions thereof with different trade-offs between assumptions and efficiency. Second, we define an encryption scheme that allows to establish chains of ciphertexts anony- mously and verify their integrity. Furthermore, the aggregatable version of the scheme allows to build a Parallel Anonymous RAM, which enhances Anonymous RAM by supporting concurrent users. Third, we show our technique for construct- ing efficient non-interactive zero-knowledge proofs for statements that consist of both algebraic and arithmetic statements. Finally, we show our framework for constructing efficient single secret leader election protocols, which have been recently identified as an important component in proof-of-stake cryptocurrencies.Fortschritte in der Informationstechnik haben leistungsstarke allgegenwärtige Rechner hervorgerufen, während uns digitale Netzwerke neue Wege für die schnelle Kommunikation ermöglicht haben. Durch die Vielzahl von Anwendungen führte dies zur Übertragung von riesigen Datenvolumen. Seit Jahrzehnten wurden bereits verschiedene kryptographische Verfahren und Technologien zum Datenschutz erforscht und analysiert. Das Ziel ist die Privatsphäre der Benutzer zu schützen und gleichzeitig nützliche Funktionalität anzubieten, was oft mit einem Kompromiss zwischen Sicherheitseigenschaften, kryptographischen Annahmen und Effizienz verbunden ist. In einer Fülle von kryptographischen Konstruktionen spielen Anonymitätseigenschaften eine besondere Rolle, da sie in vielen realistischen Szenarien sehr wichtig sind. Allerdings fehlen vielen kryptographischen Primitive Anonymitätseigenschaften oder sie stehen im Zusammenhang mit erheblichen Kosten. In dieser Dissertation erweitern wir den Bereich von kryptographischen Prim- itiven mit einem Fokus auf Anonymität. Erstens definieren wir Anonymous RAM, eine Verallgemeinerung von Einzelbenutzer-Oblivious RAM für mehrere misstraute Benutzer, und stellen dazu zwei Konstruktionen mit verschiedenen Kompromissen zwischen Annahmen und Effizienz vor. Zweitens definieren wir ein Verschlüsselungsverfahren, das es erlaubt anonym eine Verbindung zwischen Geheimtexten herzustellen und deren Integrität zu überprüfen. Darüber hinaus bietet die aggregierbare Variante von diesem Verfahren an, Parallel Anonymous RAM zu bauen. Dieses verbessert Anonymous RAM, indem es mehrere Benutzer in einer parallelen Ausführung unterstützen kann. Drittens zeigen wir eine Meth- ode für das Konstruieren effizienter Zero-Knowledge-Protokolle, die gleichzeitig aus algebraischen und arithmetischen Teilen bestehen. Zuletzt zeigen wir ein Framework für das Konstruieren effizienter Single-Leader-Election-Protokolle, was kürzlich als ein wichtiger Bestandteil in den Proof-of-Stake Kryptowährungen erkannt worden ist

Design and Analysis of Opaque Signatures

Digital signatures were introduced to guarantee the authenticity and integrity of the underlying messages. A digital signature scheme comprises the key generation, the signature, and the verification algorithms. The key generation algorithm creates the signing and the verifying keys, called also the signer’s private and public keys respectively. The signature algorithm, which is run by the signer, produces a signature on the input message. Finally, the verification algorithm, run by anyone who knows the signer’s public key, checks whether a purported signature on some message is valid or not. The last property, namely the universal verification of digital signatures is undesirable in situations where the signed data is commercially or personally sensitive. Therefore, mechanisms which share most properties with digital signatures except for the universal verification were invented to respond to the aforementioned need; we call such mechanisms “opaque signatures”. In this thesis, we study the signatures where the verification cannot be achieved without the cooperation of a specific entity, namely the signer in case of undeniable signatures, or the confirmer in case of confirmer signatures; we make three main contributions. We first study the relationship between two security properties important for public key encryption, namely data privacy and key privacy. Our study is motivated by the fact that opaque signatures involve always an encryption layer that ensures their opacity. The properties required for this encryption vary according to whether we want to protect the identity (i.e. the key) of the signer or hide the validity of the signature. Therefore, it would be convenient to use existing work about the encryption scheme in order to derive one notion from the other. Next, we delve into the generic constructions of confirmer signatures from basic cryptographic primitives, e.g. digital signatures, encryption, or commitment schemes. In fact, generic constructions give easy-to-understand and easy-to-prove schemes, however, this convenience is often achieved at the expense of efficiency. In this contribution, which constitutes the core of this thesis, we first analyze the already existing constructions; our study concludes that the popular generic constructions of confirmer signatures necessitate strong security assumptions on the building blocks, which impacts negatively the efficiency of the resulting signatures. Next, we show that a small change in these constructionsmakes these assumptions drop drastically, allowing as a result constructions with instantiations that compete with the dedicated realizations of these signatures. Finally, we revisit two early undeniable signatures which were proposed with a conjectural security. We disprove the claimed security of the first scheme, and we provide a fix to it in order to achieve strong security properties. Next, we upgrade the second scheme so that it supports a iii desirable feature, and we provide a formal security treatment of the new scheme: we prove that it is secure assuming new reasonable assumptions on the underlying constituents

A patient agent controlled customized blockchain based framework for internet of things

Although Blockchain implementations have emerged as revolutionary technologies for various industrial applications including cryptocurrencies, they have not been widely deployed to store data streaming from sensors to remote servers in architectures known as Internet of Things. New Blockchain for the Internet of Things models promise secure solutions for eHealth, smart cities, and other applications. These models pave the way for continuous monitoring of patient’s physiological signs with wearable sensors to augment traditional medical practice without recourse to storing data with a trusted authority. However, existing Blockchain algorithms cannot accommodate the huge volumes, security, and privacy requirements of health data. In this thesis, our first contribution is an End-to-End secure eHealth architecture that introduces an intelligent Patient Centric Agent. The Patient Centric Agent executing on dedicated hardware manages the storage and access of streams of sensors generated health data, into a customized Blockchain and other less secure repositories. As IoT devices cannot host Blockchain technology due to their limited memory, power, and computational resources, the Patient Centric Agent coordinates and communicates with a private customized Blockchain on behalf of the wearable devices. While the adoption of a Patient Centric Agent offers solutions for addressing continuous monitoring of patients’ health, dealing with storage, data privacy and network security issues, the architecture is vulnerable to Denial of Services(DoS) and single point of failure attacks. To address this issue, we advance a second contribution; a decentralised eHealth system in which the Patient Centric Agent is replicated at three levels: Sensing Layer, NEAR Processing Layer and FAR Processing Layer. The functionalities of the Patient Centric Agent are customized to manage the tasks of the three levels. Simulations confirm protection of the architecture against DoS attacks. Few patients require all their health data to be stored in Blockchain repositories but instead need to select an appropriate storage medium for each chunk of data by matching their personal needs and preferences with features of candidate storage mediums. Motivated by this context, we advance third contribution; a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The mapping between health data features and characteristics of each repository is learned using machine learning. The Blockchain’s capacity to make transactions and store records without central oversight enables its application for IoT networks outside health such as underwater IoT networks where the unattended nature of the nodes threatens their security and privacy. However, underwater IoT differs from ground IoT as acoustics signals are the communication media leading to high propagation delays, high error rates exacerbated by turbulent water currents. Our fourth contribution is a customized Blockchain leveraged framework with the model of Patient-Centric Agent renamed as Smart Agent for securely monitoring underwater IoT. Finally, the smart Agent has been investigated in developing an IoT smart home or cities monitoring framework. The key algorithms underpinning to each contribution have been implemented and analysed using simulators.Doctor of Philosoph