International Association
for Cryptologic Research

Running machine learning algorithms on encrypted data is a way forward to marry functionality needs common in industry with the important concerns for privacy when working with potentially sensitive data. While there is already a growing field on this topic and a variety of protocols, mostly employing fully homomorphic encryption or performing secure multiparty computation (MPC), we are the first to propose a protocol that makes use of a specialized encryption scheme that allows to do secure comparisons on ciphertexts and update these ciphertexts to be encryptions of the same plaintexts but under a new key. We call this notion Updatable Order-Revealing Encryption (uORE) and provide a secure construction using a key-homomorphic pseudorandom function. In a second step, we use this scheme to construct an efficient three-round protocol between two parties to compute a decision tree (or forest) on labeled data provided by both parties. The protocol is in the passively-secure setting and has some leakage on the data that arises from the comparison function on the ciphertexts. We motivate how our protocol can be compiled into an actively-secure protocol with less leakage using secure enclaves, in a graceful degradation manner, e.g. falling back to the uORE leakage, if the enclave becomes fully transparent. We also analyze the leakage of this approach, giving an upper bound on the leaked information. Analyzing the performance of our protocol shows that this approach allows us to be much more efficient (especially w.r.t. the number of rounds) than current MPC-based approaches, hence allowing for an interesting trade-off between security and performance.

Fully Homomorphic Encryption (FHE) is a powerful tool that brings privacy and security to all sorts of applications by allowing us to perform additions and multiplications directly on ciphertexts without the need of the secret key. Some applications of FHE that were previously overlooked but have recently been gaining traction are data compression and image processing. Practically, FHE enables applications such as private satellite searching, private object recognition, or even encrypted video editing.

We propose a practical FHE-friendly image compression and processing pipeline where an image can be compressed and encrypted on the client-side, sent to a server which decompresses it homomorphically and then performs image processing in the encrypted domain before returning the encrypted result to the client.

Inspired by JPEG, our pipeline also relies on discrete cosine transforms and quantization to simplify the representation of an image in the frequency domain, making it possible to effectively use a compression algorithm. This pipeline is designed to be compatible with existing image-processing techniques in FHE, such as pixel-wise processing and convolutional filters. Using this technique, a high-definition ($1024\times1024$) image can be homomorphically decompressed, processed with a convolutional filter and re-compressed in under $24.7$s, while using ~8GB memory.

Temporary contract | 12 Months | Belval Are you passionate about research? So are we! Come and join us The Luxembourg Institute of Science and Technology (LIST) is a Research and Technology Organization (RTO) active in the fields of materials, environment and IT. Do you want to know more about LIST? Check our website: https://www.list.lu/ Discover our IT for Innovative Services department: https://www.list.lu/en/informatics/ How will you contribute? Your specific mission includes, but is not limited to, participating into the following activities along the project partners: • To analyze the security of wireless networks in dedicated scenarios, e.g., stage control in theatres. • To analyze the independences (security-oriented) between different services which use the same wireless network. • To prototype ML-based vulnerability and attack detection technologies for wireless networks. • To develop open-source software. • To validate the effectiveness of developed technologies. You are in charge of disseminating and promoting the research activities that will be carried out, whether through publications, prototype development or technical reports. You’re highly motivated and have proven skills in machine learning & cybersecurity to address the security concerns in wireless communication networks. You have already good experience in designing network intrusion detection solutions that use advanced machine learning techniques which can offer significant advantages over other methods. And last, but not least, you’re a great practitioner of cybersecurity technique benchmarking and testing in simulated environments. Is Your profile described below? Are you our future colleague? Apply now! As to join us, you: • Hold a PhD. degree in Computer Science or related disciplines • Have good programming skills (particularly experience on Python and C++) • Have good track record on wireless network security, such as vulnerability detection and anomaly detection in Wifi and Telecom netw

Closing date for applications:

Contact: Schwartz Cathy

More information: https://www.list.lu/en/jobs/

This postdoctoral position is for 3 years (with possible extension to up to 4 years) and is linked with a research effort aiming to apply cryptographic methods for studying the security aspects of Artificial Intelligence (AI). Cryptographic approaches will be tested for attacks on AI and existing protection methods in cryptography will be applied for security of AI. The candidate will have the freedom to explore new related topics and drive the research in the direction of security of AI and cryptographic elements. The postdoc will work with a team at the Selmer Center in Secure Communication, including among others Adj. Prof. Vincent Rijmen, Adj. Prof. Sondre Rønjom and Prof. Lilya Budaghyan.

Closing date for applications:

Contact: Prof. Budaghyan: lilya.budaghyan@uib.no

More information: https://www.jobbnorge.no/en/available-jobs/job/260444/lead-ai-postdoctoral-research-fellow-position-within-cryptography-and-security-of-ai

Ready to join the future of innovation in our team at NXP? We are expanding our Trust Provisioning Team at NXP Gratkorn!

Trust Provisioning is the secure creation, insertion, and distribution of confidential data and key material for chip personalization, including product configuration and development of software for underlying production flows.

Key Responsibilities:

Design and implementation of secure web services for key and data distribution

Design and implementation of unit and integration tests for automated test execution in CI/CD pipelines, including quality aspects

Contributing to architectural and security concepts to ensure end-to-end protection of sensitive key material and data

Closing date for applications:

Contact: Kerstin Krauss

More information: https://nxp.wd3.myworkdayjobs.com/careers/job/Gratkorn/Secure-Web-Service-Java-Software-Engineer-for-Trust-Provisioning--m-f-d-_R-10051290

The IBM Zürich Research Lab invites applications for a PhD position in the area of Quantum-Safe Cryptography. The position is fully funded by SNF through the grant CryptonIs: Advanced Cryptography Based on Isogenies. The successful candidate will conduct research on cryptographic algorithms and schemes pertaining to the area of Isogeny-based Cryptography, a branch of Quantum-Safe Cryptography grounded in Number Theory and Arithmetic Geometry, under the supervision of Drs. Andrea Basso and Luca De Feo. They will join a diverse team of cryptographers working on all aspects of theoretical and applied cryptography. We are looking for candidates with an interest in the following topics Algorithmic Number Theory, Computational Algebraic Geometry, Cryptographic primitives and protocols, Cryptanalysis.

Closing date for applications:

Contact: Andrea Basso and Luca De Feo for questions. Apply online via the form at the given link. Only applications received before May 1st are guaranteed to be taken in consideration.

More information: https://www.zurich.ibm.com/careers/2024_008.html

We are pleased to announce an opportunity for a highly motivated individual to join our team at Universitat Autònoma de Barcelona as a Postdoctoral Researcher in Blockchain Technology. This position offers a unique chance to contribute to cutting-edge research and innovation in the field of distributed ledger technologies.

Responsibilities:

• Conducting original research in blockchain technology, with a focus on cryptographic protocols, consensus mechanisms, and scalability solutions.
• Developing novel algorithms and protocols to address key challenges in blockchain scalability, security, and privacy.
• Publishing high-quality research papers in top-tier conferences and journals.
• Mentoring graduate students and contributing to academic initiatives within the department.

Qualifications:

• A Ph.D. in Computer Science, Mathematics, or a related field, with a strong publication record in blockchain or cryptography.
• Expertise in cryptographic protocols and blockchain technology, with demonstrated proficiency in Python or Rust programming languages.
• Familiarity with Solidity programming for smart contract development is highly desirable.
• Strong analytical and problem-solving skills, with a passion for exploring new ideas and pushing the boundaries of research.
• Excellent communication and collaboration abilities, with a track record of working effectively in multidisciplinary teams.

This is a fixed-term position with a contract lasting until December 31, 2025.

To apply, please submit the following documents to jordi.herrera@uab.cat with subject [Blockchain Postdoctoral Position] before May 2, 2024:

• A detailed CV including a list of publications.
• A cover letter describing your research interests, relevant experience, and career goals.
• Contact information for at least three professional references.

Closing date for applications:

Contact: jordi.herrera@uab.cat

Side-channel analysis is an important part of the security evaluations of hardware components and more specifically of those that include cryptographic algorithms. Profiling attacks are among the most powerful attacks as they assume the attacker has access to a clone device of the one under attack. Using the clone device allows the attacker to make a profile of physical leakages linked to the execution of algorithms. This work focuses on the characteristics of this profile and the information that can be extracted from its application to the attack traces. More specifically, looking at unsuccessful attacks, it shows that by carefully ordering the attack traces used and limiting their number, better results can be achieved with the same profile. Using this method allows us to consider the classical attack method, i.e. where the traces are randomly ordered, as the worst case scenario. The best case scenario is when the attacker is able to successfully order and select the best attack traces. A method for identifying efficient ordering when using deep learning models as profiles is also provided. A new loss function "Scoring loss" is dedicated to training machine learning models that give a score to the attack prediction and the score can be used to order the predictions.

Hash chain based password systems are a useful way to guarantee authentication with one-time passwords. The core idea is specified in RFC 1760 as S/Key. At CCS 2017, Kogan et al. introduced T/Key, an improved password system where one-time passwords are only valid for a limited time period. They proved security of their construction in the random oracle model under a basic modeling of the adversary. In this work, we make various advances in the analysis and instantiation of hash chain based password systems. Firstly, we describe a slight generalization called U/Key that allows for more flexibility in the instantiation and analysis, and we develop a security model that refines the adversarial strength into offline and online complexity, that can be used beyond the random oracle model, and that allows to argue multi-user security directly. Secondly, we derive a new security proof of U/Key in the random oracle model, as well as dedicated and tighter security proofs of U/Key instantiated with a sponge construction and a truncated permutation. When applied to T/Key, these results improve significantly over the earlier results: whereas the originally suggested instantiation using SHA-256 achieved 128 bits of security using a hash function with a state size of 384 bits, with a truncated permutation construction one can achieve 128 bits of security already with a state size of 256 bits.

Analyzing user data while protecting the privacy of individuals remains a big challenge. Trusted execution environments (TEEs) are a possible solution as they protect processes and Virtual Machines (VMs) against malicious hosts. However, TEEs can leak access patterns to code and to the data being processed. Furthermore, when data is stored in a TEE database, the data volume required to answer a query is another unwanted side channel that contains sensitive information. Both types of information leaks, access patterns and volume patterns, allow for database reconstruction attacks.

In this paper, we present Menhir, an oblivious TEE database that hides access patterns with ORAM guarantees and volume patterns through differential privacy. The database allows range and point queries with SQL-like WHERE-clauses. It builds on the state-of-the-art oblivious AVL tree construction Oblix (S&P'18), which by itself does not protect against volume leakage. We show how volume leakage can be exploited in range queries and improve the construction to mitigate this type of attack. We prove the correctness and obliviousness of Menhir. Our evaluation shows that our approach is feasible and scales well with the number of rows and columns in the database.

We show a polynomial time quantum algorithm for solving the learning with errors problem (LWE) with certain polynomial modulus-noise ratios. Combining with the reductions from lattice problems to LWE shown by Regev [J.ACM 2009], we obtain polynomial time quantum algorithms for solving the decisional shortest vector problem (GapSVP) and the shortest independent vector problem (SIVP) for all $n$-dimensional lattices within approximation factors of $\tilde{\Omega}(n^{4.5})$. Previously, no polynomial or even subexponential time quantum algorithms were known for solving GapSVP or SIVP for all lattices within any polynomial approximation factors.

To develop a quantum algorithm for solving LWE, we mainly introduce two new techniques. First, we introduce Gaussian functions with complex variances in the design of quantum algorithms. In particular, we exploit the feature of the Karst wave in the discrete Fourier transform of complex Gaussian functions. Second, we use windowed quantum Fourier transform with complex Gaussian windows, which allows us to combine the information from both time and frequency domains. Using those techniques, we first convert the LWE instance into quantum states with purely imaginary Gaussian amplitudes, then convert purely imaginary Gaussian states into classical linear equations over the LWE secret and error terms, and finally solve the linear system of equations using Gaussian elimination. This gives a polynomial time quantum algorithm for solving LWE.

Structured Encryption (StE) enables a client to securely store and query data stored on an untrusted server. Recent constructions of StE have moved beyond basic queries, and now support large subsets of SQL. However, the security of these constructions is poorly understood, and no systematic analysis has been performed.

We address this by providing the first leakage-abuse attacks against StE for SQL schemes. Our attacks can be run by a passive adversary on a server with access to some information about the distribution of underlying data, a common model in prior work. They achieve partial query recovery against select operations and partial plaintext recovery against join operations. We prove the optimality and near-optimality of two new attacks, in a Bayesian inference framework. We complement our theoretical results with an empirical investigation testing the performance of our attacks against real-world data and show they can successfully recover a substantial proportion of queries and plaintexts.

In addition to our new attacks, we provide proofs showing that the conditional optimality of a previously proposed leakage-abuse attack and that inference against join operations is NP-hard in general.

In this paper, we introduce a new framework for constructing linkable ring signatures (LRS). Our framework is based purely on signatures of knowledge (SoK) which allows one to issue signatures on behalf of any NP-statement using the corresponding witness. Our framework enjoys the following advantages: (1) the security of the resulting LRS depends only on the security of the underlying SoK; (2) the resulting LRS naturally supports online/offline signing (resp. verification), where the output of the offline signing (resp. verification) can be re-used across signatures of the same ring. For a ring size $n$, our framework requires a SoK of the NP statement with size $\log n$.

To instantiate our framework, we adapt the well-known post-quantum secure non-interactive argument of knowledge (NIAoK), ethSTARK, into an SoK. This SoK inherents the post-quantum security and has a signature size poly-logarithmic in the size of the NP statement. Thus, our resulting LRS has a signature size of $O(\text{polylog}(\log n))$. By comparison, existing post-quantum ring signatures, regardless of linkability considerations, have signature sizes of $O(\log n)$ at best. Furthermore, leveraging online/offline verification, part of the verification of signatures on the same ring can be shared, resulting in a state-of-the-art amortized verification cost of $O(\text{polylog}(\log n))$.

Our LRS also performs favourably against existing schemes in practical scenarios. Concretely, our scheme has the smallest signature size among all post-quantum ring signatures for any ring size larger than $32$. In our experiment, at $128$-bit security and ring size of $1024$, our LRS has a size of $29$KB, and an amortized verification cost of $0.3$ ms, surpassing the state-of-the-art by a significant margin. Even without considering amortization, the verification time for a single signature is $128$ ms, which is still 10x better than state-of-the-art succinct construction, marking it comparable to those featuring linear signature size. A similar performance advantage can also be seen at signing.

This paper presents an in-depth exploration of the development and deployment of a Layer 1 (L1) blockchain designed to underpin metaverse experiences. As the digital and physical realms become increasingly intertwined, the metaverse emerges as a frontier for innovation, demanding robust, scalable, and secure infrastructure. The core of our investigation centers around the challenges and insights gained from constructing a blockchain framework capable of supporting the vast, dynamic environments of the metaverse. Through the development process, we identified key areas of focus: interoperability, performance and scalability, cost, identity, privacy, security, and accessibility.

Our findings indicate that most challenges can be effectively addressed through the implementation of cryptography and subnets (i.e., Avalanche architecture), which allow for segmented, optimized environments within the broader metaverse ecosystem. This approach not only enhances performance but also provides a flexible framework for managing the diverse needs of metaverse applications.

Fault attacks that exploit the propagation of effective/ineffective faults present a richer attack surface than Differential Fault Attacks, in the sense that the adversary depends on a single bit of information to eventually leak secret cryptographic material. In the recent past, a number of propagation-based fault attacks on Lattice-based Key Encapsulation Mechanisms have been proposed; many of which have no known countermeasures. In this work, we propose an orthogonal countermeasure principle that does not follow adhoc strategies (like shuffling operations on secret coefficients), but rather depends on cryptographically-backed guarantees to provide quantifiable defence against aforementioned fault attacks. Concretely, we propose a framework that uses rejection sampling (which has been traditionally used as alternatives to trapdoors) to convert otherwise deterministic algorithms to probabilistic ones. Our specific goals allow careful selection of distributions such that our framework functions with a constant number of retries (around $2-3$) for unfaulted executions. In other words, should a fault be injected, the probability of success is negligible; for correct execution however, the probability of success is overwhelmingly high. Using our framework, we hence enable probabilistic decryptions in Kyber, NewHope, and Masked Kyber, and completely cut-off fault propagation in known attacks on these constructions, allowing a sound defence against known fault attacks in literature.

MRAE security is an important goal for many AEAD applications where the nonce uniqueness cannot be maintained and security risks are significant. However, MRAE schemes can be quite expensive. Two of the SoTA MRAE-secure schemes; Deoxys-II and AES-GCM-SIV rely on internal parallelism and special instructions to achieve competitive performance. However, they both suffer from the same bottleneck, they have at least one call to the underlying primitive that cannot be parallelized to any other call. Romulus-M and LMDAE are two other more recent MRAE secure schemes based on TBCs that target low area hardware. However, they are unparallelizable so they are slower than their counterparts.

In this paper, we present two new AEAD modes and four instantiations based on Tweakable Block Ciphers. These new modes target equipping high-speed applications on parallel platforms with nonce misuse resistant AEAD (MRAE). The first mode, LLSIV, targets similar performance on single-core platforms to SCT-2, while eliminating the bottlenecks that make SCT-2 not fully parallelizable. The enhanced parallelism allows LLSIV to encrypt significantly more blocks on parallel platforms, compared to SCT-2, in the same amount of time. LLSIV is based on the NaT MAC, where each ciphertext block can itself be viewed as an instance of NaT when the plaintext is prepended with $0^n$. The trade-off is that LLSIV requires the inverse function of the TBC. However, the inverse function is used only once per message and we demonstrate that for parallel implementations it represents a very small overhead.

We give an instantiation of LLSIV based on the SKINNY-128-384 TBC, and a pruned scheme, dubbed pLLSIV, which targets enhanced performance compared both SCT-2 and LLSIV on all platforms, while having reduced security claims. It relies on the recently popularized prove-then-prune methodology to take full advantage of the properties of LLSIV. This leads to a significant performance improvement, making pLLSIV even faster than online TBC-based schemes that are not MRAE-secure. Last but not least, we give an instantiation that uses the primitives used in AES-GCM-SIV: the PolyVal hash function and AES. Our instantiation is faster than AES-GCM-SIV on all platforms and have better bounds. On the other hand, it relies on the ideal cipher model as it uses the ICE TBC proposed as part of the Remus AEAD design.

The second mode we describe is LLDFV. It uses ideas from LLSIV combined the Decryption-Fast SIV (DFV) framework proposed recently by Minematsu. The goal is to reduce the number of calls to the TBC by one, while making the scheme as parallelizable as LLSIV. This makes the scheme faster that DFV on all platforms.

FUTURE is a recently proposed lightweight block cipher that achieved a remarkable hardware performance due to careful design decisions. FUTURE is an Advanced Encryption Standard (AES)-like Substitution-Permutation Network (SPN) with 10 rounds, whose round function consists of four components, i.e., SubCell, MixColumn, ShiftRow and AddRoundKey. Unlike AES, it is a 64-bit-size block cipher with a 128-bit secret key, and the state can be arranged into 16 cells. Therefore, the operations of FUTURE including its S-box is defined over $\mathbb{F}_2^4$. The previous studies have shown that the integral properties of 4-bit S-boxes are usually weaker than larger-size S-boxes, thus the number of rounds of FUTURE, i.e., 10 rounds only, might be too aggressive to provide enough resistance against integral cryptanalysis. In this paper, we mount the integral cryptanalysis on FUTURE. With state-of-the-art detection techniques, we identify several integral distinguishers of 7 rounds of FUTURE. By extending this 7-round distinguisher by 3 forward rounds, we manage to recover all the 128 bits secret keys from the full FUTURE cipher without the full codebook for the first time. To further achieve better time complexity, we also present a key recovery attack on full FUTURE with full codebook. Both attacks have better time complexity than existing results.

We present a solution to the open problem of designing an efficient, unbiased and timing attack-resistant shuffling algorithm for NTRU fixed-weight sampling. Although it can be implemented without timing leakages of secret data in any architecture, we illustrate with ARMv7-M and ARMv8-A implementations; for the latter, we take advantage of architectural features such as NEON and conditional instructions, which are representative of features available on architectures targeting similar systems, such as Intel. Our proposed algorithm improves asymptotically upon the current approach, which is based on constant-time sorting networks ($O(n)$ versus $O(n \log^2 n)$), and an implementation of the new algorithm is also faster in practice, by a factor of up to $6.91\ (591\%)$ on ARMv8-A cores and $12.58\ (1158\%)$ on the Cortex-M4; it also requires fewer uniform random bits. This translates into performance improvements for NTRU encapsulation, compared to state-of-the-art implementations, of up to 50% on ARMv8-A cores and 71% on the Cortex-M4, and small improvements to key generation (up to 2.7% on ARMv8-A cores and 6.1% on the Cortex-M4), with negligible impact on code size and a slight improvement in RAM usage for the Cortex-M4.

In this work we define the notion of a permutation correlation $(\pi,A,B,C)$ s.t. $\pi(A)=B+C$ for a random permutation $\pi$ of $n$ elements and vectors $A,B,C\in \mathbb{F}^n$. We demonstrate the utility of this correlation for a wide range of applications. The correlation can be derandomized to obliviously shuffle a secret-shared list, permute a secret-shared list by a secret-shared permutation, and more. Similar techniques have emerged as a popular building block for the honest majority protocols when efficient batched random access is required, e.g. collaborative filtering, sorting, database joins, graph algorithms, and many more. We present the highly flexible notion of permutation correlation and argue that it should be viewed as a first class primitive in the MPC practitioner's toolbox.

We give two novel protocols for efficiently generating a random permutation correlation. The first makes use of recent advances in MPC-friendly PRFs to obtain a protocol requiring $O(n\ell)$ OTs/time and constant rounds to permute $n$ $\ell$-bit strings. Unlike the modern OT extension techniques we rely on, this was previously only achievable from relatively more expensive public-key cryptography, e.g. Paillier or LWE. We implement this protocol and demonstrate that it can generate a correlation for $n=2^{20},\ell=128$ in 19 seconds and $\sim2\ell n$ communication, a 15 \& $1.1\times$ improvement over the LWE solution of Juvekar at al. (CCS 2018). The second protocol is based on pseudo-random correlation generators and achieves an overhead that is \emph{sublinear} in the string length $\ell$, i.e. the communication and number of OTs is $O(n\log \ell)$. The latter protocol is ideal for the setting when you need to repeatedly permute secret-shared data by the same permutation, e.g. in graph algorithms.

Finally, we present a suite of highly efficient protocols for performing various batched random access operations. These include a class of protocols we refer to as \emph{extraction}, which allow a user to \emph{mark} a subset of $X$ and have this subset obliviously extracted into an output list. Additionally, the parties can specify an \emph{arbitrary} selection function $\sigma:[n]\rightarrow[n]$ and obtain shares of $\sigma(X)=(X_{\sigma(1)},\ldots,X_{\sigma(n)})$ from $X$. We implement these protocols and report on their performance.

Nextcloud is a leading cloud storage platform with more than 20 million users. Nextcloud offers an end-to-end encryption (E2EE) feature that is claimed to be able “to keep extremely sensitive data fully secure even in case of a full server breach”. They also claim that the Nextcloud server “has Zero Knowledge, that is, never has access to any of the data or keys in unencrypted form”. This is achieved by having encryption and decryption operations that are done using file keys that are only available to Nextcloud clients, with those file keys being protected by a key hierarchy that ultimately relies on long passphrases known exclusively to the users.

We provide the first detailed documentation and security analysis of Nextcloud's E2EE feature. Nextcloud's strong security claims motivate conducting the analysis in the setting where the server itself is considered malicious. We present three distinct attacks against the E2EE security guarantees in this setting. Each one enables the confidentiality and integrity of all user files to be compromised. All three attacks are fully practical and we have built proof-of-concept implementations for each. The vulnerabilities make it trivial for a malicious Nextcloud server to access and manipulate users' data.

We have responsibly disclosed the three vulnerabilities to Nextcloud. The second and third vulnerabilities have been remediated. The first was addressed by temporarily disabling file sharing from the E2EE feature until a redesign of the feature can be made. We reflect on broader lessons that can be learned for designers of E2EE systems.