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We implement the Grain-128AEAD stream cipher in hardware, using a 65 nm library. By exploring different optimization techniques, both at RTL level but also during synthesis, we first target high throughput, then low power. We reach over 33 GB/s targeting a high-speed design, at expense of power and area. We also show that, when targeting low power, the design only requires 0.23 $${\upmu }$$W runni
While biometric authentication for commercial use so far mainly has been used for local device unlock use cases, there are great opportunities for using it also for central authentication such as for remote login. However, many current biometric sensors like for instance mobile fingerprint sensors have too large false acceptance rate (FAR) not allowing them, for security reasons, to be used in lar
In this paper we are proposing a new member in the SNOW family of stream ciphers, called SNOW-V. The motivation is to meet an industry demand of very high speed encryption in a virtualized environment, something that can be expected to be relevant in a future 5G mobile communication system. We are revising the SNOW 3G architecture to be competitive in such a pure software environment, making use o
We improve iterative decoding of the moderate density parity-check codes, recently suggested as code candidates in the McEliece public key cryptosystem. In case of bit-flipping (BF) decoder failure, the code parity-check matrix is extended by adding auxiliary variable nodes based on reliability information from the BF decoder. Then iterative decoding is applied to the extended parity-check matrix.
This book constitutes the refereed proceedings of the 14th International Workshop on Post-Quantum Cryptography, PQCrypto 2022, held in College Park, MD, USA, in August 14–18, 2023.The 25 full papers presented in this book were carefully reviewed and selected from 51 submissions. They are categorized in the following topical sections: code-based cryptography; group-action-based cryptography; isogen
In post-quantum cryptography (PQC), Learning With Errors (LWE) is one of the dominant underlying mathematical problems. For example, in NIST’s PQC standardization process, the Key Encapsulation Mechanism (KEM) protocol chosen for standardization was Kyber, an LWE-based scheme. Recently the dual attack surpassed the primal attack in terms of concrete complexity for solving the underlying LWE proble
Misuse resilience is an important security criterion in the evaluation of the NIST Post-quantum cryptography standardization process. In this paper, we propose new key mismatch attacks against Kyber and Saber, NIST's selected scheme for encryption and one of the finalists in the third round of the NIST competition, respectively. Our novel idea is to recover partial information of multiple secret e
In LWE-based KEMs, observed decryption errors leak information about the secret key in the form of equations or inequalities. Several practical fault attacks have already exploited such leakage by either directly applying a fault or enabling a chosen-ciphertext attack using a fault. When the leaked information is in the form of inequalities, the recovery of the secret key is not trivial. Recent me
Millimeter-wave cellular communication requires beamforming procedures that enable alignment of the transmitter and receiver beams as the user equipment (UE) moves. For efficient beam tracking it is advantageous to classify users according to their traffic and mobility patterns. Research to date has demonstrated efficient ways of machine learning based UE classification. Although different machine
The learning with errors (LWE) problem is one of the main mathematical foundations of post-quantum cryptography. One of the main groups of algorithms for solving LWE is the Blum–Kalai–Wasserman (BKW) algorithm. This paper presents new improvements of BKW-style algorithms for solving LWE instances. We target minimum concrete complexity, and we introduce a new reduction step where we partially reduc
In this paper we consider a collection of relative pose problems which arise naturally in applications for visual indoor navigation using unmanned aerial vehicles (UAVs). We focus on cases where additional information from an onboard IMU is available and thus provides a partial extrinsic calibration through the gravitational vector. The solvers are designed for a partially calibrated camera, for a
In this paper, we present a side-channel attack on a first-order masked implementation of IND-CCA secure Saber KEM. We show how to recover both the session key and the long-term secret key from 24 traces using a deep neural network created at the profiling stage. The proposed message recovery approach learns a higher-order model directly, without explicitly extracting random masks at each executio
This thesis proposes approaches and models to increase the energy saving of the User Equipment (UE) in Long-Term Evolution (LTE) and 5G. The focus is mainly on Discontinuous Reception (DRX), the UE energy saving mechanism that was first introduced in LTE and will play an important role in 5G too.In this thesis, we take two main approaches. The first approach is based on joint optimization of DRX a
3D human pose and shape estimation plays a vital role in many computer vision applications. There are many deep learning based methods attempting to solve the problem only relying on single-view RGB images for training the network. However, since some public datasets are captured from multi-view cameras system, we propose a novel method to tackle the problem by putting optimization-based multi-vie
Emerging fine-grained cloud resource billing creates incentives to review the software execution footprint in virtual environments. Operators can use novel virtual execution environments with ever lower overhead: from virtual machines to containers, to unikernels and serverless functions. However, the execution footprint of security mechanisms in virtualized deployments has either remained the sam
Along with the rapid development of cloud computing technology, containerization technology has drawn much attention from both industry and academia. In this paper, we perform a comparative measurement analysis of Docker-sec, which is a Linux Security Module proposed in 2018, and a new AppArmor profile generator called Lic-Sec, which combines Docker-sec with a modified version of LiCShield, which
