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In this paper, we show that a software implementation of IND-CCA-secure Saber key encapsulation mechanism protected by first-order masking and shuffling can be broken by deep learning-based power analysis. Using an ensemble of deep neural networks trained at the profiling stage, we can recover the session key and the secret key from 257 × N and 24 × 257 × N traces, respectively, where N is the num
Background. A mathematical framework is presented for simultaneously quantifying and evaluating the trade-off between tumor control and late complications for risk-based radiation therapy (RT) decision-support. To demonstrate this, we estimate life years lost (LYL) attributable to tumor recurrence, late cardiac toxicity and secondary cancers for standard-risk pediatric medulloblastoma (MB) patient
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
We study the notion of anonymous credentials with Publicly Auditable Privacy Revocation (PAPR). PAPR credentials simultaneously provide conditional user privacy and auditable privacy revocation. The first property implies that users keep their identity private when authenticating unless and until an appointed authority requests to revoke this privacy, retroactively. The second property enforces th
In this paper, we present the first chosen-ciphertext (CC) cache-timing attacks on the reference implementation of HQC. We build a cache-timing based distinguisher for implementing a plaintext-checking (PC) oracle. The PC oracle uses side-channel information to check if a given ciphertext decrypts to a given message. This is done by identifying a vulnerability during the generating process of two
The Internet of Things (IoT) is a large network of connected devices. In IoT, devices can communicate with each other or back-end systems to transfer data or perform assigned tasks. Communication protocols used in IoT depend on target applications but usually require low bandwidth. On the other hand, IoT devices are constrained, having limited resources, including memory, power, and computational
Data analytics is regarded as an important function of 5G networks. The Network Data Analytics Function (NWDAF) is standardized in 3GPP to enhance 5G network performance by analyzing data from network functions and user equipment. Abnormal behavior detection, which is part of the NWDAF framework, has the potential to be a powerful tool to improve 5G network security. Despite this, only limited res
Side-channel resilience is a crucial feature when assessing whether a postquantum cryptographic proposal is sufficiently mature to be deployed. In this paper, we propose a generic and efficient adaptive approach to improve the sample complexity (i.e., the required number of traces) of plaintext-checking (PC) oracle-based sidechannel attacks (SCAs), a major class of key recovery chosen-ciphertext S
Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40–50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated wit
A unification of characteristic mode decomposition for all method-of-moment formulations of field integral equations describing free-space scattering is derived. The work is based on an algebraic link between impedance and transition matrices, the latter of which was used in early definitions of characteristic modes and is uniquely defined for all scattering scenarios. This also makes it possible
In this paper, we linear quadratic team decision problems, where a team of agents minimizes a convex quadratic cost function over T time steps subject to possibly distinct linear measurements of the state of nature. We assume that the state of nature is a Gaussian random variable and that the agents do not know the cost function nor the linear functions mapping the state of nature to their measure
We study network SIR (Susceptible - Infected - Recovered) epidemic models in the case of two interacting populations. We analyze the dynamics behavior of the fractions of infected individuals in the two populations. In contrast to the classical scalar SIR epidemic model, where the fraction of infected individuals is known to have an unimodal behavior (either decreasing throughout time or initially
Faults and errors are common in the execution of digital controllers on top of embedded hardware. Researchers from the embedded system domain devised models to understand and bound the occurrence of these faults. Using these models, control researchers have demonstrated robustness properties of control systems, and of their corresponding digital implementations. In this paper, we build a framework
System level synthesis is a promising approach that formulates structured optimal controller synthesis problems as convex problems. This work solves the distributed linear-quadratic regulator problem under communication constraints directly in infinite-dimensional space, without the finite-impulse response relaxation common in related work. Our method can also be used to construct optimal distribu
Social influence is largely recognized as a key factor in opinion formation processes. Recently, the role of external forces in inducing opinion displacement and polarization in social networks has attracted significant attention. This is in particular motivated by the necessity to understand and possibly prevent interference phenomena during political campaigns and elections. In this paper, we fo
We present a new, scalable alternative to the structured singular value, which we call v, provide a convex upper bound, study their properties and compare them to l1 robust control. The analysis relies on a novel result on the relationship between robust control of dynamical systems and non-negative constant matrices.
Positioning is an essential feature in Narrow-Band Internet-of-Things (NB-IoT) systems. Observed Time Difference of Arrival is one of the supported positioning techniques for NB-IoT. It utilizes the downlink NB positioning reference signal (NPRS) generated based on a length-31 Gold sequence. Although a Gold sequence has good auto-correlation and cross-correlation properties, the correlation proper
