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Website fingerprinting (WF) attacks identify the websites visited over anonymized connections by analyzing patterns in network traffic flows, such as packet sizes, directions, or interval times using a machine learning classifier. Previous studies showed WF attacks achieve high classification accuracy. However, several issues call into question whether existing WF approaches are realizable in practice and thus motivate a re-exploration. Due to Tor's performance issues and resulting poor browsing experience, the vast majority of users opt for Virtual Private Networking (VPN) despite VPNs weaker privacy protections. Many other past assumptions are increasingly unrealistic as web technology advances. Our work addresses several key limitations of prior art. First, we introduce a new approach that classifies entire websites rather than individual web pages. Site-level classification uses traffic from all site components, including advertisements, multimedia, and single-page applications. Second, our Convolutional Neural Network (CNN) uses only the jitter and size of 500 contiguous packets from any point in a TCP stream, in contrast to prior work requiring heuristics to find page boundaries. Our seamless approach makes eavesdropper attack models realistic. Using traces from a controlled browser, we show our CNN matches observed traffic to a website with over 90% accuracy. We found the training traffic quality is critical as classification accuracy is significantly reduced when the training data lacks variability in network location, performance, and clients' computational capability. We enhanced the base CNN's efficacy using domain adaptation, allowing it to discount irrelevant features, such as network location. Lastly, we evaluate several defensive strategies against seamless WF attacks., Comment: 16 pages

We establish rigorous inequalities between different electronic properties linked to optical sum rules, and organize them into weak and strong bounds on three characteristic properties of insulators: electron localization length $\ell$ (the quantum fluctuations in polarization), electric susceptibility $\chi$, and optical gap $E_{\rm G}$. All-electron and valence-only versions of the bounds are given, and the latter are found to be more informative. The bounds on $\ell$ are particularly interesting, as they provide reasonably tight estimates for an ellusive ground-state property -- the average localization length of valence electrons -- from tabulated experimental data: electron density, high-frequency dielectric constant, and optical gap. The localization lengths estimated in this way for several materials follow simple chemical trends, especially for the alkali halides. We also illustrate our findings via analytically solvable harmonic oscillator models, which reveal an intriguing connection to the physics of long-ranged van der Waals forces.

We give a new improvement over Newton's method for root-finding, when the function in question is doubly differentiable. It generally exhibits faster and more reliable convergence. It can be also be thought of as a correction to Halley's method, as this can exhibit undesirable behaviour.

High-resolution angle- and spin-resolved photoemission spectroscopy reveals new features of the electronic structure of the ferromagnetic triple-layered ruthenate Sr$_4$Ru$_3$O$_{10}$. There are narrow spectral peaks $\sim$30 meV below the Fermi-level in two regions of the Brillouin zone: a hole-like band at the zone-center and a saddle-point van Hove singularity at the zone edge. Below T$_c$ each feature is almost completely spin-polarized, with opposite sign polarization and with strong Kondo-coherence-like temperature-dependent spectral weight variation suggestive of strong Hund's metal correlations. In addition, there are distinct Fermi surfaces for wide electron-like minority spin bands around the zone center and narrow hole-like majority spin Fermi surface contours around the zone corners. The origin of these features is in general agreement with density functional calculations, if they are shifted to reduce the exchange splitting, and scaled to take into account effects of correlation. Furthermore, the deduced narrow band origins from the tri-layer splitting of $d_{xz/yz}$ orbitals implies a layer-specific spin-polarization contribution from the narrow bands. Over a larger energy range, net spin-majority polarization of incoherent Ru $d$-bands is observed to extend down to the top of the oxygen bands, where additional narrow oxygen bands contribute to the magnetism with spin-minority polarization., Comment: 11 pages, 5 figures plus supplement 8 pages, 4 figures

We show how to derive the Black-Scholes model and its generalisation to the `exchange-option' (to exchange one asset for another) via the continuum limit of the Binomial tree. No knowledge of stochastic calculus or partial differential equations is assumed, as we do not use them., Comment: Added S1.7 on derivation of the delta

The notion of a credit spread curve is fundamental in fixed income investing, but in practice it is not `given' and needs to be constructed from bond prices either for a particular issuer, or for a sector rating-by-rating. Rather than attempting to fit spreads -- and as we discuss here, the Z-spread is unsuitable -- we fit parametrised survival curves. By deriving a valuation formula for a risky bond, we explain and avoid the problem that bonds with a high dollar price trade at a higher yield or spread than those with low dollar price (at the same maturity point), even though they do not necessarily offer better value. In fact, a concise treatment of this effect is elusive, and much of the academic literature on risky bond pricing, including a well-known paper by Duffie and Singleton (1997), is fundamentally incorrect. We then proceed to show how to calculate carry, rolldown and relative value for bonds/CDS. Also, once curve construction has been programmed and automated we can run it historically and assess the way a curve has moved over time. This provides the necessary grounding for econometric and arbitrage-free models of curve dynamics, which will be pursued in later work, as well as assessing how the perceived relative value of a particular instrument varies over time., Comment: Presents an extended form of the forward hazard rate model; gives details on CDS curve stripping; extends discussion on EM; new section on accreting bonds; new section on bond forwards

We report electronic band structure calculations for Sr$_{4}$Ru$_{3}$O$_{10}$ that displays both ferromagnetic and metamagnetic behavior. The density functional calculations find the ground state to be ferromagnetic in agreement with the experiment and we find that the inclusion of Coulomb Hubbard interaction U applied to the Ru 4d states has dramatic effects on the Fermi surface, which reveal the role of Coulomb interactions and correlated many-body physics. The minority spin bands are mainly empty with Fermi surfaces in the outer areas of the Brillouin zone away from the $\Gamma$ point with bands that disperse steeply upward. The majority spin bands are full or nearly fully occupied and form narrow bands near the Fermi energy around the $\Gamma$ point, which could be the electronic origin of the metamagnetism. The results are in qualitative agreement with recent angle resolved photoemission spectroscopy (ARPES) experiments and show the need for a combined theoretical study and experimental ARPES investigation with better energy resolution to reveal the nature of the narrow bands close to the Fermi-level, which is critical for understanding the exotic magnetic properties observed in this material.

This paper proposes a new hardware accelerator for sparse convolutional neural networks (CNNs) by building a hardware unit to perform the Image to Column (IM2COL) transformation of the input feature map coupled with a systolic array-based general matrix-matrix multiplication (GEMM) unit. Our design carefully overlaps the IM2COL transformation with the GEMM computation to maximize parallelism. We propose a novel design for the IM2COL unit that uses a set of distributed local memories connected by a ring network, which improves energy efficiency and latency by streaming the input feature map only once. We propose a tall systolic array for the GEMM unit while also providing the ability to organize it as multiple small GEMM units, which enables our design to handle a wide range of CNNs and their parameters. Further, our design improves performance by effectively mapping the sparse data to the hardware units by utilizing sparsity in both input feature maps and weights. Our prototype, SPOTS, is on average 1.74X faster than Eyeriss. It is also 78X, and 12X more energy-efficient when compared to CPU and GPU implementations, respectively., Comment: 24 pages

An analysis is presented of a Brownian particle moving on the half-line, subject to a restoring force proportional to its displacement and an absorbing boundary at the origin. When the initial displacement is large, the central moments of the time to be absorbed tend to finite constants, as do the position moments when evaluated at the most probable absorption time. These quantities are derived explicitly.

We give a complete description of the third-moment (skewness) characteristics of both linear and nonlinear momentum trading strategies, the latter being understood as transformations of a normalised moving-average filter (EMA). We explain in detail why the skewness is generally positive and has a term structure. This paper is a synthesis of two papers published by the author in RISK in 2012, with some updates and comments., Comment: v2: Expanded the Appendix

We consider the area functional defined by the integral of an Ornstein-Uhlenbeck process which starts from a given value and ends at the time it first reaches zero (its equilibrium level). Exact results are presented for the mean, variance, skewness and kurtosis of the underlying area probability distribution, together with the covariance and correlation between the area and the first passage time. Amongst other things, the analysis demonstrates that the area distribution is asymptotically normal in the weak noise limit, which stands in contrast to the first passage time distribution. Various applications are indicated., Comment: 28 pages, 3 figures, updated version as published

Markovian credit migration models are a reasonably standard tool nowadays, but there are fundamental difficulties with calibrating them. We show how these are resolved using a simplified form of matrix generator and explain why risk-neutral calibration cannot be done without volatility information. We also show how to use elementary ideas from differential geometry to make general inferences about calibration stability. This the longer version of an article published by RISK (Feb 2021)., Comment: Minor corrections from V1

We address the modelling of commodities that are supposed to have positive price but, on account of a possible failure in the physical delivery mechanism, may turn out not to. This is done by explicitly incorporating a `delivery liability' option into the contract. As such it is a simple generalisation of the established Black model., Comment: Extended section on Levy models and given explicit formulae and numerical example. Corrected typo in put/call formulae (eq.5,6 in this vsn)

This paper describes REAP, a software-hardware approach that enables high performance sparse linear algebra computations on a cooperative CPU-FPGA platform. REAP carefully separates the task of organizing the matrix elements from the computation phase. It uses the CPU to provide a first-pass re-organization of the matrix elements, allowing the FPGA to focus on the computation. We introduce a new intermediate representation that allows the CPU to communicate the sparse data and the scheduling decisions to the FPGA. The computation is optimized on the FPGA for effective resource utilization with pipelining. REAP improves the performance of Sparse General Matrix Multiplication (SpGEMM) and Sparse Cholesky Factorization by 3.2X and 1.85X compared to widely used sparse libraries for them on the CPU, respectively., Comment: 12 pages

Fixed income has received far less attention than equity portfolio optimisation since Markowitz' original work of 1952, partly as a result of the need to model rates and credit risk. We argue that the shape of the efficient frontier is mainly controlled by linear constraints, with the standard deviation relatively unimportant, and propose a two-factor model for its time evolution.