International Association
for Cryptologic Research

Even though the currently used encryption and signature schemes are well tested and secure in a classical computational setting, they are not quantum-resistant as Shor's work proves. Taking this into account, alternatives based on hard mathematical problems that cannot be solved using quantum methods are needed, and lattice-based cryptography offers such solutions. The well-known GGH and NTRUEncrypt encryption schemes are proven secure, but their corresponding signature schemes are flawed in their design approach. Once introducing the computationally hard problems like Ring-LWE, elegant and efficient cryptographic primitives could be built.

Security of cryptographic primitives is usually proved by assuming ``ideal'' probability distributions. We need to replace them with approximated ``real'' distributions in the real-world systems without losing the security level. We demonstrate that the Hellinger distance is useful for this problem, while the statistical distance is mainly used in the cryptographic literature. First, we show that for preserving $\lambda$-bit security of a given security game, the closeness of $2^{-\lambda/2}$ to the ideal distribution is sufficient for the Hellinger distance, whereas $2^{-\lambda}$ is generally required for the statistical distance. The result can be applied to both search and decision primitives through the bit security framework of Micciancio and Walter (Eurocrypt 2018). We also show that the Hellinger distance gives a tighter evaluation of closeness than the max-log distance when the distance is small. Finally, we show that the leftover hash lemma can be strengthened to the Hellinger distance. Namely, a universal family of hash functions gives a strong randomness extractor with optimal entropy loss for the Hellinger distance. Based on the results, a $\lambda$-bit entropy loss in randomness extractors is sufficient for preserving $\lambda$-bit security. The current understanding based on the statistical distance is that a $2\lambda$-bit entropy loss is necessary.

Due to high IC design costs and emergence of countless untrusted foundries, logic encryption has been taken into consideration more than ever. In state-of-the-art logic encryption works, a lot of performance is sold to guarantee security against both the SAT-based and the removal attacks. However, the SAT-based attack cannot decrypt the sequential circuits if the scan chain is protected or if the unreachable states encryption is adopted. Instead, these security schemes can be defeated by the model checking attack that searches iteratively for different input sequences to put the activated IC to the desired reachable state. In this paper, we propose a practical logic encryption approach to defend against the model checking attack on sequential circuits. The robustness of the proposed approach is demonstrated by experiments on around fifty benchmarks.

In July 2020, the lattice-based CRYSTALS-Dilithium digital signature scheme has been chosen as one of the three third-round finalists in the post-quantum cryptography standardization process by the National Institute of Standards and Technology (NIST). In this work, we present the first Very High Speed Integrated Circuit Hardware Description Language (VHDL) implementation of the CRYSTALS-Dilithium signature scheme for Field-Programmable Gate Arrays (FPGAs). Due to our parallelization-based design requiring only low numbers of cycles, running at high frequency and using reasonable amount of hardware resources on FPGA, our implementation is able to sign 15832 messages per second and verify 10524 signatures per second. In particular, the signing algorithm requires 68461 Look-Up Tables (LUTs), 86295 Flip-Flops (FFs), and the verification algorithm takes 61738 LUTs and 34963 FFs on Virtex 7 UltraScale+ FPGAs. In this article, experimental results for each Dilithium security level are provided and our VHDL-based implementation is compared with related High-Level Synthesis (HLS)-based implementations. Our solution is ca 114 times faster (in the signing algorithm) and requires less hardware resources.

Gun violence results in a significant number of deaths in the United States. Starting in the 1960’s, the US Congress passed a series of gun control laws to regulate the sale and use of firearms. One of the most important but politically fraught gun control measures is a national gun registry. A US Senate office is currently drafting legislation that proposes the creation of a voluntary national gun registration system. At a high level, the bill envisions a decentralized system where local county officials would control and manage the registration data of their constituents. These local databases could then be queried by other officials and law enforcement to trace guns. Due to the sensitive nature of this data, however, these databases should guarantee the confidentiality of the data.

In this work, we translate the high-level vision of the proposed legislation into technical requirements and design a cryptographic protocol that meets them. Roughly speaking, the protocol can be viewed as a decentralized system of locally-managed end-to-end encrypted databases. Our design relies on various cryptographic building blocks including structured encryption, secure multi-party computation and secret sharing. We propose a formal security definition and prove that our design meets it. We implemented our protocol and evaluated its performance empirically at the scale it would have to run if it were deployed in the United States. Our results show that a decentralized and end-to-end encrypted national gun registry is not only possible in theory but feasible in practice.

Event date: 28 June to 1 July 2021
Submission deadline: 18 March 2021
Notification: 29 April 2021

The Services and Cybersecurity (SCS) group at the University of Twente invites applications for a 4-years PhD position on the topic of 'cryptographic protocols for privacy-preserving machine learning'.

We are looking for candidates with a strong background in (applied) cryptography.

More information:
https://www.utwente.nl/en/organisation/careers/!/2021-218/phd-position-on-cryptographic-protocols-for-privacy-preserving-machine-learning

Deadline for applications: 11 February 2021, 23:59 CET

Closing date for applications:

Contact: Prof. Dr. Andreas Peter (a.peter@utwente.nl)

More information: https://www.utwente.nl/en/organisation/careers/!/2021-218/phd-position-on-cryptographic-protocols-for-privacy-preserving-machine-learning

The IACR Test-of-Time Award is given annually for each one of the three IACR General Conferences (Eurocrypt, Crypto, and Asiacrypt). An award will be given at a conference for a paper which has had a lasting impact on the field and was published 15 years prior.

We welcome nominations for the 2021 award (for papers published in 2006) until Feb 20, 2021. The proceedings of these conferences can be found here:

• Asiacrypt 2006
• Crypto 2006
• Eurocrypt 2006

To submit your nomination please send an email to testoftime@iacr.org

More information about the IACR Test-of-Time awards can be found in iacr.org/testoftime/

The 2021 Selection Committee:

• Ueli Maurer (chair)
• Nigel Smart
• Francois-Xavier Standaert (Eurocrypt 2021 program co-chair)
• Chris Peikert (Crypto 2021 program co-chair)
• Mehdi Tibouchi (Asiacrypt 2021 program co-chair)

For security token adoption by financial institutions and industry players on the blockchain, there is a need for a secure asset management protocol that enables condential asset issuance and transfers by concealing from the public the transfer amounts and asset types, while on a public blockchain. Flexibly supporting arbitrary restrictions on financial transactions, only some of which need to be supported by zero-knowledge proofs. This paper proposes leveraging a hybrid design approach, by using zero-knowledge proofs, supported by restrictions enforced by trusted mediators. As part of our protocol, we also describe a novel transaction ordering mechanism that can support a flexible transaction workflow without putting any timing constraints on when the transactions should be generated by the users or processed by the network validators. This technique is likely to be of independent interest.

So far, most of the Identity-Based Encryption (IBE) schemes have been realized by employing bilinear pairings, lattices, trapdoor discrete logarithm, or based on the quadratic residue problem. Among the IBE schemes, only pairing-based methods seem to be practical. Previously published non-pairing-based schemes are generally inefficient in encryption, decryption, key generation, ciphertext size or key size. In this paper, we propose an IBE scheme based on a hybrid of Diffie-Hellman and RSA-like hardness assumption. The computational cost of the proposed scheme is lower than the previous schemes and the ciphertext size for an $l$-bit plaintext is only $2l$ bits. The proposed scheme is similar to the well-known ElGamal encryption algorithm; therefore it might be used in applications such as oblivious computation.

In this work, we are concerned with the hardening of post-quantum key encapsulation mechanisms (KEM) against side-channel attacks, with a focus on the comparison operation required for the Fujisaki-Okamoto (FO) transform. We identify critical vulnerabilities in two proposals for masked comparison and successfully attack the masked comparison algorithms from TCHES 2018 and TCHES 2020. To do so, we use first-order side-channel attacks and show that the advertised security properties do not hold. Additionally, we break the higher-order secured masked comparison from TCHES 2020 using a collision attack, which does not require side-channel information. To enable implementers to spot such flaws in the implementation or underlying algorithms, we propose a framework that is designed to test the re-encryption step of the FO transform for information leakage. Our framework relies on a specifically parametrized $t$-test and would have identified the previously mentioned flaws in the masked comparison. Our framework can be used to test both the comparison itself and the full decapsulation implementation.

ForkAE is a family of authenticated encryption (AE) schemes using a forkcipher as a building block. ForkAE was published in Asiacrypt'19 and is a second-round candidate in the NIST lightweight cryptography process. ForkAE comes in several modes of operation: SAEF, PAEF, and rPAEF. SAEF is optimized for authenticated encryption of short messages and processes the message blocks in a sequential and online manner. SAEF requires a smaller internal state than its parallel sibling PAEF and is better fitted for devices with smaller footprint. At SAC 2020 it was shown that SAEF is also an online nonce misuse-resistant AE (OAE) and hence offers enhanced security against adversaries that make blockwise adaptive encryption queries. It has remained an open question if SAEF resists attacks against blockwise adaptive decryption adversaries, or more generally when the decrypted plaintext is released before the verification (RUP).

RUP security is a particularly relevant security target for lightweight (LW) implementations of AE schemes on memory-constrained devices or devices with stringent real-time requirements. Surprisingly, very few NIST lightweight AEAD candidates come with any provable guarantees against RUP. In this work, we show that the SAEF mode of operation of the ForkAE family comes with integrity guarantees in the RUP setting. The RUP integrity (INT-RUP) property was defined by Andreeva et~al.~in Asiacrypt'14. Our INT-RUP proof is conducted using the coefficient H technique and it shows that, without any modifications, SAEF is INT-RUP secure up to the birthday bound, i.e., up to $2^{n/2}$ processed data blocks, where $n$ is the block size of the forkcipher. The implication of our work is that SAEF is indeed RUP secure in the sense that the release of unverified plaintexts will not impact its ciphertext integrity.

Universal Composability Summer Intern Beavercreek, Ohio Riverside Research’s Trusted and Resilient Systems research group is conducting cutting edge research in applying formal methods for system security analysis. This innovative research will help transform how we design and build high assurance, complex systems. We are seeking a motivated researcher (ideally in a PhD program) who has experience with the Universal Composability framework to join our team for the summer and help us tackle some interesting and challenging problems. The individual who fills this role will work with top researchers in secure system design and cryptography to explore the art of the possible in analyzing complex systems using Universal Composability. All positions with Riverside Research require U.S. citizenship. Job Duties: • Conduct literature reviews • Scope and define challenging research problems in the area of Universal Composability • Conduct research with a small, dynamic team • Publish results in a top security conference • Other duties as assigned Required Qualifications: • U.S. Citizenship • Enrolled in a degree seeking program (ideally PhD) in fields such as Computer Science, Computer Engineering, Electrical Engineering, Mathematics • Previous experience with Universal Composability • Ability to work independently and with a team • Superior written and verbal communications skills Desired Qualifications: • Previous publications using Universal Composability (especially if applied to systems beyond traditional cryptographic protocols) • Understanding of Open Architecture systems Riverside Research strives to be one of America's premier providers of independent, trusted technical and scientific expertise. We continue to add experienced and technically astute staff who are highly motivated to help our DoD and Intelligence Community (IC) customers deliver world class programs. As a not-for-profit, technology-oriented defense company, we believe service to customers and s

Closing date for applications:

Contact: Eileen Norton, Sr. Recruiter, Riverside Research, enorton@riversideresearch.org Dr. Michael Clark, Associate Director, Trusted and Resilient Systems, Riverside Research Open Innovation Center, IACR Member

More information: https://boards.greenhouse.io/riversideresearch/jobs/4347155003

The Zcash Foundation is a 501(c)(3) nonprofit, public charity that builds and supports privacy infrastructure for the public good. We work on strengthening financial privacy with technology, focused on the Zcash protocol and blockchain.

We’re looking for someone who is as excited as we are about building private financial infrastructure for the public good, and we take that task very seriously.

The role as a cryptography engineer within the core Zcash Foundation team will be responsible for building cryptographic protocols as well as distributed systems. The ideal candidate embodies the Foundation’s values, while fully aligning with its mission and goals.

Engineers at the Zcash Foundation are responsible for implementing the core Zcash protocol, maintaining deployed software, fixing bugs, and identifying improvements to the protocol for the future. Other duties include writing about our work and interfacing with external stakeholders such as those who use our software and interoperable implementations of the Zcash protocol. The position reports to the Zcash Foundation’s engineering manager.

Zcash Foundation Core Engineering Projects: Currently the engineering team is working on Zebra, an independent implementation of the Zcash protocol written in Rust, and soon we will dedicate resources to building out Zcash wallet functionality.

Closing date for applications:

Contact: Submit application here: https://docs.google.com/forms/d/e/1FAIpQLSelpDkmqjgVgiTfVFukB9TbIoIExWxVDHn0VvnSboO4nJIN1A/viewform

More information: https://www.zfnd.org/blog/open-position-cryptography-engineer/

The Cryptanalysis Taskforce at Nanyang Technological University in Singapore led by Prof. Jian Guo is seeking for candidates to fill 3 Post-doctoral Research Fellow (or Senior Research Fellows with more than 5 years post PhD research experience) positions on symmetric-key cryptography, including but not limited to the following sub-areas:

• tool aided cryptanalysis, such as MILP, CP, STP, and SAT
• machine learning aided cryptanalysis and designs
• privacy-preserving friendly symmetric-key designs
• quantum cryptanalysis
• theory and proof
• cryptanalysis against SHA-2, SHA-3, and AES

Established in 2014, the Cryptanalysis Taskforce is a group dedicated for cutting edge research in symmetric-key cryptography. Since then, the team has been active in both publications in and services for IACR. It has done quite some cryptanalysis work on various important targets such as SHA-3, AES, function graph, TBC designs etc, and continues its works in the areas mentioned above, with strong funding support from the university and government agencies in Singapore. We offer competitive salary package with extremely low tax, as well as excellent environment dedicating for research in Singapore. The contract will be initially for 1 year, and has the possibility to be extended. Candidates are expected to have proven record of publications in IACR conferences. Interested candidates are to send their CV and 2 reference letters to Jian Guo. Review of applicants will start immediately until the positions are filled. More information about the Cryptanalysis Taskforce research group can be found via http://team.crypto.sg

Closing date for applications:

Contact: Asst Prof. Jian Guo, guojian@ntu.edu.sg

More information: http://team.crypto.sg

Job Title Embedded Cryptography Expert- QUALCOMM (France) Post Date October 2020 Company - Division Qualcomm Technologies, Inc. - CDMA Technology Job Area Engineering - Security Location France – Sophia Antipolis Job Overview: In this position you will perform tasks like these: • Define HW crypto security requirements (Functional, Performance, Security level) • Define HW/SW partitioning to address next challenge in cryptography (PQC, Crypto Agility) • Define and architect Crypto HW IP blocks that contributes to the overall SoC Security ArchitectureArchitecture and design of state-of-the-art mechanisms thwarting physical attacks • Monitor evaluation of crypto IP resistance and robustness • Competitive analysis of security IPs and features • Investigate future/roadmap security related technologies • Participation to academic conference and industrial/research security working group

Closing date for applications:

Contact: avial@qti.qualcomm.com

More information: https://qualcomm.wd5.myworkdayjobs.com/External/job/Sophia-Antipolis/Crypto-Expert---Sophia-Antipolis--France_3004178

Advanced Encryption Standard used with Galois Counter Mode, mode of operation is one of the the most secure modes to use the AES. This paper represents an overview of the AES modes focusing the AES-GCM mode and its particularities. Moreover, after a detailed analysis of the possibility of enhancement for the encryption and authentication phase, a method of generating custom encryption schemes based on GF($2^8$) irreducible polynomials different from the standard polynomial used by the AES-GCM mode is provided. Besides the polynomial customization, the solution proposed in this paper offers the possibility to determine, for each polynomial, the constants that can be used in order to keep all the security properties of the algorithm. Using this customization method, allows changing the encryption schemes over a period of time without interfering with the process, bringing a major improvement from the security point of view by avoiding pattern creation. Furthermore, this paper sets the grounds for implementing authentication enhancement using a similar method to determine the polynomials that can be used instead of the default authentication polynomial, without changing the algorithm strength at all.

The progress on constructing quantum computers and the ongoing standardization of post-quantum cryptography (PQC) have led to the development and refinement of promising new digital signature schemes and key encapsulation mechanisms (KEM). Especially lattice-based schemes have gained some popularity in the research community, presumably due to acceptable key, ciphertext, and signature sizes as well as good performance results and cryptographic strength. However, in some practical applications like smart cards, it is also crucial to secure cryptographic implementations against side-channel and fault attacks. In this work, we analyze the so-called redundant number representation (RNR) that can be used to counter side-channel attacks. We show how to avoid security issues with the RNR due to unexpected de-randomization and we apply it to the Kyber KEM and show that the RNR has a very low overhead. We then verify the RNR methodology by practical experiments, using the non-specific t-test methodology and the ChipWhisperer platform. Furthermore, we present a novel countermeasure against fault attacks based on the Chinese remainder theorem (CRT). On an ARM Cortex-M4, our implementation of the RNR and fault countermeasure offers better performance than masking and redundant calculation. Our methods thus have the potential to expand the toolbox of a defender implementing lattice-based cryptography with protection against two common physical attacks.

Having shared access to high-quality random numbers is essential in many important applications. Yet, existing constructions of distributed random beacons still have limitations such as imperfect security guarantees, strong setup or network assumptions, or high costs. In this paper, we present SPURT, an efficient distributed randomness beacon protocol that does not require any trusted or expensive setup and is secure against a malicious adversary that controls up to one-third of the nodes in a partially synchronous network. We formally prove that each output of SPURT is unpredictable, bias-resistant, and publicly verifiable. SPURT has an amortized total communication cost of O(\lambda n^2) per beacon output in the fault-free case and O(\lambda n^2\log n + n^3) in the worst case. We implement SPURT and evaluate it using a network of up to 128 nodes running in geographically distributed AWS instances. Our evaluation shows that SPURT has practical computation and bandwidth costs and can produce beacon outputs every second for a network of 64 nodes, and every 3 seconds for a network of 128 nodes.

A major concern in training and releasing machine learning models is to what extent the model contains sensitive information that the data holders do not want to reveal. Property inference attacks consider an adversary who has access to the trained model and tries to extract some global statistics of the training data. In this work, we study property inference in scenarios where the adversary can maliciously control part of the training data (poisoning data) with the goal of increasing the leakage.

Previous work on poisoning attacks focused on trying to decrease the accuracy of models either on the whole population or on specific sub-populations or instances. Here, for the first time, we study poisoning attacks where the goal of the adversary is to increase the information leakage of the model. Our findings suggest that poisoning attacks can boost the information leakage significantly and should be considered as a stronger threat model in sensitive applications where some of the data sources may be malicious.

We first describe our property inference poisoning attack that allows the adversary to learn the prevalence in the training data of any property it chooses: it chooses the property to attack, then submits input data according to a poisoned distribution, and finally uses black box queries (label-only queries) on the trained model to determine the frequency of the chosen property. We theoretically prove that our attack can always succeed as long as the learning algorithm used has good generalization properties.

We then verify effectiveness of our attack by experimentally evaluating it on two datasets: a Census dataset and the Enron email dataset. In the first case we show that classifiers that recognizes whether an individual has high income (Census data) also leak information about the race and gender ratios of the underlying dataset. In the second case, we show classifiers trained to detect spam emails (Enron data) can also reveal the fraction of emails which show negative sentiment (according to a sentiment analysis algorithm); note that the sentiment is not a feature in the training dataset, but rather some feature that the adversary chooses and can be derived from the existing features (in this case the words). Finally, we add an additional feature to each dataset that is chosen at random, independent of the other features, and show that the classifiers can also be made to leak statistics about this feature; this shows that the attack can target features completely uncorrelated with the original training task. We were able to achieve above $90\%$ attack accuracy with $9-10\%$ poisoning in all of these experiments.