Stochastic Gradient Descent (SGD) is the foundation of modern machine learning (ML). In privacy-sensitive settings, gradients can reveal details about individual data points. Differential Privacy (DP) protects sensitive data during ML training by clipping gradients and adding calibrated Gaussian noise. However, existing frameworks assume semi-honest participants, which fails in adversarial or federated environments where malicious actors can bypass or alter the noise addition process, breaking privacy guarantees. We present VeriDP, a framework for verifiable differentially private training that cryptographically enforces and proves the correct execution of differentially private stochastic gradient descent (DP-SGD) in zero knowledge. VeriDP integrates Zero-Knowledge Proofs (ZKPs) with polynomial commitments, sumcheck and GKR-based proofs, and incrementally verifiable computation (IVC) to generate compact proofs of correct gradient computation, clipping, averaging, and Gaussian noise generation—without revealing private data or randomness. Unlike previous systems that only verify the final privacy budget, VeriDP enables per-iteration verifiability of each model update, providing strong privacy assurances even in adversarial settings. This establishes a novel and complete Zero-Knowledge Proof of Differentially Private Stochastic Gradient Descent (ZK-DPSGD), uniting differential privacy and verifiable computation for secure and auditable ML. Our evaluation shows that prover time increases linearly with the number of input samples, while both verifier time (2–5 ms) and proof size (3–4 KB) remain compact and effectively constant.

The rise of 5G technology has highlighted the critical role of Thick Mobile Virtual Network Operators (MVNOs) in providing customized mobile services. However, security and privacy challenges specific to Thick MVNOs remain inadequately addressed. In this paper, we present PGUS (Pretty Good User Security) for Thick MVNOs. Our proposed PGUS framework introduces a new cryptographic primitive called the Sanitizable Blind Signature (SBS), along with a novel Authentication and Key Agreement protocol named PGUS-AKA. Additionally, we have developed a seamless handover protocol, PGUS-HO, which is designed to secure all communication within a Thick MVNO environment. Furthermore, we conduct a thorough formal security analysis within the Universal Composability (UC) framework to address key threats, providing a strong solution for securing next-generation mobile networks. We also provide the evaluations on a 5G testbed which demonstrate the effectiveness of PGUS.

Consumers seeking a new mobile plan have many choices in the present mobile landscape. The Mobile Virtual Network Operator (MVNO) has recently gained considerable attention among these options. MVNOs offer various benefits, making them an appealing choice for a majority of consumers. These advantages encompass flexibility, access to cutting-edge technologies, enhanced coverage, superior customer service, and substantial cost savings. Even though MVNO offers several advantages, it also creates some security and privacy concerns for the customer simultaneously. For instance, in the existing solution, MVNO needs to hand over all the sensitive details, including the users' identities and master secret keys of their customers, to a mobile operator (MNO) to validate the customers while offering any services. This allows MNOs to have unrestricted access to the MVNO subscribers' location and mobile data, including voice calls, SMS, and Internet, which the MNOs frequently sell to third parties (e.g., advertisement companies and surveillance agencies) for more profit. Although critical for mass users, such privacy loss has been historically ignored due to the lack of practical and privacy-preserving solutions for registration and handover procedures in cellular networks. In this paper, we propose a universally composable authentication and handover scheme with strong user privacy support, where each MVNO user can validate a mobile operator (MNO) and vice-versa without compromising user anonymity and unlinkability support. Here, we anticipate that our proposed solution will most likely be deployed by the MVNO(s) to ensure enhanced privacy support to their customer(s).

Non-interactive zero-knowledge proofs (NIZKs) and in particular succinct NIZK arguments of knowledge (zk-SNARKs) increasingly see real-world adoption in large and complex systems. Many zk-SNARKs require a trusted setup, i.e., a common reference string (CRS), and for practical use it is desirable to reduce the trust in the CRS generation. The latter can be achieved via the notions of subversion or updatable CRS. Another important property when deployed in large systems is the ability to securely compose them to obtain more complex protocols, e.g., via the Universal Composability (UC) framework. Relying on the UC framework allows arbitrary and secure composition of protocols in a modular way. In this work, we investigate whether zk-SNARKs can provide updatability and composability simultaneously. This is a challenging task as the UC framework rules out several natural techniques for such a construction. As our main result, we show that it is indeed possible to achieve these properties in a generic and modular way if we relax the succinctness properties of zk-SNARKs slightly to those of a circuit-succinct NIZK which is not witness-succinct, i.e., by increasing the proof size of the underlying zk-SNARK by the size of the witness$w$. We argue that for various practical applications of zk-SNARKs this overhead is acceptable. Our starting point is the Lamassu framework (ACM CCS'20), which we extend in several directions. Our new generic compiler adds only minimal overhead, which we demonstrate by benchmarking its application to the Sonic proof system (ACM CCS'19).

Zero-knowledge proofs and in particular succinct non-interactive zero-knowledge proofs (so called zk-SNARKs) are getting increasingly used in real-world applications, with cryptocurrencies being the prime example. Simulation extractability (SE) is a strong security notion for zk-SNARKs which informally ensures non-malleability of proofs. The high importance of this property is acknowledged by leading companies in this field such as Zcash and underpinned by various attacks against the malleability of cryptographic primitives in the past. Another problematic issue for the practical use of zk-SNARKs is the requirement of a fully trusted setup, as especially for large-scale decentralized applications finding a trusted party that runs the setup is practically impossible. Quite recently, the study of approaches to relax or even remove the trust in the setup procedure, and in particular subversion as well as updatable zk-SNARKs (with latter being the most promising approach), has been initiated and received considerable attention since then. Unfortunately, so far SE-SNARKs with the aforementioned properties are only constructed in an ad-hoc manner and no generic techniques are available.