International Association
for Cryptologic Research

In this article, we propose a new public key cryptosystem, called \textbf{NAB}. The most important features of NAB are that its security strength is no easier than the security issues of the NTRU cryptosystem~\cite{Hoffstein96} and the encryption/decryption process is very fast compared to the previous public key cryptosystems RSA~\cite{Rivest78amethod}, Elgamal~\cite{ElGamal85}, NTRU~\cite{Hoffstein96}. Since the NTRU cryptosystem~\cite{Hoffstein96} is still not known to be breakable using quantum computers, NAB is also the same. In addition, the expansion of the ciphertext is barely greater than the plaintext and the ratio of the bit-size of the ciphertext to the bit-size of the plaintext can be reduced to just over one. We suggest that NAB is an alternative to RSA~\cite{Rivest78amethod}, Elgamal~\cite{ElGamal85} and NTRU~\cite{Hoffstein96} cryptosystems.

In many cases, machine learning and privacy are perceived to be at odds. Privacy concerns are especially relevant when the involved data are sensitive. This paper deals with the privacy-preserving inference of deep neural networks. We report on first experiments with a new library implementing a variant of the TFHE fully homomorphic encryption scheme. The underlying key technology is the programmable bootstrapping. It enables the homomorphic evaluation of any function of a ciphertext, with a controlled level of noise. Our results indicate for the first time that deep neural networks are now within the reach of fully homomorphic encryption. Importantly, in contrast to prior works, our framework does not necessitate re-training the model.

Until now, there are two different methods to compute 4-GLV decompositions on the elliptic curves over $\mathbb{F}_{p^2}$ which are quadratic twists and possess a “restricted” endomorphism $\psi$ satisfying $\psi^{2}+1=0$. They are Longa and Sica's twofold Cornacchia-type algorithm (ASIACRYPT 2012) and Benjamin Smith's method--ready-made short bases (AMS 2015). In this paper, we first extend Smith's method from the case of quadratic twists to the case of quartic or sextic twists and give ready-made short bases for 4-GLV decompositions on these high degree twisted curves. After our supplements, Smith's method can be used to compute 4-GLV decompositions on more elliptic curves. Secondly, we focus on exploring more potential of Longa and Sica's algorithm, which is an elaborate iterated Cornacchia algorithm that can compute short bases for 4-GLV decompositions. The algorithm consists of two sub-algorithms, the first one in the ring of integers $\mathbb{Z}$ and the second one in the Gaussian integer ring $\mathbb{Z}[i]$. We observe that $\Z[i]$ in the second sub-algorithm can be replaced by another Euclidean domain $\mathbb{Z}[\omega]$ $(\omega=\frac{-1+\sqrt{-3}}{2})$. As a consequence, we design a new twofold Cornacchia-type algorithm with a theoretic upper bound of output $C\cdot n^{1/4}$, where $C=\frac{3+\sqrt{3}}{2}\sqrt{1+|r|+|s|}$ with small values $r, s$ given by the curve. The new twofold algorithm can be used to compute $4$-GLV decompositions on two classes of curves. First it gives a new and unified method to compute all $4$-GLV decompositions on $j$-invariant $0$ elliptic curves over $\mathbb{F}_{p^2}$. We exploit the fact that this family of curves must have an endomorphism $\phi$ satisfying $\phi^{2}+\phi+1=0$ (and hence $\mathbb{Z}[\phi]=\mathbb{Z}[\omega]$). Of the two previous methods on this class of elliptic curves, the first one was proposed by Hu, Longa and Xu in 2012 (Designs, Codes and Cryptography) but is applicable only to curves which are twists of degree $6$ and possess a “restricted” endomorphism $\psi$ satisfying $\psi^{4}-\psi^{2}+1=0$, the second one follows from the the work of Longa and Sica (ASIACRYPT 2012) and is applicable only to curves with a “restricted” endomorphism $\psi$ satisfying $\psi^{2}+1=0$. Second it can be used to compute the $4$-GLV decomposition on the Jacobian of the hyperelliptic curve defined as $\mathcal{C}/\mathbb{F}_{p}:y^{2}=x^{6}+ax^{3}+b$, which has an endomorphism $\phi$ with the characteristic equation $\phi^2+\phi+1=0$ (hence $\Z[\phi]=\Z[\omega]$).

Many privacy-preserving protocols employ a primitive that allows a sender to "flag" a message to a recipient's public key, such that only the recipient (who possesses the corresponding secret key) can detect that the message is intended for their use. Examples of such protocols include anonymous messaging, privacy-preserving payments, and anonymous tracing. A limitation of the existing techniques is that recipients cannot easily outsource the detection of messages to a remote server, without revealing to the server the exact set of matching messages. In this work we propose a new class of cryptographic primitives called fuzzy message detection schemes. These schemes allow a recipient to derive a specialized message detection key that can identify correct messages, while also incorrectly identifying non-matching messages with a specific and chosen false positive rate $p$. This allows recipients to outsource detection work to an untrustworthy server, without revealing precisely which messages belong to the receiver. We show how to construct these schemes under a variety of assumptions; describe several applications of the new technique; and show that our schemes are efficient enough to use in real applications.

The hybrid argument is a fundamental and well-established proof technique of modern cryptography for showing the indistinguishability of distributions. As such, its details are often glossed over and phrases along the line of "this can be proven via a standard hybrid argument" are common in the cryptographic literature. Yet, the hybrid argument is not always as straightforward as we make it out to be, but instead comes with its share of intricacies. For example, a commonly stated variant says that if one has a sequence of hybrids $H_0,...,H_t$, and each pair $H_i$, $H_{i+1}$ is computationally indistinguishable, then so are the extreme hybrids $H_0$ and $H_t$. We iterate the fact that, in this form, the statement is only true for constant $t$, and we translate the common approach for general $t$ into a rigorous statement.

The paper here is not a research paper in the traditional sense. It mainly consists of an excerpt from the book "The Theory of Hash Functions and Random Oracles - An Approach to Modern Cryptography" (Information Security and Cryptography, Springer, 2021), providing a detailed discussion of the intricacies of the hybrid argument that we believe is of interest to the broader cryptographic community. The excerpt is reproduced with permission of Springer.

In this paper, we present ZEN, a toolchain for producing efficient zero-knowledge proof systems of privacy-preserving verifiable neural network models. Taking an existing neural network as an input, ZEN produces a verifiable computation scheme for a classification task or a recognition task, namely ZEN$_{class}$ and ZEN$_{rec}$. Both ZEN$_{class}$ and ZEN$_{rec}$ ensure the privacy, more precisely, the zero-knowledge property of the input data. In practice, this means removing the personal identifications, such as the facial image or other biometric data, from the attack surface. And thanks to three decades’ consecutive efforts on zkSNARK from our community, the entire process is non-interactive and verifiable. Thus, our schemes potentially enable many important applications, ranging from trustless oracles for decentralized ledgers to privacy-preserving facial identification systems. To our best knowledge, ZEN is the first zero-knowledge neural network scheme that preserves the privacy of input data while delivering verifiable outputs. To build efficient schemes with no additional accuracy loss, ZEN includes two major technical contributions. First, we propose a zkSNARK friendly quantization approach, which is semantically equivalent to the state-of-the-art quantization algorithm, yet brings significant savings in constraint size. Second, we propose a novel encoding scheme, namely stranded encoding, that encodes batched dot products, the workhorse of many matrix operations, using only a fraction of finite field elements. This brings sizable savings in terms of the number of constraints for the matrix operation circuits. Our end-to-end evaluation demonstrates the effectiveness of ZEN: compared with simply combining the state-of-the-art full quantization scheme with zkSNARK (ZEN-vanilla), ZEN has $3.68 \sim 20.99 \times$ ($14.14 \times$ on average) savings in the number of constraints (as a result, in prover time as well) thanks to our zkSNARK friendly quantization and stranded encoding.

Proof of Elapsed Time (PoET) is a Nakamoto-style consensus algorithm where proof of work is replaced by a wait time randomly generated by a trusted execution environment (TEE). PoET was originally developed by Intel engineers and contributed to Hyperledger Sawtooth, but has never been formally defined or analyzed. In particular, PoET enables consensus on a bitcoin-like scale without having to resort to mining. Proof of Luck (PoL), designed by Milutinovic et. al., is a similar (but not identical) protocol that also builds a Nakamoto-style consensus algorithm using a TEE. Like PoET, it also lacks a formal proof.

In this work, we formally define a simplified version of PoET and Proof of Luck, which we call elapsed time (ET) consensus with a trusted timer. We prove the security of our ET consensus protocol with a trusted gimer given an honest majority assumption in a model very similar to the bitcoin backbone model proposed by Garay et al. which we call the elapsed time backbone model. Our model and protocol aims to capture the essence of PoeT and PoL while ignoring some of the more practical difficulties associated with such protocols, such as bootstrapping and setting up the TEE.

The PoET protocol also contains a function called the $z$-test that limits the number of blocks a player can publish in any particular larger set of blocks. Surprisingly, by improving this $z$-test a little bit we can prove the security of our ET consensus protocol without any TEEs with a (slightly stronger) honest majority assumption. This implies that Nakamoto-style consensus with rate limiting and no proofs of work can be used to obtained scalable consensus in a permissioned setting: in other words, ``bitcoin without proofs of work'' can be made secure without a TEE for private blockchains!

In this paper, we present the complete analysis of Huff curves for implementing isogeny-based cryptography. In this regard, we first investigate the computational cost of the building-blocks when compression functions are used for Huff curves and presented an additional formula on Huff curves for implementing isogeny-based cryptography. From our implementation, the performance of Huff-SIDH and Montgomery-SIDH is almost the same, and Huff-CSIDH is 6.4\% faster than Montgomery-CSIDH but 4\% slower than Hybrid-CSIDH. The result of our work shows that the Huff curve can be quite practical for implementing isogeny-based cryptography but has some limitations.

In this paper, we present two new perturbations for the design of multivariate schemes that we call ``Ariadne Thread'' and ``Salt''. From these ideas, we present some efficient multivariate encryption and signature schemes with explicit parameters that resist all known attacks. In particular they resist the two main (and often very powerful) attacks in this area: the Gröbner attacks (to compute a cleartext from a ciphertext) and the MinRank attacks (to recover the secret key). Ariadne Threat and Salt can also be seen as new ``perturbations'' that we can use to enforce many multivariate schemes. The ``Salt'' perturbation works only for public key equations of degree (at least) 3. Similarly at present the ``Ariadne Thread'' perturbation seems to be particularly powerful with public keys of degree 3. Despite this, the size of the public key may still be reasonable since we can use larger fields (and also maybe non dense equations). Ariadne Thread perturbation seems to be particularly interesting for encryption. This is unusual since in multivariate cryptography encryption is generally more difficult than signatures.

In this paper, we computationally analyze Passkey Entry in its entirety as a cryptographic authenticated key exchange (AKE) - including user-protocol interactions that are typically ignored as out-of-band. To achieve this, we model the user-to-device channels, as well as the typical device-to-device channel, and adversarial control scenarios in both cases. In particular, we separately capture adversarial control of device displays on the initiating and responding devices as well as adversarial control of user input mechanisms using what we call a CYBORG model. The CYBORG model enables realistic real-world security analysis in light of published attacks on user-mediated protocols such as Bluetooth that leverage malware and device displays. In light of this, we show that all versions of Passkey Entry fail to provide security in our model. Finally, we demonstrate how slight modications to the protocol would allow it to achieve stronger security guarantees for all current variants of passkey generation, as well as a newly proposed twofold mode of generation we term Dual Passkey Entry. These proof-of-concept modications point to improved design approaches for user-mediated protocols. Finally, this work points to categories of vulnerabilities, based on compromise type, that could be exploited in Bluetooth Passkey Entry.

Secure Multiparty Computation involves a protocol between parties with an aim to produce a computed result just as a Trust Party would produce if the parties provided their inputs to it. The Trusted party in conventional computation is replaced by "un-trusted" parties in Secure Multiparty Computation. We first show that this existing Binary definition of Trust is inadequate. Real world is rife with disparities, that which produce a perceivable trust gradient between the participants. Conventional MPC models do not take this into account and rather provide security guarantees based on the threshold of corrupted parties. The thresholds are supposed to cover for some of the parties turning out to be corrupt. Often, with the knowledge of \emph{prior probability} of a party being corrupt, we can do better if we allot weight to each party based on how trusted we perceive it to be. Our paper explores this idea and our contributions towards it are two folds. First, we introduce the Graded Trust model where each party essentially has a \emph{Trust Grade} assigned to it in the protocol based on the prior of it being corrupt. Then, we present a discussion on the philosophy behind graded trust, and the potential benefits for large scale public MPC systems.

The concept of private stream aggregation (PSA) has been proposed by Shi et al. (NDSS 2011) to allow for data analysis in a privacy-preserving manner. In this work, we introduce the notion of labeled secret sharing (LaSS) schemes and show how to use it to construct PSA schemes. We also show how to realize LaSS using pseudorandom functions or alternatively with a hash function modeled as a random oracle and how it can be used to construct PSA schemes. Additionally, we revisit the security model of Becker et al. (NDSS 2018) and describe stronger security notions for PSA. We then present additional constructions achieving the stronger security notions by relying on recent results on multi-client functional encryption. For all of our constructions, we present implementations to show their practicality and the performance gains over existing solutions.

We are looking for an assistant/associate professor to extend and complement the cryptology research and teaching of the Cyber Security Section at DTU Compute. The position is available from August 1 2021 or according to mutual agreement.

Closing date for applications:

Contact: Professor Lars Ramkilde Knudsen, lrkn@dtu.dk. Please use the above link when applying for the position. Applications sent by email will not be considered.

More information: https://www.dtu.dk/english/about/job-and-career/vacant-positions/job?id=dd355396-a1f7-4960-8e94-af0f50a374dc

Event date: 23 January 2021

Ph.D. positions are available in the Cryptology and Data Security research group at the Institute of Computer Science, University of Bern, led by Christian Cachin.

Our research addresses all aspects of security in distributed systems, especially cryptographic protocols, consistency, consensus, and cloud-computing security. We are particularly interested in blockchains, distributed ledger technology, cryptocurrencies, and their security and economics.

Candidates should have a strong background in computer science. They should like conceptual, rigorous thinking for working theoretically, or be interested in building innovative systems for working practically. Demonstrated expertise in cryptography, distributed computing, or blockchain technology is a plus. Applicants must hold a master degree in the relevant research fields.

Positions are available immediately and come with a competitive salary. The selection process runs until suitable candidates have been found. The University of Bern conducts excellent research and lives up its vision that “Knowledge generates value”. The city of Bern lies in the center of Switzerland and offers some of the highest quality of life worldwide.

If you are interested, please apply be sending email with one single PDF file and subject line set to Application for Ph.D., addressed directly to Prof. Christian Cachin at crypto (at) inf.unibe.ch.

Since we receive many applications, we encourage you to include material that demonstrates your interests and strengths and sets you apart from others.

For more information, please contact Christian Cachin (https://crypto.unibe.ch/cc/).

Closing date for applications:

Contact: Christian Cachin < crypto (at) inf.unibe.ch >

More information: https://crypto.unibe.ch/

Join the vibrant security and applied crypto research group in Brno, Czechia! Join the research team that won the 2016 USENIX Security Symposium Best Paper Award, 2017 ACM CCS Real-World Impact Award, or 2020 CHES Best Paper Award. The team that helped hundreds of graduates in the security Master programs, has been involved in both fundamental and applied crypto/security/privacy research projects and industry partnerships.

The Dean of the Faculty of Informatics, Masaryk University, invites applications for one position of Assistant Professor in Cybersecurity, with the Department of Computer Systems and Communications.

Applications due: February 28, 2021
Employment start date: By mutual agreement

This position is aimed to strengthen the work of the Centre for Research on Cryptography and Security (CRoCS - https://crocs.fi.muni.cz/) at the Faculty of Informatics. CRoCS works to improve security and privacy of real-world solutions through applied research (often in cooperation with industry) and advanced education of future security professionals. System security or network security focus are most desired, yet the abilities to work with a team of graduate students and faculty on research targeting top security/crypto conferences and to engage both undergraduate and graduate students in both educational and research exercises are most critical.

Job description keypoints:

• Active international cooperation, in both research and education.
• Involvement in teaching in the cybersecurity area.
• Supervision of Master/Bachelor theses and consultancy or co-supervision of PhDs.
• Involvement in expanding industrial cooperation in the cybersecurity area.
• Expert knowledge in at least one of the areas covered by courses:
  • PV181 Laboratory of security and applied cryptography {https://is.muni.cz/course/fi/podzim2019/PV181};
  • PA193 Secure coding principles and practices {https://is.muni.cz/course/fi/podzim2019/PA193}.
  • PA197 Secure Network Design {https://is.muni.cz/course/fi/jaro2020/PA197}.

Closing date for applications:

Contact: Vashek Matyas

More information: https://www.muni.cz/en/about-us/careers/vacancies/59434

The AWS Cryptography Group is looking for an Applied Scientist with knowledge of cryptographic computing technologies such as privacy preserving machine learning, fully and partially homomorphic encryption, secure multiparty computation, private information retrieval, and related technologies. You will use this knowledge to conceptualize how this technology can be integrated into internal infrastructure and public AWS services, develop prototypes, and provide customers with world-class security. The ideal candidate will have a strong understanding of cryptography, the ability to prototype solutions, and a passion to realize these technologies in AWS products and services. We encourage research and publication of results that apply to our customers most complex initiatives.

We are seeking a candidates who are innovative, look for new ideas everywhere, and are not limited by “not invented here”. They should think big, and have bold ideas for new ways to serve customers.

BASIC QUALIFICATIONS

• PhD in Computer Science or a closely related field
• Expert knowledge of cryptography and, in particular, cryptographic-computing techniques (homomorphic encryption, secure multiparty computation, etc.)
• Practical knowledge in one or more common development languages (C/C++, Java, Go, Rust, Python, etc.)
• Good written and verbal communication skills.

PREFERRED QUALIFICATIONS

• Basic knowledge of machine learning
• 5+ years of industry experience

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Closing date for applications:

Contact: Bill Horne

More information: https://amazon.jobs/en/internal/jobs/1397391/applied-cryptographer

Our Statistics and Privacy team focuses on establishing step-change improvements to advance our long-term business growth. The team's expertise spans many domains including statistics, machine learning and cryptography. We develop methodologies, design and prototype solutions, and partner with our engineering colleagues to launch these solutions such that millions of advertisers can benefit. Examples include internal and external experimentation platforms, ads delivery optimization for efficient causal outcomes, and the application of privacy enhancing technologies across our ads product stack.

We are looking for research interns to join our teams to drive forward new prototypes and methodologies. Interns will pursue novel applied research associated with privacy preserving machine learning, cryptography and internet technology, or causal inference and experimentation platforms. This work is critical to our long-term product development, and we expect interns to provide both scientific expertise and creative solutions to accelerate their project area.

Responsibilities

Assess potential opportunities and execute world-class research associated with your area of scientific expertise

Write high quality academic papers to advocate the research and innovations

Establish approaches to rigorously assess relative performance of new technologies or strategies

Learn new tools, systems and languages quickly as required by the particular project you are working on

Apply communication skills to engage diverse audiences on technical topics and nuanced insights

Minimum Qualifications

Currently has, or is in the process of obtaining, a PhD degree in statistics, computer science, electrical engineering, physics, quantitative social science, or a related quantitative field

Expertise in one of the following areas: privacy preserving machine learning, cryptography and internet technology, or causal inference and experimentation platforms

continued on application webpage, see https://www.facebook.com/careers/v2/jobs/270789727484557/

Closing date for applications:

Contact: Apply Online or reach out to Benjamin Case (bmcase {at} fb DOT com) or Sanjay Saravanan

More information: https://www.facebook.com/careers/v2/jobs/270789727484557/

The Institute of Applied Information Processing and Communications (aka IAIK) is the largest university institute in Austria for research and education in security and privacy. It has been active in this field for more than 30 years and currently employs more than 60 researchers. Within the "Secure Systems" area of our institute Sujoy Sinha Roy is establishing the new research group "Cryptographic Engineering”.

In order to complement our team, we are looking for a fulltime post-doctoral researcher:

Responsibilities:
The post-doctoral researcher will be working on the hardware acceleration of homomorphic encryption within the “Cyroptografic Engineering” group within the “Secure Systems” area at IAIK.

Required Qualifications:

A PhD (or close to completion) in computer science, information and computer engineering, software development, mathematics, or a related field.

Publications in top conferences, or submitted/accepted papers in top journals.

Experience with cryptography, programming, and digital circuit design (ASIC or FPGA) design

How to apply:
Applications, curriculum vitae and other documents should preferably be uploaded here https://free.formcloud.de/formcycle/form/provide/7780/. Please select 7050/postdoc_2021 as a reference number.

The position is full time - 40 h per week and the employment duration is set for 18 months. Prefered starting date early 2021. The application deadline is February 15th 2021.

Closing date for applications:

Contact: Sujoy Sinha Roy – sujoy.sinharoy@iaik.tugraz.at

Chosen ciphertext security for lattice based encryption schemes is generally achieved through a generic transformation such as the Fujisaki-Okamoto transformation. This method requires full re-encryption of the plaintext during decapsulation, which typically dominates the cost of the latter procedure. In this work we show that it is possible to develop alternative transformations specifically designed for lattice based encryption schemes. We propose two novel chosen ciphertext transformations, $\mathtt{ETC1}$ and $\mathtt{ETC2}$, in which re-encryption is replaced by checking the error term of the input ciphertext. We show that our new ciphertext validity check can be securely applied to lattice based encryption schemes under specific conditions. For the NIST post-quantum standardization candidate Threebears we show a speed-up for decapsulation of up to $37.4\%$. Moreover, as our method only changes the validation check during decapsulation, it is fully backwards compatible with existing implementations of the Fujisaki-Okamoto transformation.