Signer-Anonymous Designated-Verifier Redactable Signatures for Cloud-Based Data Sharing

Redactable signature schemes allow to black out predefined parts of a signed message without affecting the validity of the signature, and are therefore an important building block in privacy-enhancing cryptography. However, a second look shows, that for many practical applications, they cannot be used in their vanilla form. On the one hand, already the identity of the signer may often reveal sensitive information to the receiver of a redacted message; on the other hand, if data leaks or is sold, everyone getting hold of (redacted versions of) a signed message will be convinced of its authenticity. We overcome these issues by providing a definitional framework and practically efficient instantiations of so called signer-anonymous designated-verifier redactable signatures (AD-RS). As a byproduct we also obtain the first group redactable signatures, which may be of independent interest. AD-RS are motivated by a real world use-case in the field of health care and complement existing health information sharing platforms with additional important privacy features. Moreover, our results are not limited to the proposed application, but can also be directly applied to various other contexts such as notary authorities or e-government services

Research Philosophy of Modern Cryptography

Proposing novel cryptography schemes (e.g., encryption, signatures, and protocols) is one of the main research goals in modern cryptography. In this paper, based on more than 800 research papers since 1976 that we have surveyed, we introduce the research philosophy of cryptography behind these papers. We use ``benefits and ``novelty as the keywords to introduce the research philosophy of proposing new schemes, assuming that there is already one scheme proposed for a cryptography notion. Next, we introduce how benefits were explored in the literature and we have categorized the methodology into 3 ways for benefits, 6 types of benefits, and 17 benefit areas. As examples, we introduce 40 research strategies within these benefit areas that were invented in the literature. The introduced research strategies have covered most cryptography schemes published in top-tier cryptography conferences

Fully Invisible Protean Signatures Schemes

Protean Signatures (PS), recently introduced by Krenn et al. (CANS \u2718), allow a semi-trusted third party, named the sanitizer, to modify a signed message in a controlled way. The sanitizer can edit signer-chosen parts to arbitrary bitstrings, while the sanitizer can also redact admissible parts, which are also chosen by the signer. Thus, PSs generalize both redactable signature (RSS) and sanitizable signature (SSS) into a single notion. However, the current definition of invisibility does not prohibit that an outsider can decide which parts of a message are redactable - only which parts can be edited are hidden. This negatively impacts on the privacy guarantees provided by the state-of-the-art definition. We extend PSs to be fully invisible. This strengthened notion guarantees that an outsider can neither decide which parts of a message can be edited nor which parts can be redacted. To achieve our goal, we introduce the new notions of Invisible RSSs and Invisible Non-Accountable SSSs (SSS\u27), along with a consolidated framework for aggregate signatures. Using those building blocks, our resulting construction is significantly more efficient than the original scheme by Krenn et al., which we demonstrate in a prototypical implementation

Locally Verifiable Signature and Key Aggregation

Aggregate signatures (Boneh, Gentry, Lynn, Shacham, Eurocrypt 2003) enable compressing a set of $N$ signatures on $N$ different messages into a short aggregate signature. This reduces the space complexity of storing the signatures from linear in $N$ to a fixed constant (that depends only on the security parameter). However, verifying the aggregate signature requires access to all $N$ messages, resulting in the complexity of verification being at least $\Omega(N)$. In this work, we introduce the notion of locally verifiable aggregate signatures that enable efficient verification: given a short aggregate signature $\sigma$ (corresponding to a set $\mathcal{M}$ of $N$ messages), the verifier can check whether a particular message $m$ is in the set, in time independent of $N$. Verification does not require knowledge of the entire set $\mathcal{M}$. We demonstrate many natural applications of locally verifiable aggregate signature schemes: in the context of certificate transparency logs; in blockchains; and for redacting signatures, even when all the original signatures are produced by a single user. We provide two constructions of single-signer locally verifiable aggregate signatures, the first based on the RSA assumption and the second on the bilinear Diffie-Hellman inversion assumption, both in the random oracle model. As an additional contribution, we introduce the notion of compressing cryptographic keys in identity-based encryption (IBE) schemes, show applications of this notion, and construct an IBE scheme where the secret keys for $N$ identities can be compressed into a single aggregate key, which can then be used to decrypt ciphertexts sent to any of the $N$ identities

Privacy Enhancing Technologies for solving the privacy-personalization paradox : taxonomy and survey

Personal data are often collected and processed in a decentralized fashion, within different contexts. For instance, with the emergence of distributed applications, several providers are usually correlating their records, and providing personalized services to their clients. Collected data include geographical and indoor positions of users, their movement patterns as well as sensor-acquired data that may reveal users’ physical conditions, habits and interests. Consequently, this may lead to undesired consequences such as unsolicited advertisement and even to discrimination and stalking. To mitigate privacy threats, several techniques emerged, referred to as Privacy Enhancing Technologies, PETs for short. On one hand, the increasing pressure on service providers to protect users’ privacy resulted in PETs being adopted. One the other hand, service providers have built their business model on personalized services, e.g. targeted ads and news. The objective of the paper is then to identify which of the PETs have the potential to satisfy both usually divergent - economical and ethical - purposes. This paper identifies a taxonomy classifying eight categories of PETs into three groups, and for better clarity, it considers three categories of personalized services. After defining and presenting the main features of PETs with illustrative examples, the paper points out which PETs best fit each personalized service category. Then, it discusses some of the inter-disciplinary privacy challenges that may slow down the adoption of these techniques, namely: technical, social, legal and economic concerns. Finally, it provides recommendations and highlights several research directions

Data Protection for the Internet of Things

The Internet of Things (abbreviated: “IoT”) is acknowledged as one of the most important disruptive technologies with more than 16 billion devices forecasted to interact autonomously by 2020. The idea is simple, devices will help to measure the status of physical objects. The devices, containing sensors and actuators, are so small that they can be integrated or attached to any object in order to measure that object and possibly change its status accordingly. A process or work flow is then able to interact with those devices and to control the objects physically. The result is the collection of massive data in a ubiquitous form. This data can be analysed to gain new insights, a benefit propagated by the “Big Data” and “Smart Data” paradigms. While governments, cities and industries are heavily involved in the Internet of Things, society’s privacy awareness and the concerns over data protection in IoT increase steadily. The scale of the collection, processing and dissemination of possibly private information in the Internet of Things has long begun to raise privacy concerns. The problem is a fundamental one, it is the massive data collection that benefits the investment on IoT, while it contradicts the interest on data minimization coming from privacy advocates. And the challenges go even further, while privacy is an actively researched topic with a mature variety of privacy preserving mechanisms, legal studies and surveillance studies in specific contexts, investigations of how to apply this concepts in the constrained environment of IoT have merely begun. Thus the objective of this thesis is threefold and tackles several topics, looking at them in a differentiated way and later bringing them together for one of the first, (more) complete pictures of privacy in IoT. The first starting point is the throughout study of stakeholders, impact areas and proposals on an architectural reference model for IoT. At the time of this writing, IoT was adversed heavily by several companies, products and even governments, creating a blurred picture of what IoT really is. This thesis surveys stakeholders, scenarios, architecture paradigms and definitions to find a working definition for IoT which adequately describes the intersection between all of the aforementioned topics. In a further step, the definition is applied exemplary on two scenarios to identify the common building blocks of those scenarios and of IoT in general. The building blocks are then verified against a similar approach by the IoT-A and Rerum projects and unified to an IoT domain model. This approach purposefully uses notions and paradigms provided in related scientific work and European projects in order to benefit from existing efforts and to achieve a common understanding. In this thesis, the observation of so called cyber-physical properties of IoT leads to the conclusion that IoT proposals miss a core concept of physical interaction in the “real world”. Accordingly, this thesis takes a detour to jurisdiction and identifies ownership and possession as a main concept of “human-to-object” relationships. The analysis of IoT building blocks ends with an enhanced IoT domain model. The next step breaks down “privacy by design”. Notably hereby is that privacy by design has been well integrated in to the new European General Data Protection Regulation (GDPR). This regulation heavily affects IoT and thus serves as the main source of privacy requirements. Gürses et al.’s privacy paradigm (privacy as confidentiality, privacy as control and privacy as practice) is used for the breakdown, preceded by a survey of relevant privacy proposals, where relevancy was measured upon previously identified IoT impact areas and stakeholders. Independently from IoT, this thesis shows that privacy engineering is a task that still needs to be well understood. A privacy development lifecycle was therefore sketched as a first step in this direction. Existing privacy technologies are part of the survey. Current research is summed up to show that while many schemes exist, few are adequate for actual application in IoT due to their high energy or computational consumption and high implementation costs (most notably caused by the implementation of special arithmetics). In an effort to give a first direction on possible new privacy enhancing technologies for IoT, new technical schemes are presented, formally verified and evaluated. The proposals comprise schemes, among others, on relaxed integrity protection, privacy friendly authentication and authorization as well as geo-location privacy. The schemes are presented to industry partners with positive results. This technologies have thus been published in academia and as intellectual property items. This thesis concludes by bringing privacy and IoT together. The final result is a privacy enhanced IoT domain model accompanied by a set of assumptions regarding stakeholders, economic impacts, economic and technical constraints as well as formally verified and evaluated proof of concept technologies for privacy in IoT. There is justifiable interest in IoT as it helps to tackle many future challenges found in several impact areas. At the same time, IoT impacts the stakeholders that participate in those areas, creating the need for unification of IoT and privacy. This thesis shows that technical and economic constraints do not impede such a process, although the process has merely begun

Privacy-Preserving and Regulation-Enabled Mechanisms for Blockchain-based Financial Services

With the success of cryptocurrencies such as Bitcoin, blockchain technology has attracted extensive attention from both academia and industry. As a distributed ledger technology, blockchain provides decentralization and immutability, and can build trust among multiple parties. Owning to these unique characteristics, blockchain has become an innovative approach to secure and reliable record-keeping and transaction execution, and has the potential to revolutionize the financial industry and drive economic change on a global scale. For example, it can streamline banking and lending services, enable decentralized trading, and facilitate cross-border payment transactions. Although blockchain is expected to create a new paradigm for the financial industry, transactions stored on the blockchain are shared among the nodes in the blockchain network, which may contain sensitive information of users, such as the identities of senders and receivers, and the contents of transactions. Thus, privacy preservation should be achieved when applying blockchain to different financial services. Many privacy-preserving mechanisms have been proposed to guarantee identity privacy and data confidentiality for blockchain-based transactions. However, the strong degree of privacy may create new regulatory concerns. First, in privacy-preserving mortgage lending, there exists double-mortgage fraud, by which a borrower can use the same asset as collateral to obtain multiple loans from different financial institutions. Second, in decentralized data trading, data buyers may refuse to pay funds to data sellers after obtaining data, and data sellers may send fake data to data buyers. Verifying data availability and retrievability without viewing data before payment for fair trading is a challenging issue. Moreover, the identity privacy of data sellers should be preserved during the trading. Third, in privacy-preserving blockchain-based payment systems, the identities of the payer, payee, and transferred amount are protected. Nevertheless, the anonymity of transactions can be exploited for illegal activities, such as money laundering. Thus, considering the strict regulatory requirements of the financial industry, such as limiting the amount of cryptocurrency transferred over a period of time, privacy preservation and regulation should be balanced in blockchain-based financial services. In this thesis, we focus on three major blockchain-based financial services to concentrate on how to solve the dilemma between privacy protection and strict regulatory requirements at various phases in the fund flow, which are lending, trading, and payment. Firstly, the thesis investigates the borrower privacy and double-mortgage regulation issues in mortgage lending, and proposes a blockchain-based privacy-preserving and accountable mortgage data management scheme. In the scheme, the mortgage data of borrowers can be shared on the blockchain to detect the double-mortgage fraud without revealing the identity of borrowers. But financial institutions can still uncover the identity of a dishonest borrower if he/she pledges the same asset for multiple mortgages, which is achieved by integrating cryptographic tools such as verifiable secret sharing, zero-knowledge proof, and ElGamal encryption. A mortgage request contains a share of identity information of the borrower and the ownership certificate of an asset. By utilizing ElGamal encryption and verifiable secret sharing, the borrower can prove that its identity information is indeed included in the mortgage request and can be used to reconstruct its identity when double-mortgage behavior is detected. Secondly, the thesis investigates the identity privacy and trading-misbehavior regulation in blockchain-based data trading. Blockchain can build trust between data buyers and data sellers. To resolve the fairness issue of demonstrating data availability and retrievability without leaking data while preserving identity privacy of data sellers, we propose a blockchain-based fair data trading protocol with privacy preservation, where a data buyer can declare data requirements and acceptable issuers of data, and a data seller can conduct privacy-preserving and fine-grained data selling. We first define the fairness and privacy demands for both parties. By incorporating anonymous attribute-based credentials, structure-preserving signatures, and zero-knowledge proofs, data can be traded in part while data authenticity is guaranteed and data issuers are hidden. A smart contract is utilized to realize atomic transactions. Security proof is provided to demonstrate that the scheme can achieve privacy preservation and fairness for the participants. Thirdly, the thesis investigates the transaction privacy and anti-money laundering regulation issues in distributed anonymous payment (DAP) systems. To solve the conflict between privacy and regulation, we propose a novel DAP scheme that supports regulatory compliance and enforcement. We first introduce regulators into the system, who define regulatory policies, including limiting the total amount of cryptocurrency one can transfer and the frequency of transactions one can conduct in a time period. The policies are enforced through commitments and non-interactive zero-knowledge proofs for compostable statements. By this, users can prove that transactions are valid and comply with regulations. We use both Zero-knowledge Succinct Non-Interactive Arguments of Knowledge (Zk-SNARKs) and sigma protocols to generate the zero-knowledge proofs for regulation compliance. A tracing mechanism is designed in the scheme to allow regulators to recover the real identities of users when suspicious transactions are detected. In summary, this thesis proposes effective privacy-preserving and regulation-enabled solutions for blockchain-based lending, data trading, and anonymous payment. The results from the thesis should shed light for future study on blockchain-based systems where privacy preservation and regulation are required

Blockchain-enabled cybersecurity provision for scalable heterogeneous network: A comprehensive survey

Blockchain-enabled cybersecurity system to ensure and strengthen decentralized digital transaction is gradually gaining popularity in the digital era for various areas like finance, transportation, healthcare, education, and supply chain management. Blockchain interactions in the heterogeneous network have fascinated more attention due to the authentication of their digital application exchanges. However, the exponential development of storage space capabilities across the blockchain-based heterogeneous network has become an important issue in preventing blockchain distribution and the extension of blockchain nodes. There is the biggest challenge of data integrity and scalability, including significant computing complexity and inapplicable latency on regional network diversity, operating system diversity, bandwidth diversity, node diversity, etc., for decision-making of data transactions across blockchain-based heterogeneous networks. Data security and privacy have also become the main concerns across the heterogeneous network to build smart IoT ecosystems. To address these issues, today’s researchers have explored the potential solutions of the capability of heterogeneous network devices to perform data transactions where the system stimulates their integration reliably and securely with blockchain. The key goal of this paper is to conduct a state-of-the-art and comprehensive survey on cybersecurity enhancement using blockchain in the heterogeneous network. This paper proposes a full-fledged taxonomy to identify the main obstacles, research gaps, future research directions, effective solutions, and most relevant blockchain-enabled cybersecurity systems. In addition, Blockchain based heterogeneous network framework with cybersecurity is proposed in this paper to meet the goal of maintaining optimal performance data transactions among organizations. Overall, this paper provides an in-depth description based on the critical analysis to overcome the existing work gaps for future research where it presents a potential cybersecurity design with key requirements of blockchain across a heterogeneous network