A New Algorithm for Solving Ring-LPN with a Reducible Polynomial

The LPN (Learning Parity with Noise) problem has recently proved to be of great importance in cryptology. A special and very useful case is the RING-LPN problem, which typically provides improved efficiency in the constructed cryptographic primitive. We present a new algorithm for solving the RING-LPN problem in the case when the polynomial used is reducible. It greatly outperforms previous algorithms for solving this problem. Using the algorithm, we can break the Lapin authentication protocol for the proposed instance using a reducible polynomial, in about 2^70 bit operations

Conic Optimization Theory: Convexification Techniques and Numerical Algorithms

Optimization is at the core of control theory and appears in several areas of this field, such as optimal control, distributed control, system identification, robust control, state estimation, model predictive control and dynamic programming. The recent advances in various topics of modern optimization have also been revamping the area of machine learning. Motivated by the crucial role of optimization theory in the design, analysis, control and operation of real-world systems, this tutorial paper offers a detailed overview of some major advances in this area, namely conic optimization and its emerging applications. First, we discuss the importance of conic optimization in different areas. Then, we explain seminal results on the design of hierarchies of convex relaxations for a wide range of nonconvex problems. Finally, we study different numerical algorithms for large-scale conic optimization problems.Comment: 18 page

Real-time flutter analysis

The important algorithm issues necessary to achieve a real time flutter monitoring system; namely, the guidelines for choosing appropriate model forms, reduction of the parameter convergence transient, handling multiple modes, the effect of over parameterization, and estimate accuracy predictions, both online and for experiment design are addressed. An approach for efficiently computing continuous-time flutter parameter Cramer-Rao estimate error bounds were developed. This enables a convincing comparison of theoretical and simulation results, as well as offline studies in preparation for a flight test. Theoretical predictions, simulation and flight test results from the NASA Drones for Aerodynamic and Structural Test (DAST) Program are compared

Experimental demonstration of digital predistortion for orthogonal frequency-division multiplexing-radio over fibre links near laser resonance

Radio over fibre (RoF), an enabling technology for distribution of wireless broadband service signals through analogue optical links, suffers from non-linear distortion. Digital predistortion has been demonstrated as an effective approach to overcome the RoF non-linearity. However, questions remain as to how the approach performs close to laser resonance, a region of significant dynamic non-linearity, and how resilient the approach is to changes in input signal and link operating conditions. In this work, the performance of a digital predistortion approach is studied for directly modulated orthogonal frequency-division multiplexing RoF links operating from 2.47 to 3.7 GHz. It extends previous works to higher frequencies, and to higher quadrature amplitude modulation (QAM) levels. In addition, the resilience of the predistortion approach to changes in modulation level of QAM schemes, and average power levels are investigated, and a novel predistortion training approach is proposed and demonstrated. Both memoryless and memory polynomial predistorter models, and a simple off-line least-squares-based identification method, are used, with excellent performance improvements demonstrated up to 3.0 GHz