International Association
for Cryptologic Research

Research Internships at Microsoft provide a dynamic environment for research careers with a network of world-class research labs led by globally-recognized scientists and engineers. Our researchers and engineers pursue innovation in a range of scientific and technical disciplines to help solve complex challenges in diverse fields, including computing, healthcare, economics, and the environment.

The Cryptography and Privacy Research Group is hiring interns for the summer of 2022. We are seeking strong candidates to work with our renowned researchers on various topics. We are particularly interested in privacy-preserving ML, privacy and transparency techniques for digital identity systems and public key infrastructures, account/identity/password recovery, and web privacy/security, including fraud detection and prevention. We encourage all PhD students with relevant technical background in any of these topics to apply as soon as possible, as we will start interviewing immediately.

For summer internships, we typically work closely with Microsoft product groups (Teams, Edge, to name a few) to bring research ideas to real life. The internships often involve prototyping the research results, so a strong candidate is expected to have some proficiency in programming and interest in working alongside our engineers.

More information and application at https://careers.microsoft.com/us/en/job/1195145/Research-Intern-Privacy-and-Cryptography

Closing date for applications:

Contact: Kim Laine (kim.laine@microsoft.com)

We have a fully funded position to pursue a PhD (or join us as a postdoc) as part of our French-German project Propolis on Smart City Privacy, in a consortium with Eurecom, SAP, and The Urban Institute: https://propolis-project.eu/ . We will primarily work on publishing location trajectories with DP guarantees and differentially private ML on location data (for instance for traffic management, public security, and risk management in smart cities).

We can hire MSc graduates from CS, math and related fields who would like to pursue a PhD, or PostDocs to prepare them for academic/industry careers -- or to keep them with us for a while (including co-supervision of MSc/PhD students, if applicable). We are and will remain a small, international, diverse team with close interaction. Good command of the English language is necessary (no German needed), and we recruit based on qualification and commitment. We focus on positive working environments and the quality of results.

Closing date for applications:

Contact: Thorsten Strufe and Javier Parra-Arnau

More information: https://ps.tm.kit.edu/english/200.php

Four fully funded positions to do a PhD or Post-Doc (co-supervision of PhD students, in case of interest) on 6G security and privacy (location privacy, availability, security architectures, practical quantum key generation) at KIT/KASTEL and Excellence Cluster CeTI.

Closing date for applications:

Contact: Thorsten Strufe

More information: https://ps.tm.kit.edu/english/200.php

Event date: to
Submission deadline: 21 March 2022
Notification: 6 June 2022

In a fast changing world, it takes pioneering spirit to create trustworthy technology. We enable secure connectivity and payment solutions for billions of people around the globe. At G+D Mobile Security, you will play a key role in realizing the digital transformation.

G+D Mobile Security is looking for a Cryptography Engineer (m/f/d) for its Cryptology department at its Munich Headquarters as soon as possible

Job description:

• Secure implementation of cryptographic algorithms and security relevant OS components for smart cards in assembler
• Optimization regarding run time and memory consumption
• Design and implementation of countermeasures to defend against hardware related attacks against smart cards
• Analysis of the results of side-channel attacks and derivation of effective countermeasures

Your Profile:

• Background in mathematics, computer science or electronic engineering
• Ideally PhD in cryptography or 3+ years experience in cryptography or related area
• Programming skills in assembler for 8/16/32 bit embedded microcontrollers
• Ideally experience in embedded security and side-channel-attacks

Your benefits:

• High level of responsibility and exciting projects
• Working in an international security technology company
• Very flexible working hours and home office possibilities
• Wide range of training and further education opportunities
• Attractive family benefits such as a summer holiday camp for children
• Other benefits such as an own sports club and a canteen subsidized by the employer

We are looking forward to receiving your application!

https://careers.gi-de.com/job/Munich-Kryptologen-%28mfd%29-81677/723297801/

Closing date for applications:

Contact: Dr. Harald Vater (Harald.Vater (at) gi-de.com)

The candidate will investigate the utilisation of emerging variants of blockchains, such as redactable directed acyclic graph (DAG) based blockchain, as well as proof-of-location techniques for securing IoT and wireless devices. The candidate will work under a supervisory team with high expertise in IoT, wireless networks and protocols from, blockchain and information security, including Dr Djamel Djenouri and Dr Essam Ghadafi. For an informal discussion about the studentship, please email Dr Djamel Djenouri (Djamel.Djenouri@uwe.ac.uk) or Dr Essam Ghadafi (Essam.Ghadafi@uwe.ac.uk).

Closing date for applications:

Contact: Essam Ghadafi (Essam.Ghadafi@uwe.ac.uk)

More information: https://www.uwe.ac.uk/research/postgraduate-research-study/how-to-apply/studentship-opportunities/iot-over-wireless-networks

The CISPA Helmholtz Center for Information Security provides a unique work environment that offers the advantages of a university department and a research laboratory alike. As the latest member of the Helmholtz Association, the largest research organization in Germany, CISPA has embarked on a mission: to rethink the digitalized world of the future from the ground up and make it safer through innovative cutting-edge research. In the medium term, the center will grow to more than 800 employees with 60 Faculty and research group leaders. Faculty receive extremely competitive institutional funding, enjoy academic freedom, and build and lead their team of young researchers, and are granted the opportunity to teach graduate and undergraduate courses.

CISPA is located in Saarbrücken, in the tri-border area of Germany, France, and Luxembourg. We maintain an international and diverse work environment and seek applications from outstanding researchers worldwide. The working language is English. A command of German is not required for a successful career at CISPA.

CISPA is looking for candidates that hold a doctoral degree in computer science or related areas and have an outstanding research track record in all areas related to IT-Security, Privacy and Cryptography, especially in, but not limited to the fields of

software security,

security of critical infrastructure,

embedded systems,

network and distributed system (incl. blockchains) security,

hardware security,

privacy-enhancing technologies,

usable security and privacy,

applied cryptography,

quantum cryptography,

cryptanalysis.

All applicants are expected to build up a research team that pursues an internationally visible research agenda.

Tenure-track positions are intended for candidates with excellent research credentials and the potential to pursue a program of innovative research. The positions are comparable to tenure-track positions at a leading university, and come with two full time research staff positions and generous support for other expenses.

Closing date for applications:

Contact: scientific-recruiting@cispa.saarland

More information: https://jobs.cispa.saarland/jobs/detail/tenure-track-faculty-positions-in-all-areas-related-to-it-security-privacy-and-cryptography-f-m-d-129

Secure inference allows a server holding a machine learning (ML) inference algorithm with private weights, and a client with a private input, to obtain the output of the inference algorithm, without revealing their respective private inputs to one another. While this problem has received plenty of attention, existing systems are not applicable to a large class of ML algorithms (such as in the domain of Natural Language Processing) that perform featurization as their first step. In this work, we address this gap and make the following contributions:

1. We initiate the formal study of secure featurization and its use in conjunction with secure inference protocols. 2. We build secure featurization protocols in the one/two/three-server settings that provide a tradeoff between security and efficiency. 3. Finally, we apply our algorithms in the context of secure phishing detection and evaluate our end-to-end protocol on models that are commonly used for phishing detection.

Large-scale quantum computers will be able to efficiently solve the underlying mathematical problems of widely deployed public key cryptosystems in the near future. This threat has sparked increased interest in the field of Post-Quantum Cryptography (PQC) and standardization bodies like NIST, IETF, and ETSI are in the process of standardizing PQC schemes as a new generation of cryptography. This raises the question of how to ensure a fast, reliable, and secure transition to upcoming PQC standards in today’s highly interconnected world.

In this work, we propose and investigate a migration strategy towards post-quantum (PQ) authentication for the network protocol Transport Layer Security (TLS). Our strategy is based on the concept of “mixed certificate chains” which use different signature algorithms within the same certificate chain. In order to demonstrate the feasibility of our migration strategy we combine the well-studied and trusted hash-based signature schemes SPHINCS+ and XMSS with elliptic curve cryptography first and subsequently with lattice-based PQC signature schemes (CRYSTALS-Dilithium and Falcon). Furthermore, we combine authentication based on mixed certificate chains with the lattice-based key encapsulation mechanism (KEM) CRYSTALS-Kyber as representative for PQC KEMs to evaluate a fully post-quantum and mutually authenticated TLS 1.3 handshake.

Our results show that mixed certificate chains containing hash-based signature schemes only at the root certificate authority level lead to feasible connection establishment times despite the increase in communication size. By analyzing code size and peak memory usage of our client and server programs we further demonstrate the suitability of our migration strategy even for embedded devices.

This paper continues author's previous ones about compression of points on elliptic curves $E_b\!: y^2 = x^3 + b$ (with $j$-invariant $0$) over a finite field $\mathbb{F}_{\!q}$. More precisely, we show in detail how any two (resp. three) points from $E_b(\mathbb{F}_{\!q})$ can be quickly compressed to two (resp. three) elements of $\mathbb{F}_{\!q}$ (apart from a few auxiliary bits) in such a way that the corresponding decompression stage requires to extract only one cubic (resp. sextic) root in $\mathbb{F}_{\!q}$ (with several multiplications and without inversions). As a result, for many $q$ occurring in practice the new compression-decompression methods are more efficient than the classical one with the two (resp. three) $x$ or $y$ coordinates of the points, which extracts two (resp. three) roots in $\mathbb{F}_{\!q}$. We explain why the new methods are useful in the context of modern real-world pairing-based protocols. As a by-product, when $q \equiv 2 \ (\mathrm{mod} \ 3)$ (in particular, $E_b$ is supersingular), we obtain a two-dimensional analogue of Boneh--Franklin's encoding, that is a way to sample two \grqq independent'' $\mathbb{F}_{\!q}$-points on $E_b$ at the cost of one cubic root in $\mathbb{F}_{\!q}$. Finally, we comment on the case of four and more points from $E_b(\mathbb{F}_{\!q})$.

Payment channels (PC) are a promising solution to the scalability issue of cryptocurrencies, allowing users to perform the bulk of the transactions off-chain without needing to post everything on the blockchain. Many PC proposals however, suffer from a severe limitation: Both parties need to constantly monitor the blockchain to ensure that the other party did not post an outdated transaction. If this event happens, the honest party needs to react promptly and engage in a punishment procedure. This means that prolonged absence periods (e.g., due to a power outage) may be exploited by malicious users. As a mitigation, the community has introduced watchtowers, a third-party monitoring the blockchain on behalf of off-line users. Unfortunately, watchtowers are either trusted, which is critical from a security perspective, or they have to lock a certain amount of coins, called collateral, for each monitored PC in order to be held accountable, which is financially infeasible for a large network.

We present Sleepy Channels, the first bi-directional PC protocol without watchtowers (or any other third party) that supports an unbounded number of payments and does not require parties to be persistently online. The key idea is to confine the period in which PC updates can be validated on-chain to a short, pre-determined time window, which is where the PC parties have to be online. This behavior is incentivized by letting the parties lock a collateral in the PC, which can be adjusted depending on their mutual trust and which they get back much sooner if they are online during this time window. Our protocol is compatible with any blockchain that is capable of verifying digital signatures (e.g., Bitcoin), as shown by our proof of concept. Moreover, Sleepy Channels impose a communication and computation overhead similar to state-of-the-art PC protocols while removing watchtower's collateral and fees for the monitoring service.

We present a novel full hardware implementation of Streamlined NTRU Prime, with two variants: A high-speed, high-area implementation, and a slower, low-area implementation. We introduce several new techniques that improve performance, including a batch inversion for key generation, a high-speed schoolbook polynomial multiplier, an NTT polynomial multiplier combined with a CRT map, a new DSP-free modular reduction method, a high-speed radix sorting module, and new en- and decoders. With the high-speed design, we achieve the to-date fastest speeds for Streamlined NTRU Prime, with speeds of 5007, 10989 and 64026 cycles for encapsulation, decapsulation, and key generation respectively, while running at 285 MHz on a Xilinx Zynq Ultrascale+. The entire design uses 40060 LUT, 26384 flip-flops, 36.5 Bram and 31 DSP.

Due to the popularity of blockchain-based cryptocurrencies, the increasing digitalization of payments, and the constantly reducing role of cash in society, central banks have shown an increased interest in deploying central bank digital currencies (CBDCs) that could serve as a replacement of cash. While most recent research on CBDCs focuses on blockchain technology, it is not clear that this choice of technology provides the optimal solution. In particular, the centralized trust model of a CBDC offers opportunities for different designs. In this paper, we depart from blockchain designs and instead build on ideas from traditional e-cash schemes. We propose a new style of building digital currencies that combines the transaction processing model of e-cash with the account model of managing funds that is commonly used in blockchain solutions. We argue that such a style of building digital currencies is especially well-suited to CBDCs. We also design the first such digital currency system, called Platypus, that provides strong privacy, massive scalability, and expressive but simple regulation, which are all critical features for a CBDC. Platypus achieves these properties by adapting techniques similar to those used in anonymous blockchain cryptocurrencies like Zcash and applying them to the e-cash context.

Functional encryption (FE) is an advanced topic in the research of cryptography, and the Agr17 FE scheme is one of the major FE schemes. It took the BGG+14 attribute-based encryption (ABE) scheme as a bottom structure, which was upgraded into a `partially hiding predicate encryption' (PHPE) scheme and combined with a fully homomorphic encryption (FHE) scheme. However, there is a remaining problem, the implementation of the modulus reduction, in the Agr17 FE scheme. First, a modulus reduction is necessary for the polynomial-time computability of the scheme. Second, the detailed steps of the modulus reduction were absent in the scheme (including its conference version and full version). Instead, the authors only pointed out several reference works. The author's meaning seemed to be that the modulus reduction of the Agr17 FE scheme can be obtained by directly using or simply generalizing these reference works. Third, these reference works only described various modulus reductions of FHE schemes, without the hint of how to generalize them into the modulus reduction of FE schemes. Finally, any modulus reduction of FHE can not be simply generalized into the modulus reduction of the Agr17 FE scheme due to the following two facts: (1) The Agr17 FE scheme has two moduli, which are the modulus of the FHE ciphertext and of the ABE ciphertext, both are originally superpolynomial in size for processing $P/poly$ functions. (2) Both moduli need to be scaled down to polynomial size, and both of them need to be reduced to the same new modulus, otherwise, the correctness of the scheme will fail.

In this paper, we demonstrate that the Agr17 FE scheme is $P/poly$ invalid. More specifically, we show that, when processing $P/poly$ functions, the Agr17 FE scheme cannot be implemented again after its modulus reduction. To show the soundness of our demonstration, we present the statements in two stages. At the first stage, we show that the modulus reduction of the Agr17 FE scheme should be a double modulus reduction, which includes two modulus reductions for the FHE ciphertext and ABE ciphertext, respectively. This double modulus reduction has the following three key points: (1) The modulus reduction for the FHE ciphertext should be seen as a series of Boolean operations, and converted into `attribute quasi-homomorphic operations'. (2) The modulus reduction for the ABE ciphertext is a learning-with-errors (LWE) -based modulus reduction, which is an ordinary modulus reduction. (3) The two modulus reductions should obtain the same new modulus, otherwise, the scheme would not be implemented again. At the second stage, we show that the modulus reduction for the ABE ciphertext will destroy the structure of ABE so that the subsequent decryption would not be executed. The reason lies in that the decryption of ABE is an LWE decryption with conditions rather than an ordinary LWE decryption, and the modulus reduction will destroy the conditions of decryption. Besides, to show such invalidity cannot be easily crossed by revising the scheme, we design a `natural' revised version of the Agr17 scheme. The key point is to change the small modulus inner product into an arithmetic inner product, which can be obtained by the modulus inner product of the ABE ciphertext. The revised scheme is valid, i.e., the decryption can be implemented correctly. However, the revised scheme is insecure because the decryptor knows much more secret information, and hence the scheme can be broken by collusion attacks with much less cost.

On modern processors HCTR is one of the most efficient constructions for building a tweakable super-pseudorandom permutation. However, a bug in the specification and another in Chakraborty and Nandi's security proof invalidate the claimed security bound. We here present HCTR2, which fixes these issues and improves the security bound, performance and flexibility. GitHub: https://github.com/google/hctr2

Circuit-based Private Set Intersection (circuit-PSI) enables two parties with input set $X$ and $Y$ to compute a function $f$ over the intersection set $X \cap Y$, without revealing any other information. State-of-the-art protocols for circuit-PSI commonly involves a procedure that securely checks whether two input strings are equal and outputs an additive share of the equality result. More importantly, this procedure occupies the largest portion, roughly $90\%$ computational or communication cost for circuit-PSI. In this work, we propose {\textit{equality preserving compression}} (EPC) protocol that compresses the length of equality check targets while preserving equality using homomorphic encryption (HE) scheme, which is secure against the semi-honest adversary. We then apply our EPC protocol to previous circuit-PSI protocols framework and implement them. As a result, we achieve around 2x improvement on both communication and computational cost {\emph{at one stroke}} than previous results.

ZUC-256 is a stream cipher, together with AES-256 and SNOW-V, proposed as the core primitive in future set of 3GPP confidentiality and integrity algorithms for the upcoming 5G applications which offer the 256-bit security. \\ While the original initialization scheme of ZUC-256 can work with a 256-bit key and an IV of length up to 184 bits, we describe a new initialization scheme of ZUC-256 that supports an IV of the exact 128 bits in this paper. Compared to the original initialization scheme, this new key/IV setup algorithm avoids the division of the whole key/IV byte and provides a simple and natural-looking initialization scheme for ZUC-256.

Recent private information retrieval (PIR) schemes preprocess the database with a query-independent offline phase in order to achieve sublinear computation during a query-specific online phase. These offline/online protocols expand the set of applications that can profitably use PIR, but they make a critical assumption: that the database is immutable. In the presence of changes such as additions, deletions, or updates, existing schemes must preprocess the database from scratch, wasting prior effort. To address this, we introduce incremental preprocessing for offline/online PIR schemes, allowing the original preprocessing to continue to be used after database changes, while incurring an update cost proportional to the number of changes rather than the size of the database. We adapt two offline/online PIR schemes to use incremental preprocessing and show how it significantly improves the throughput and reduces the latency of applications where the database changes over time.

Intellectual Property (IP) thefts of trained machine learning (ML) models through side-channel attacks on inference engines are becoming a major threat. Indeed, several recent works have shown reverse engineering of the model internals using such attacks, but the research on building defenses is largely unexplored. There is a critical need to efficiently and securely transform those defenses from cryptography such as masking to ML frameworks. Existing works, however, revealed that a straightforward adaptation of such defenses either provides partial security or leads to high area overheads. To address those limitations, this work proposes a fundamentally new direction to construct neural networks that are inherently more compatible with masking. The key idea is to use modular arithmetic in neural networks and then efficiently realize masking, in either Boolean or arithmetic fashion, depending on the type of neural network layers. We demonstrate our approach on the edge-computing friendly binarized neural networks (BNN) and show how to modify the training and inference of such a network to work with modular arithmetic without sacrificing accuracy. We then design novel masking gadgets using Domain-Oriented Masking (DOM) to efficiently mask the unique operations of ML such as the activation function and the output layer classification, and we prove their security in the glitch-extended probing model. Finally, we implement fully masked neural networks on an FPGA, quantify that they can achieve a similar latency while reducing the FF and LUT costs over the state-of-the-art protected implementations by 34.2% and 42.6%, respectively, and demonstrate their first-order side-channel security with up to 1M traces.

This paper introduces Otti, a general-purpose compiler for SNARKs that provides language-level support for numerical optimization problems. Otti produces efficient arithmetizations of programs that contain optimization problems including linear programming (LP), semi-definite programming (SDP), and a broad class of stochastic gradient descent (SGD) instances. Numerical optimization is a fundamental algorithmic building block: applications include scheduling and resource allocation tasks, approximations to NP-hard problems, and training of neural networks. Otti takes as input arbitrary programs written in a subset of C that contain optimization problems specified via an easy-to-use API. Otti then automatically produces rank-1 constraints satisfiability (R1CS) instances that express a succinct transformation of those pro- grams whose correct execution implies the optimality of the solution to the original optimization problem. Our experimental evaluation on real numerical solver benchmarks used by commercial LP, SDP, and SGD solvers shows that Otti, instantiated with the Spartan proof system, can prove the optimality of solutions in as little as 300 ms---over 4 orders of magnitude faster than existing approaches.