Transport Layer Security (TLS) is foundational for safeguarding client-server communication. However, it does not extend integrity guarantees to third-party verification of data authenticity. If a client wants to present data obtained from a server, it cannot convince any other party that the data has not been tampered with. TLS oracles ensure data authenticity beyond the client-server TLS connection, such that clients can obtain data from a server and ensure provenance to any third party, without server-side modifications. Generally, a TLS oracle involves a third party, the verifier, in a TLS session to verify that the data obtained by the client is accurate. Existing protocols for TLS oracles are communication-heavy, as they rely on interactive protocols. We present ORIGO, a TLS oracle with constant communication. Similar to prior work, ORIGO introduces a third party in a TLS session, and provides a protocol to ensure the authenticity of data transmitted in a TLS session, without forfeiting its confidentiality. Compared to prior work, we rely on intricate details specific to TLS 1.3, which allow us to prove correct key derivation, authentication and encryption within a Zero Knowledge Proof (ZKP). This, combined with optimizations for TLS 1.3, leads to an efficient protocol with constant communication in the online phase. Our work reduces online communication by 375× and online runtime by up to 4.6×, compared to prior work.

Web users can gather data from secure endpoints and demonstrate the provenance of sensitive data to any third party by using privacy-preserving TLS oracles. In practice, privacy-preserving TLS oracles remain limited and cannot verify larger, sensitive data sets. In this work, we introduce new optimizations for TLS oracles, which enhance the efficiency of selectively verifying the provenance of confidential web data. The novelty of our work is a construction which secures an honest verifier zero-knowledge proof system in the asymmetric privacy setting while retaining security against malicious adversaries. Concerning TLS 1.3 in the one round-trip time (1-RTT) mode, we propose a new, optimized garble-then-prove paradigm in a security setting with malicious adversaries. Our improvements reach new performance benchmarks and facilitate a practical deployment of privacy-preserving TLS oracles in web browsers.

Latest identity systems rely on public blockchains to enhance user autonomy and reduce tracking from conventional identity providers. At the same time, identity systems integrate novel technologies such as zero-knowledge proofs (ZKPs) to improve data privacy and data compliance. We show that a naive verification of ZKPs at smart contracts enables replay attacks: Attackers can replay ZKPs at arbitrary times without having access to the private inputs that are required for the computation of the ZKP. To solve this problem, we construct a transaction sequence which verifies time-bound and replay-resistant ZKPs at smart contracts. Our construction introduces an additional but constant fee of 0.14${\$}$ per verification of a ZKP on the public blockchain Ethereum. With our new construction, we propose Portal, a novel identity system for decentralized single sign-on.

Modern privacy-enhancing technologies reach new forms of computation and data privacy according to a statement (e.g. private value $\gt \mathbf{100}$). However, beyond the statement expression, the description of a private computation circuit requires knowledge of security algorithms protecting private values. To keep the description of private and compliant computation circuits as close to the statement expression as possible, we introduce a new composable policy language called zkPolicy. Further, we introduce a policy transpiler, called zkGen, to decouple the complexity expressed via zkPolicy from the complexity of the underlying security algorithms. Our results show that, with zkPolicy, the description of compliant data provenance circuits can be reduced from 957 to 22 lines of code. And, with zkGen, we automate the generation and composition of private computation circuits to a minimum effort of configuring a zkPolicy.

Society appears to be on the verge of recognizing the need for control over sensitive data in modern web applications. Recently, many systems claim to give control to individuals, promising the preeminent goal of data sovereignty. However, despite recent attention, research and industry efforts are fragmented and lack a holistic system overview. In this paper, we provide the first transecting systematization of data sovereignty by drawing from a dispersed body of knowledge. We clarify the field by identifying its three main areas: (i) decentralized identity, (ii) decentralized access control and (iii) policy-compliant decentralized computation. We find that literature lacks a cohesive set of formal definitions. Each area is considered in isolation, and priorities in industry and academia are not aligned due to a lack of clarity regarding user control. To solve this issue, we propose formal definitions for each sub-area. By highlighting that data sovereignty transcends the domain of decentralized identity, we aim to guide future works to embrace a broader perspective on user control. In each section, we augment our definition with security and privacy properties, discuss the state of the art and proceed to identify open challenges. We conclude by highlighting synergies between areas, emphasizing the real-world benefit obtained by further developing data sovereign systems.

Emerging identity systems in the Web 3.0 achieve a new notion of digital ownership and control. Yet, existing identity ecosystems face bootstrapping issues as trustworthy authorities cannot be represented with adequate privacy. To equip authorities with trustworthy attributes, this work introduces a protocol of domain ownership oracles, where domain owners can prove domain ownership to any third party while remaining anonymous. To prove ownership of an anonymous domain example. com, users convince verifiers of t he f acts that (i) example.com is in control of users and that (ii) example.com belongs to a public anonymity set of domains. Verifiers learn nothing beyond these two facts and cannot determine which user owns which domain. For the first time, o ur work proposes a practical system to attribute anonymous domain owners with credentials of domain ownership where the degree of anonymity depends on the size of a public anonymity set of domains.

With the ongoing efforts toward autonomous driving, modern vehicles become increasingly digital and smart. Hence, the vehicle architecture including smart sensors, ECUs, and in-vehicle communication also faces new challenges to satisfy the ever-changing safety and security requirements. The complexity of the system naturally exposes many attack surfaces that demand for sound security solutions to protect the vehicle from potential intrusions. State-of-the-art approaches such as intrusion detection and intrusion response systems require lots of training and testing against various attack scenarios. However, implementing such attacks in real environments is difficult, expensive, and involves many legal and safety considerations. With Simutack, we present an open-source attack simulation framework that is capable of generating realistic attack scenarios for comprehensive security testing in the automotive development process. The framework integrates several classes of attacks, for instance, smart sensor attacks, V2X attacks, and attacks targeting the in-vehicle networks, which are all among the most commonly exploited attack vectors. We evaluate three common attack scenarios that showcase the applicability and capabilities of our work. In each scenario, the generated attack data is processed and returned to the simulation to visualize the attack’s effect on the vehicle and its environment. Furthermore, a custom autopilot application demonstrates the attack’s impact on autonomous driving systems.

The publish/subscribe (Pub/Sub) model offers a communication scheme that is appropriate for a variety of mobile Internet of Things (IoT) systems (e.g., autonomous vehicles). In most of these systems, ensuring the end-to-end (E2E) security of exchanged information is a critical requirement. However, the Pub/Sub scheme lacks appropriate mechanisms to ensure the E2E security, even when state-of-the-art solutions, such as transport layer security (TLS) or attribute-based encryption (ABE), were adopted. These solutions either do not offer E2E security or are infeasible to be adopted in mobile IoT systems with resource-constrained platforms. In this article, we propose a framework, so-called SEEMQTT, to ensure secure E2E Pub/Sub-based communication for mobile IoT systems. Our solution allows the publisher to encrypt the published messages and control which subscribers can decrypt these messages without violating the decoupling requirement of the Pub/Sub model. Our solution leverages multiple honest-but-curious KeyStores to store secret shares generated from a secret key using a secret sharing scheme. The links between the publisher and every KeyStores are secured using identity-based encryption (IBE). The publisher uses the secret key to encrypt published messages. Trust delegation is used to authorize certain subscribers to access these shares and consequently decrypt the published messages. We provide an Arduino-based library that implements our proposed protocol. Also, we perform an extensive performance evaluation using real IoT hardware. Experimental results show that adopting our proposed solution, SEEMQTT, makes E2E security for mobile IoT systems feasible.

Driving scenarios of autonomous vehicles combine many data sources with new networking requirements in highly dynamic system setups. To keep security mechanisms applicable to new application fields in the automotive domain, our work introduces a security framework to generate, attack, and validate realistic data sets at rest and in transit. Concerning realistic data sets, our framework leverages autonomous driving simulators as well as static data sets of vehicle sensors. A configurable networking setup enables flexible data encapsulation to perform and validate networking attacks on data in transit. We validate our results with intrusion detection algorithms and simulation environments. Generated data sets and configurations are reproducible, portable, storable, and support iterative security testing of scenarios.

Cyber attacks are increasingly targeting connected vehicles. Due to this, Intrusion Response System (IRS) is becoming necessary to respond to unpreventable attacks. This paper proposes a multi-layer IRS prototype that incorporates distributed process management to support continuous control and monitoring of incident responses. Based on our analysis of IRS taxonomies, our prototype respects the latest IRS system requirements.

The Publish/Subscribe (Pub/Sub) pattern is an attractive paradigm for supporting Vehicle to Cloud (V2C) communication. However, the security threats on confidentiality, integrity, and access control of the published data challenge the adoption of the Pub/Sub model. To address that, our paper proposes a secure policy-based Pub/Sub model for V2C communication, which allows to encrypt and control the access to messages published by vehicles. A vehicle encrypts messages with a symmetric key while saving the key in distributed shares on semi-honest services, called KeyStores, using the concept of secret sharing. The security policy, generated by the same vehicle, authorizes certain cloud services to obtain the shares from the KeyStores. Here, granting access rights takes place without violating the decoupling requirement of the Pub/Sub model. Experimental results show that, besides the end-to-end security protection, our proposed system introduces significantly less overhead (almost 70% less) than the state-of-the-art approach SSL when reestablishing connections, which is a common scenario in the V2C context due to unreliable network connection.