International Association
for Cryptologic Research

About the Project
We are seeking a highly motivated PhD candidate to join our DFG-funded project on privacy-preserving rare disease analysis. This interdisciplinary research initiative focuses on developing secure and efficient methods for variant filtering, prioritization, and rare-variant association studies.

Responsibilities

• Conduct research on secure algorithms and protocols for privacy-preserving analysis of genomic and clinical data.
• Develop and integrate methods for variant filtering, prioritization, and rare-variant association studies in a federated environment.
• Implement and evaluate methods as part of an open-source software framework for privacy-preserving rare variant analyses.
• Present findings in peer-reviewed publications and international conferences.

Requirements

• Master’s degree (or equivalent) in Computer Science, Bioinformatics, Mathematics, or a related field.
• Background or interest in cryptography (e.g., secure multi-party computation), machine learning (e.g., federated learning, data privacy), or bioinformatics (e.g., variant analysis).
• Solid programming skills in at least one language commonly used in research (Python, C/C++, Java, etc.).
• Strong analytical and problem-solving capabilities.
• Excellent communication and teamwork skills.

How to Apply
Please email a single PDF to [Contact Email Address] with:

1. Cover Letter (your motivation and relevant experience)
2. CV (academic background, technical skills, publications)
3. Transcript(s) (BSc, MSc or equivalent)
4. References(contact details)

Application Deadline: [30.04.2025]

Closing date for applications:

Contact: Dr. Mete Akgün

More information: https://mdppml.github.io/downloads/PhD_Student_in_Privacy_Preserving_Rare_Disease_Analysis.pdf

Fruit-F is a lightweight short-state stream cipher designed by Ghafari et al. The authors designed this version of the cipher, after earlier versions of the cipher viz. Fruit 80/v2 succumbed to correlation attacks. The primary motivation behind this design seemed to be preventing correlation attacks. Fruit-F has a Grain-like structure with two state registers of size 50 bits each. In addition, the cipher uses an 80-bit secret key and an 80-bit IV. The authors use a complex key-derivation function to update the non-linear register which prevents the same key-bit alignment across fixed-length window of keystream bits, which is essentially what stops the correlation attacks. In this paper, we first present two attacks against Fruit-F. The first attack stems from the fact that the key-derivation can be rewritten as the Boolean xor of two key-dependent terms one of which is the Boolean OR of two bits of the key. Using this we show that the cipher does not offer 80-bit security: the effective key space of Fruit-F is slightly less than $2^{80}$, i.e. a simple brute force attack costs around $2^{80}-2^{49}$ time. The second is a differential attack using the cipher's complex initialization process. We show that under some given conditions, it is possible to have two initial vectors $V_1$ and $V_2$ that produce identical keystream vectors with any given key. Using this as a distinguisher, it is possible to collect enough linear and quadratic equations of the secret key to find it in practical time with very few keystream bits.

We demonstrate an attack on the soundness of a widely known optimization of the Gemini multilinear Polynomial Commitment Scheme (PCS). The attack allows a malicious prover to falsely claim that a multilinear polynomial takes a value of their choice, for any input point. We stress that the original Gemini multilinear PCS and HyperKZG, an adaptation of Gemini, are not affected by the attack.

Both masking and shuffling are very common software countermeasures against side-channel attacks. However, exploring possible combinations of the two countermeasures to increase and fine-tune side-channel resilience is less investigated. With this work, we aim to bridge that gap by both concretising the security guarantees of several masking and shuffling combinations presented in earlier work and additionally investigating their randomness cost. We subsequently implement these approaches to also analyse their performance. In this context, we present five different protected implementations of the new standard for lightweight cryptography, Ascon, on a 32-bit RISC-V architecture: A 3rd-order masked, unshuffled implementation and three combined 3rd-order masked and shuffled implementations. Additionally, we present a levelled implementation where only the particularly vulnerable keyed initialisation and finalisation of the permutation are masked and shuffled, while the rest is only shuffled. To further improve the security and performance of our implementations we make use of the Probe Isolating Non-Interference (PINI) masked AND gadget, coupled with techniques like bit-slicing and bit-interleaving. Utilising benchmarking and an MI-shortcut security analysis, we pinpoint the best masking-shuffling combinations that maximize security at reasonable overheads.

Since the selection of the National Institute of Standards and Technology (NIST) Post-Quantum Cryptography (PQC) standardization algorithms, research on integrating PQC into security protocols such as TLS/SSL, IPSec, and DNSSEC has been actively pursued. However, PQC migration for Internet of Things (IoT) communication protocols remains largely unexplored. Embedded devices in IoT environments have limited computational power and memory, making it crucial to optimize PQC algorithms for efficient computation and minimal memory usage when deploying them on low-spec IoT devices. In this paper, we introduce KEM-MQTT, a lightweight and efficient Key Encapsulation Mechanism (KEM) for the Message Queuing Telemetry Transport (MQTT) protocol, widely used in IoT environments. Our approach applies the NIST KEM algorithm Crystals-Kyber (Kyber) while leveraging MQTT’s characteristics and sensor node constraints. To enhance efficiency, we address certificate verification issues and adopt KEMTLS to eliminate the need for Post-Quantum Digital Signatures Algorithm (PQC-DSA) in mutual authentication. As a result, KEM-MQTT retains its lightweight properties while maintaining the security guarantees of TLS 1.3. We identify inefficiencies in existing Kyber implementations on 8-bit AVR microcontrollers (MCUs), which are highly resource-constrained. To address this, we propose novel implementation techniques that optimize Kyber for AVR, focusing on high-speed execution, reduced memory consumption, and secure implementation, including Signed LookUp-Table (LUT) Reduction. Our optimized Kyber achieves performance gains of 81%,75%, and 85% in the KeyGen, Encaps, and DeCaps processes, respectively, compared to the reference implementation. With approximately 3 KB of stack usage, our Kyber implementation surpasses all state-of-the-art Elliptic Curve Diffie-Hellman (ECDH) implementations. Finally, in KEM-MQTT using Kyber-512, an 8-bit AVR device completes the handshake preparation process in 4.32 seconds, excluding the physical transmission and reception times.

We show that the certificateless authentication scheme [Mob. Networks Appl. 2022, 27, 346-356] fails to keep anonymity, not as claimed. The scheme neglects the basic requirement for bit-wise XOR, and tries to encrypt data by the operator. The negligence results in some trivial equalities. The adversary can retrieve the user's identity from one captured string via the open channel.

Current hardware security verification processes predominantly rely on manual threat modeling and test plan generation, which are labor-intensive, error-prone, and struggle to scale with increasing design complexity and evolving attack methodologies. To address these challenges, we propose ThreatLens, an LLM-driven multi-agent framework that automates security threat modeling and test plan generation for hardware security verification. ThreatLens integrates retrieval-augmented generation (RAG) to extract relevant security knowledge, LLM-powered reasoning for threat assessment, and interactive user feedback to ensure the generation of practical test plans. By automating these processes, the framework reduces the manual verification effort, enhances coverage, and ensures a structured, adaptable approach to security verification. We evaluated our framework on the NEORV32 SoC, demonstrating its capability to automate security verification through structured test plans and validating its effectiveness in real-world scenarios.

Deep learning-based side-channel analysis has become a popular and powerful option for side-channel attacks in recent years. One of the main directions that the side-channel community explores is how to design efficient architectures that can break the targets with as little as possible attack traces, but also how to consistently build such architectures. In this work, we explore the usage of the JumpReLU activation function, which was designed to improve the robustness of neural networks. Intuitively speaking, improving the robustness seems a natural requirement for side-channel analysis, as hiding countermeasures could be considered adversarial attacks. In our experiments, we explore three strategies: 1) exchanging the activation functions with JumpReLU at the inference phase, training common side-channel architectures with JumpReLU, and 3) conducting hyperparameter search with JumpReLU as the activation function. While the first two options do not yield improvements in results (but also do not show worse performance), the third option brings advantages, especially considering the number of neural networks that break the target. As such, we conclude that using JumpReLU is a good option to improve the stability of attack results.

In this paper, we present a side-channel attack on the hardware AES accelerator of a Bluetooth chip used in millions of devices worldwide, ranging from wearables and smart home products to industrial IoT. The attack leverages information about AES computations unintentionally transmitted by the chip together with RF signals to recover the encryption key. Unlike traditional side-channel attacks that rely on power or near-field electromagnetic emissions as sources of information, RF-based attacks leave no evidence of tampering, as they do not require package removal, chip decapsulation, or additional soldered components. However, side-channel emissions extracted from RF signals are considerably weaker and noisier, necessitating more traces for key recovery. The presented profiled machine learning-assisted attack can recover the full encryption key from 90,000 traces captured at a one-meter distance from the target device, with each trace being an average of 10,000 samples per encryption. This is a twofold improvement over the correlation analysis-based attack on the same AES accelerator.

Content-defined chunking (CDC) algorithms split streams of data into smaller blocks, called chunks, in a way that preserves chunk boundaries when the data is partially changed. CDC is ubiquitous in applications that deduplicate data such as backup solutions, software patching systems, and file hosting platforms. Much like compression, CDC can introduce leakage when combined with encryption: fingerprinting attacks can exploit chunk length patterns to infer information about the data. To address these risks, many systems—mainly in the cloud backup setting—have developed bespoke mitigations by mixing a cryptographic key into the chunking process. We study these keyed CDC (KCDC) schemes “in the wild”, presenting efficient key recovery attacks against five different KCDC schemes, deployed in the backup solutions Borg, Bupstash, Duplicacy, Restic, and Tarsnap. Our attacks are in a realistic threat model that relies only on weak known or chosen-plaintext capabilities. This shows, in particular, that they fail to protect against fingerprinting attacks. To demonstrate practical exploitability, we also present “end-to-end” attacks on three complete encrypted backup applications, namely Borg, Restic and Tarsnap. These build on our attacks on the underlying KCDC schemes. In an effort to tackle these problems, we introduce the first formal treatment for KCDC schemes and propose a provably secure construction that fulfills a strong notion of security. We benchmark our construction against existing (broken) approaches, showing that it has competitive performance. In doing so, we take a step towards making real-world systems that rely on KCDC more resilient to attacks.

Distributed SNARKs enable multiple provers to collaboratively generate proofs, enhancing the efficiency and scalability of large-scale computations. The state-of-the-art distributed SNARK for Plonk, Pianist (S\&P '24), achieves constant proof size, constant amortized communication complexity, and constant verifier complexity. However, when proving the Rank-One Constraint System (R1CS), a widely used intermediate representation for SNARKs, Pianist must perform the transformation from R1CS into Plonk before proving, which can introduce a start-up cost of $10\times$ due to the expansion of the statement size. Meanwhile, existing distributed SNARKs for R1CS, e.g., DIZK (USENIX Sec. '18) and Hekaton (CCS '24), fail to match the superior asymptotic complexities of Pianist.

We propose $\textsf{Soloist}$, an optimized distributed SNARK for R1CS. $\textsf{Soloist}$ achieves constant proof size, constant amortized communication complexity, and constant verifier complexity, relative to the R1CS size $n$. Utilized with $\ell$ sub-provers, its prover complexity is $O(n/\ell \cdot \log(n/\ell))$. The concrete prover time is~$\ell\times$ as fast as the R1CS-targeted Marlin (Eurocrypt '20). For zkRollups, $\textsf{Soloist}$ can prove more transactions, with $2.5 \times$ smaller memory costs, $2.8\times$ faster preprocessing, and $1.8\times$ faster proving than Pianist.

$\textsf{Soloist}$ leverages an improved inner product argument and a new batch bivariate polynomial commitment variant of KZG (Asiacrypt '10). To achieve constant verification, we propose a new preprocessing method with a lookup argument for unprescribed tables, which are usually assumed pre-committed in prior works. Notably, all these schemes are equipped with scalable distributed mechanisms.

In order for a client to securely connect to a server on the web, the client must trust certificate authorities (CAs) only to issue certificates to the legitimate operator of the server. If a certificate is miss-issued, it is possible for an attacker to impersonate the server to the client. The goal of Certificate Transparency (CT) is to log every certificate issued in a manner that allows anyone to audit the logs for miss-issuance. A client can even audit a CT log itself, but this would leak sensitive browsing data to the log operator. As a result, client-side audits are rare in practice. In this work, we revisit private CT auditing from a real-world perspective. Our study is motivated by recent changes to the CT ecosystem and advancements in Private Information Retrieval (PIR). First, we find that checking for inclusion of Signed Certificate Timestamps (SCTs) in a log — the audit performed by clients — is now possible with PIR in under a second and under 100kb of communication with minor adjustments to the protocol that have been proposed previously. Our results also show how to scale audits by using existing batching techniques and the algebraic structure of the PIR protocols, in particular to obtain certificate hashes by included in the log. Since PIR protocols are more performant with smaller databases, we also suggest a number of strategies to lower the size of the SCT database for audits. Our key observation is that the web will likely transition to a new model for certificate issuance. While this transition is primarily motivated by the need to adapt the PKI to larger, post-quantum signature schemes, it also removes the need for SCT audits in most cases. We present the first estimates of how this transition may impact SCT auditing, based on data gathered from public CT logs. We find that large scale deployment of the new issuance model may reduce the number of SCT audits needed by a factor of 1,000, making PIR-based auditing practical to deploy.

We initiate the study of strong federated authentication with password-based credential against identity server corruption (SaPBC). We provide a refined formal security model, which captures all the necessary security properties in registration, authentication, and session key establishment between a user and an application server. The new model with fine-grained information leakage separates the leakage of password-related files and long-term secrets (including passwords and credentials). Moreover, we present two SaPBC protocols constructed from efficient cryptographic primitives for these corruption scenarios. In addition to rigorous security proofs, we also conduct comprehensive performance evaluation of the two protocols.

We analyze the composition of symmetric encryption and digital signatures in secure group messaging protocols where group members share a symmetric encryption key. In particular, we analyze the chat encryption algorithms underlying MLS, Session, Signal, and Matrix using the formalism of symmetric signcryption introduced by Jaeger, Kumar, and Stepanovs (Eurocrypt 2024). We identify theoretical attacks against each of the constructions we analyze that result from the insufficient binding between the symmetric encryption scheme and the digital signature scheme. In the case of MLS and Session, these translate into practically exploitable replay and reordering attacks by a group-insider. For Signal this leads to a forgery attack by a group-outsider with access to a user’s signing key, an attack previously discovered by Balbás, Collins, and Gajland (Asiacrypt 2023). In Matrix there are mitigations in the broader ecosystem that prevent exploitation. We provide formal security theorems that each of the four constructions are secure up to these attacks. Additionally, in Session we identified two attacks outside the symmetric signcryption model. The first allows a group-outsider with access to an exposed signing key to forge arbitrary messages and the second allows outsiders to replay ciphertexts.

Hardware IP blocks have been subjected to various forms of confidentiality and integrity attacks in recent years due to the globalization of the semiconductor industry. System-on-chip (SoC) designers are now considering a zero-trust model for security, where an IP can be attacked at any stage of the manufacturing process for piracy, cloning, overproduction, or malicious alterations. Hardware redaction has emerged as a promising countermeasure to thwart confidentiality and integrity attacks by untrusted entities in the globally distributed supply chain. However, existing redaction techniques provide this security at high overhead costs, making them unsuitable for real-world implementation. In this paper, we propose HIPR, a fine-grain redaction methodology that is robust, scalable, and incurs significantly lower overhead compared to existing redaction techniques. HIPR redacts security-critical Boolean and sequential logic from the hardware design, performs interconnect randomization, and employs multiple overhead optimization steps to reduce overhead costs. We evaluate HIPR on open-source benchmarks and reduce area overheads by 1 to 2 orders of magnitude compared to state-of-the-art redaction techniques without compromising security. We also demonstrate that the redaction performed by HIPR is resilient against conventional functional and structural attacks on hardware IPs. The redacted test IPs used to evaluate HIPR are available at: https://github.com/UF-Nelms-IoT-Git-Projects/HIPR.

A (single server) private information retrieval (PIR) allows a client to read data from a public database held on a remote server, without revealing to the server which locations she is reading. In a doubly efficient PIR (DEPIR), the database is first preprocessed offline into a data structure, which then allows the server to answer any client query efficiently in sub-linear online time. Constructing DEPIR is a notoriously difficult problem, and this difficulty even extends to a weaker notion secret-key DEPIR (SK-DEPIR), where the database is preprocessed using secret randomness and the client is given a secret key for making queries. We currently only have constructions of SK-DEPIR from the Ring LWE assumption or from non-standard code-based assumptions.

We show that the black-box use of essentially all generic cryptographic primitives (e.g., key agreement, oblivious transfer, indistinguishability obfuscation, etc.), including idealized primitives (e.g., random oracles, generic multilinear groups, virtual black-box obfuscation, etc.) is essentially useless for constructing SK-DEPIR. In particular, in any such SK-DEPIR construction, we can replace all black-box use of these primitives with just a black-box use of one-way functions. While we conjecture that SK-DEPIR cannot be constructed using black-box one-way functions alone, we are unable to show this in its full generality. However, we do show this for 2-round schemes with a passive server that simply outputs requested locations in the preprocessed data structure, which is the format of all known schemes. Overall, this shows that the black-box use of essentially all crypto primitives is insufficient for constructing 2-round passive-server SK-DEPIR, and does not provide any benefit beyond black-box one-way functions for constructing general SK-DEPIR.

In a social key recovery scheme, users back up their secret keys (typically using Shamir's secret sharing) with their social connections, known as a set of guardians. This places a heavy burden on the guardians, as they must manage their shares both securely and reliably. Finding and managing such a set of guardians may not be easy, especially when the consequences of losing a key are significant.

We take an alternative approach of social recovery within a community, where each member already holds a secret key (with possibly an associated public key) and uses other community members as their guardians forming a mutual dependency among themselves. Potentially, each member acts as a guardian for upto $(n-1)$ other community members. Therefore, in this setting, using standard Shamir's sharing leads to a linear ($O(n)$) blow-up in the internal secret storage of the guardian for each key recovery. Our solution avoids this linear blowup in internal secret storage by relying on a novel secret-sharing scheme, leveraging the fact that each member already manages a secret key. In fact, our scheme does not require guardians to store anything beyond their own secret keys.

We propose the first formal definition of a social key recovery scheme for general access structures in the community setting. We prove that our scheme is secure against any malicious and adaptive adversary that may corrupt up to $t$ parties. As a main technical tool, we use a new notion of secret sharing, that enables $(t+1)$ out of $n$ sharing of a secret even when the shares are generated independently -- we formalize this as bottom-up secret sharing (BUSS), which may be of independent interest.

Finally, we provide an implementation benchmarking varying the number of guardians both in a regional, and geo-distributed setting. For instance, for 8 guardians, our backup protocol takes around 146-149 ms in a geo-distributed WAN setting, and 4.9-5.9 ms in the LAN setting; for recovery protocol, the timings are approximately the same for the WAN setting (as network latency dominates), and 1.2-1.4 ms for the LAN setting.

This work presents an exact and compact formula for the probability of rotation-xor differentials (RX-differentials) through modular addition, for arbitrary rotation amounts, which has been a long-standing open problem. The formula comes with a rigorous proof and is also verified by extensive experiments.

Our formula uncovers error in a recent work from 2022 proposing a formula for rotation amounts bigger than 1. Surprisingly, it also affects correctness of the more studied and used formula for the rotation amount equal to 1 (from TOSC 2016). Specifically, it uncovers rare cases where the assumptions of this formula do not hold. Correct formula for arbitrary rotations now opens up a larger search space where one can often find better trails.

For applications, we propose automated mixed integer linear programming (MILP) modeling techniques for searching optimal RX-trails based on our exact formula. They are consequently applied to several ARX designs, including Salsa, Alzette and a small-key variant of Speck, and yield many new RX-differential distinguishers, some of them based on provably optimal trails. In order to showcase the relevance of the RX-differential analysis, we also design Malzette, a 12-round Alzette-based permutation with maliciously chosen constants, which has a practical RX-differential distinguisher, while standard differential/linear security arguments suggest sufficient security.

Digital identity wallets allow citizens to prove who they are and manage digital documents, called credentials, such as mobile driving licenses or passports. As with physical documents, secure and privacy-preserving management of the credential lifecycle is crucial: a credential can change its status from issued to valid, revoked or expired. In this paper, we focus on the analysis of cryptographic accumulators as a revocation scheme for digital identity wallet credentials. We describe the most well-established public key accumulators, and how zero-knowledge proofs can be used with accumulators for revocation of non-anonymous credentials. In addition, we assess the computational and communication costs analytically and experimentally. Our results show that they are comparable with existing schemes used in the context of certificate revocation.

HuFu is an unstructured lattice-based signature scheme proposed during the NIST PQC standardization process. In this work, we present a side-channel analysis of HuFu's reference implementation.

We first exploit the multiplications involving its two main secret matrices, recovering approximately half of their entries through a non-profiled power analysis with a few hundred traces. Using these coefficients, we reduce the dimension of the underlying LWE problem, enabling full secret key recovery with calls to a small block-sized BKZ.

To mitigate this attack, we propose a countermeasure that replaces sensitive computations involving a secret matrix with equivalent operations derived solely from public elements, eliminating approximately half of the identified leakage and rendering the attack unfeasible.

Finally, we perform a non-profiled power analysis targeting HuFu's Gaussian sampling procedure, recovering around 75\% of the remaining secret matrix's entries in a few hundred traces. While full key recovery remains computationally intensive, we demonstrate that partial knowledge of the secret significantly improves the efficiency of signature forgery.