The developers of critical networked applications currently relied on kernel-level protections to ensure the timely delivery of critical messages like Wireless Emergency Alert (WEA) or multi-factor authentication (MFA) notifications. However, the increasing complexity of mobile operating system kernels and network stacks increases the attack surface for adversaries to exploit. In this paper, we introduce a system which safeguards network availability for critical mobile applications against powerful attackers. We achieve this by using the Trusted Execution Environment (TEE) found in most mobile devices to host minimal network drivers. Further, we utilize Trusted I/O to ensure that critical messages reach the end-user even if the device’s kernel is compromised. To demonstrate the feasibility of our approach, we provide a PoC implementation that mimics multi-factor authentication. Our Evaluation demonstrates that latency for all applications is reduced by around $21 \%$ on a representative mobile platform (ARM Cortex A9), though a significant throughput performance is observed.

In credential-based authentication systems (wallets), users transmit personally identifiable and potentially sensitive data to Service Providers (SPs). Here, users must often trust that they are communicating with a legitimate SP and that the SP has a lawful reason for requesting the information that it does. In the event of data misuse, identifying and holding the SP accountable can be difficult.

ERATOSTHENES is an EC, co-funded, research project strongly considering modern security challenges in the domain of Internet of Things in mind of their huge penetration into our day to day lives. There are a series of recent challenges that recently have been converted into obstacles or risk points that could block the secure operation of IoT networks in all day to day activities, from home to office, to leisure and security. These include examples such as the highly increased number of connected devices (at all network levels) that are on top forming inhomogeneous networks and systems of systems. Different vendor characteristics further increase the attack surface that is expected to further rise in the upcoming years. Such, highly critical, characteristics, dramatically increase the needs for confidentiality access control, user and things’ privacy, devices’ trustworthiness and compliance that require lifecycle considerations. The ERATOSTHENES project orchestrates a novel distributed, automated, auditable, yet privacy-respectful, Trust and Identity Management Framework and Reference Architecture with the ultimate scope to dynamically and holistically manage IoT devices in a lifecycle approach, strengthening trust, identities, and resilience in the entire IoT ecosystem while supporting the enforcement of the NIS directive, GDPR and Cybersecurity Act. This publication describes the ERATOSTHENES technical concept and reference architecture as well as design considerations, architecture characteristics, connectivity and interoperability.

The growing interconnectedness of computer systems has led to the need for a flexible approach to trust management. Many countries operate trust schemes to enable the automated assessment of the trustworthiness of information. But this assessment remains a challenge if the information was issued in a foreign trust scheme. An issue is the lack of a root of trust shared between the trust schemes. Other challenges are the heterogeneity of trust models used by entities operating in different legal and cultural environments.

Personal data is an attractive source of insights for a diverse field of research and business. While our data is highly valuable, it is often privacy-sensitive. Thus, regulations like the GDPR restrict what data can be legally published, and what a buyer may do with this sensitive data. While personal data must be protected, we can still sell some insights gathered from our data that do not hurt our privacy. A data marketplace is a platform that helps users to sell their data while assisting buyers in discovering relevant datasets. The major challenge such a marketplace faces is balancing between offering valuable insights into data while preserving privacy requirements. Private data marketplaces try to solve this challenge by offering privacy-preserving computations on personal data. Such computations allow for calculating statistics or training machine learning models on personal data without accessing the data in plain. However, the user selling the data cannot restrict who can buy or what type of computation the data is allowed.

Trust management systems often use registries to authenticate data, or form trust decisions. Examples are revocation registries and trust status lists. By introducing distributed ledgers (DLs), it is also possible to create decentralized registries. A verifier then queries a node of the respective ledger, e.g., to retrieve trust status information during the verification of a credential. While this ensures trustworthy information, the process requires the verifier to be online and the ledger node available. Additionally, the connection from the verifier to the registry poses a privacy issue, as it leaks information about the user's behavior. In this paper, we resolve these issues by extending existing ledger APIs to support results that are trustworthy even in an offline setting. We do this by introducing attestations of the ledger's state, issued by ledger nodes, aggregatable into a collective attestation by all nodes. This attestation enables a user to prove the provenance of DL-based data to an offline verifier. Our approach is generic. So once deployed it serves as a basis for any use case with an offline verifier. We also provide an implementation for the Ethereum stack and evaluate it, demonstrating the practicability of our approach.

Authentication, authorization, and trust verification are central parts of an access control system. The conditions for granting access in such a system are collected in access policies. Since access conditions are often complex, dedicated languages – policy languages – for defining policies are in use.However, current policy languages are unable to express such conditions having privacy of users in mind. With privacy-preserving technologies, users are enabled to prove information to the access system without revealing it.In this work, we present a generic design for supporting privacy-preserving technologies in policy languages. Our design prevents unnecessary disclosure of sensitive information while still allowing the formulation of expressive rules for access control. For that we make use of zero-knowledge proofs (NIZKs). We demonstrate our design by applying it to the TPL policy language, while using SNARKs. Also, we evaluate the resulting ZK-TPL language and its associated toolchain. Our evaluation shows that for regular-sized credentials communication and verification overhead is negligible.

Digital identities play a vital role in an increasingly digital world. These identities often rely on central authorities to issue and manage them. Central authorities have the drawback of being a central trusted party, representing a bottleneck and single point of failure with exclusive control of identity-related data. Self-sovereign identity (SSI) tackles those problems by utilizing distributed ledger technology and making users the sovereign owners of their identity data. Nevertheless, SSI, as recent technology, still lacks qualified identity data. This is especially a problem since sensitive services like eGovernment or banking services require identity data issued by a qualified identity provider; thus, SSI - based identities cannot be used for these services. In this paper, we propose a concept for deriving identity data from an existing identity system into an SSI in a fully privacy-preserving way by additionally supporting offline verification. This way, we enable a chain of trust from the existing identity system to the SSI system by introducing a novel trust model. Our concept utilizes novel cryptographic primitives to support efficient and privacy-preserving identity showing as well as revo-cation. To underline the feasibility of our concept, we implement a proof system and benchmark the related use cases.

Identity management systems enable users (i.e., provers) to authenticate and provide attributes to verifiers by using certified credentials obtained from an authority. To accept such a credential, verifiers require information on whether the presented credentials are still valid or if they have been revoked. Up-to-date revocation information can be obtained from a revocation database; however, this requires that the verifier or prover is online. The problem becomes more interesting in the offline case when the prover (e.g., citizen) and verifier (e.g., police officer) do not have an Internet connection to query the revocation status of the presented credential (e.g., digital driver's license). In this paper, we extend the Self-Sovereign Identity (SSI) model to support both revocation as well as offline-verification. Our concept introduces attestations of validity for a point in time, which are issued by the SSI network for credentials that have not been revoked, i.e., added by authorized entities to a revocation list. The concept aims to be generic so that it can be used for various use cases, e.g., by giving users the control over the frequency of re-attestation. To show our concept's feasibility and practicality, we developed and evaluated an implementation that includes an efficient and privacy-preserving showing of credentials using noninteractive zero-knowledge proofs, all while being offline.

Use-after-free is a type of vulnerability commonly present in software written in memory-unsafe languages like C or C++, where a program frees a memory buffer too early. By placing counterfeit structures at the freed memory location, an attacker can leak information or gain execution control upon subsequent access. In this paper, we show that the concept of use-after-free can be generalized to any environment and situation where resources can be silently exchanged. As an instance of our generalization we demonstrate Use-After-FreeMail attacks. Use-After-FreeMail attacks gather email addresses from publicly available database leaks. The fully automated quantitative analysis brought to light that 33.5% of all free-mail addresses we tested are not valid anymore. In two user studies with 100 and 31 participants we found that 11-19% of users are affected by our attack. In qualitative case studies we investigated what information can be gained in Use-After-FreeMail attacks, e.g., payment information, and how far currently used accounts can be compromised (identity theft). Finally, drawing the connection between mitigations against traditional use-after-free scenarios and the Use-After-FreeMail scenario, we provide a concise list of recommendations to free-mail providers and users as a protection against use-after-free attacks.