arXiv subjects

Matthew Wright

Publications and source records attributed to Matthew Wright.

At least 37 records · Page 2Linked to original sources

arXiv2020

Tik-Tok: The Utility of Packet Timing in Website Fingerprinting Attacks

A passive local eavesdropper can leverage Website Fingerprinting (WF) to deanonymize the web browsing activity of Tor users. The value of timing information to WF has often been discounted in recent works due to the volatility of low-level timing information. In this paper, we more carefully examine the extent to which packet timing can be used to facilitate WF attacks. We first propose a new set of timing-related features based on burst-level characteristics to further identify more ways that timing patterns could be used by classifiers to identify sites. Then we evaluate the effectiveness of both raw timing and directional timing which is a combination of raw timing and direction in a deep-learning-based WF attack. Our closed-world evaluation shows that directional timing performs best in most of the settings we explored, achieving: (i) 98.4% in undefended Tor traffic; (ii) 93.5% on WTF-PAD traffic, several points higher than when only directional information is used; and (iii) 64.7% against onion sites, 12% higher than using only direction. Further evaluations in the open-world setting show small increases in both precision (+2%) and recall (+6%) with directional-timing on WTF-PAD traffic. To further investigate the value of timing information, we perform an information leakage analysis on our proposed handcrafted features. Our results show that while timing features leak less information than directional features, the information contained in each feature is mutually exclusive to one another and can thus improve the robustness of a classifier.

cs.CR↗

arXiv2019

They Might NOT Be Giants: Crafting Black-Box Adversarial Examples with Fewer Queries Using Particle Swarm Optimization

Machine learning models have been found to be susceptible to adversarial examples that are often indistinguishable from the original inputs. These adversarial examples are created by applying adversarial perturbations to input samples, which would cause them to be misclassified by the target models. Attacks that search and apply the perturbations to create adversarial examples are performed in both white-box and black-box settings, depending on the information available to the attacker about the target. For black-box attacks, the only capability available to the attacker is the ability to query the target with specially crafted inputs and observing the labels returned by the model. Current black-box attacks either have low success rates, requires a high number of queries, or produce adversarial examples that are easily distinguishable from their sources. In this paper, we present AdversarialPSO, a black-box attack that uses fewer queries to create adversarial examples with high success rates. AdversarialPSO is based on the evolutionary search algorithm Particle Swarm Optimization, a populationbased gradient-free optimization algorithm. It is flexible in balancing the number of queries submitted to the target vs the quality of imperceptible adversarial examples. The attack has been evaluated using the image classification benchmark datasets CIFAR-10, MNIST, and Imagenet, achieving success rates of 99.6%, 96.3%, and 82.0%, respectively, while submitting substantially fewer queries than the state-of-the-art. We also present a black-box method for isolating salient features used by models when making classifications. This method, called Swarms with Individual Search Spaces or SWISS, creates adversarial examples by finding and modifying the most important features in the input.

cs.LG↗

arXiv2019

Finding Minimum Spanning Forests in a Graph

We introduce a graph partitioning problem motivated by computational topology and propose two algorithms that produce approximate solutions. Specifically, given a weighted, undirected graph $G$ and a positive integer $k$, we desire to find $k$ disjoint trees within $G$ such that each vertex of $G$ is contained in one of the trees and the weight of the largest tree is as small as possible. We are unable to find this problem in the graph partitioning literature, but we show that the problem is NP-complete. We then propose two approximation algorithms, one that uses a spectral clustering approach and another that employs a dynamic programming strategy, which produce near-optimal partitions on a family of test graphs. We describe these algorithms and analyze their empirical performance.

math.CO↗

arXiv2018

Modified Relay Selection and Circuit Selection for Faster Tor

Users of the Tor anonymity system suffer from lessthan- ideal performance, in part because circuit building and selection processes are not tuned for speed. In this paper, we examine both the process of selecting among pre-built circuits and the process of selecting the path of relays for use in building new circuits to improve performance while maintaining anonymity. First, we show that having three pre-built circuits available allows the Tor client to identify fast circuits and improves median time to first byte (TTFB) by 15% over congestion-aware routing, the current state-of-the-art method. Second, we propose a new path selection algorithm that includes broad geographic location information together with bandwidth to reduce delays. In Shadow simulations, we find 20% faster median TTFB and 11% faster median total download times over congestion-aware routing for accessing webpage-sized objects. Our security evaluations show that this approach leads to better or equal security against a generic relay-level adversary compared to Tor, but increased vulnerability to targeted attacks. We explore this trade-off and find settings of our system that offer good performance, modestly better security against a generic adversary, and only slightly more vulnerability to a targeted adversary.

cs.CR↗

arXiv2018

Deep Fingerprinting: Undermining Website Fingerprinting Defenses with Deep Learning

Website fingerprinting enables a local eavesdropper to determine which websites a user is visiting over an encrypted connection. State-of-the-art website fingerprinting attacks have been shown to be effective even against Tor. Recently, lightweight website fingerprinting defenses for Tor have been proposed that substantially degrade existing attacks: WTF-PAD and Walkie-Talkie. In this work, we present Deep Fingerprinting (DF), a new website fingerprinting attack against Tor that leverages a type of deep learning called Convolutional Neural Networks (CNN) with a sophisticated architecture design, and we evaluate this attack against WTF-PAD and Walkie-Talkie. The DF attack attains over 98% accuracy on Tor traffic without defenses, better than all prior attacks, and it is also the only attack that is effective against WTF-PAD with over 90% accuracy. Walkie-Talkie remains effective, holding the attack to just 49.7% accuracy. In the more realistic open-world setting, our attack remains effective, with 0.99 precision and 0.94 recall on undefended traffic. Against traffic defended with WTF-PAD in this setting, the attack still can get 0.96 precision and 0.68 recall. These findings highlight the need for effective defenses that protect against this new attack and that could be deployed in Tor.

cs.CR↗

arXiv2018

Towards Predicting Efficient and Anonymous Tor Circuits

The Tor anonymity system provides online privacy for millions of users, but it is slower than typical web browsing. To improve Tor performance, we propose PredicTor, a path selection technique that uses a Random Forest classifier trained on recent measurements of Tor to predict the performance of a proposed path. If the path is predicted to be fast, then the client builds a circuit using those relays. We implemented PredicTor in the Tor source code and show through live Tor experiments and Shadow simulations that PredicTor improves Tor network performance by 11% to 23% compared to Vanilla Tor and by 7% to 13% compared to the previous state-of-the-art scheme. Our experiments show that PredicTor is the first path selection algorithm to dynamically avoid highly congested nodes during times of high congestion and avoid long-distance paths during times of low congestion. We evaluate the anonymity of PredicTor using standard entropy-based and time-to-first-compromise metrics, but these cannot capture the possibility of leakage due to the use of location in path selection. To better address this, we propose a new anonymity metric called CLASI: Client Autonomous System Inference. CLASI is the first anonymity metric in Tor that measures an adversary's ability to infer client Autonomous Systems (ASes) by fingerprinting circuits at the network, country, and relay level. We find that CLASI shows anonymity loss for location-aware path selection algorithms, where entropy-based metrics show little to no loss of anonymity. Additionally, CLASI indicates that PredicTor has similar sender AS leakage compared to the current Tor path selection algorithm due to PredicTor building circuits that are independent of client location.

cs.CR↗

arXiv2017

On galaxy rotation curves from a continuum mechanics approach to modified gravity

We consider a modification of General Relativity motivated by the treatment of anisotropies in Continuum Mechanics. The Newtonian limit of the theory is formulated and applied to galactic rotation curves. By assuming that the additional structure of spacetime behaves like a Newtonian gravitational potential for small deviations from isotropy, we are able to recover the Navarro-Frenk-White profile of dark matter halos by a suitable identification of constants. We consider the Burkert profile in the context of our model and also discuss rotation curves more generally.

gr-qc↗

arXiv2017

Forming Guard Sets using AS Relationships

The mechanism for picking guards in Tor suffers from security problems like guard fingerprinting and from performance issues. To address these issues, Hayes and Danezis proposed the use of guard sets, in which the Tor system groups all guards into sets, and each client picks one of these sets and uses its guards. Unfortunately, guard sets frequently need nodes added or they are broken up due to fluctuations in network bandwidth. In this paper, we first show that these breakups create opportunities for malicious guards to join many guard sets by merely tuning the bandwidth they make available to Tor, and this greatly increases the number of clients exposed to malicious guards. To address this problem, we propose a new method for forming guard sets based on Internet location. We construct a hierarchy that keeps clients and guards together more reliably and prevents guards from easily joining arbitrary guard sets. This approach also has the advantage of confining an attacker with access to limited locations on the Internet to a small number of guard sets. We simulate this guard set design using historical Tor data in the presence of both relay-level adversaries and network-level adversaries, and we find that our approach is good at confining the adversary into few guard sets and thus limiting the impact of attacks.

cs.CR↗

arXiv2017

The Evaluation of Circuit Selection Methods on Tor

Tor provides anonymity online by routing traffic through encrypted tunnels, called circuits, over paths of anonymizing relays. To enable users to connect to their selected destination servers without waiting for the circuit to be build, the Tor client maintains a few circuits at all times. Nevertheless, Tor is slower to use than directly connecting to the destination server. In this paper, we propose to have the Tor client measure the performance of the pre-built circuits and select the fastest circuits for users to send their traffic over. To this end, we define and evaluate nine metrics for selecting which pre-built circuit to use based on different combinations of circuit length, Round Trip Time (RTT), and congestion. We also explore the effect on performance of the number of pre-built circuits at the time of the selection. Through whole-network experiments in Shadow, we show that using circuit RTT with at least three pre-built circuits allows the Tor client to identify fast circuits and improves median time to first byte (TTFB) by 22% over Tor and 15% over congestion-aware routing, the state-of-the-art in Tor circuit selection. We evaluate the security of the proposed circuit selection mechanism against both a relay-level and a network-level adversary and find no loss of security compared with Tor.

cs.CR↗

arXiv2017

Approval Voting in Product Societies

In approval voting, individuals vote for all platforms that they find acceptable. In this situation it is natural to ask: When is agreement possible? What conditions guarantee that some fraction of the voters agree on even a single platform? Berg et. al. found such conditions when voters are asked to make a decision on a single issue that can be represented on a linear spectrum. In particular, they showed that if two out of every three voters agree on a platform, there is a platform that is acceptable to a majority of the voters. Hardin developed an analogous result when the issue can be represented on a circular spectrum. We examine scenarios in which voters must make two decisions simultaneously. For example, if voters must decide on the day of the week to hold a meeting and the length of the meeting, then the space of possible options forms a cylindrical spectrum. Previous results do not apply to these multi-dimensional voting societies because a voter's preference on one issue often impacts their preference on another. We present a general lower bound on agreement in a two-dimensional voting society, and then examine specific results for societies whose spectra are cylinders and tori.

math.CO↗

arXiv2017

Cosmological dynamics of extended chameleons

We investigate the cosmological dynamics of the recently proposed extended chameleon models at both background and linear perturbation levels. Dynamical systems techniques are employed to fully characterize the evolution of the universe at the largest distances, while structure formation is analysed at sub-horizon scales within the quasi-static approximation. The late time dynamical transition from dark matter to dark energy domination can be well described by almost all extended chameleon models considered, with no deviations from $Λ$CDM results at both background and perturbation levels. The results obtained in this work confirm the cosmological viability of extended chameleons as alternative dark energy models.

gr-qc↗

arXiv2016

Toward an Efficient Website Fingerprinting Defense

Website Fingerprinting attacks enable a passive eavesdropper to recover the user's otherwise anonymized web browsing activity by matching the observed traffic with prerecorded web traffic templates. The defenses that have been proposed to counter these attacks are impractical for deployment in real-world systems due to their high cost in terms of added delay and bandwidth overhead. Further, these defenses have been designed to counter attacks that, despite their high success rates, have been criticized for assuming unrealistic attack conditions in the evaluation setting. In this paper, we propose a novel, lightweight defense based on Adaptive Padding that provides a sufficient level of security against website fingerprinting, particularly in realistic evaluation conditions. In a closed-world setting, this defense reduces the accuracy of the state-of-the-art attack from 91% to 20%, while introducing zero latency overhead and less than 60% bandwidth overhead. In an open-world, the attack precision is just 1% and drops further as the number of sites grows.

cs.CR↗

arXiv2016

Buchdahl's inequality in five dimensional Gauss-Bonnet gravity

The Buchdahl limit for static spherically symmetric isotropic stars is generalised to the case of five dimensional Gauss-Bonnet gravity. Our result depends on the sign of the Gauss-Bonnet coupling constant $α$. When $α>0$, we find, unlike in general relativity, that the bound is dependent on the stellar structure, in particular the central energy density. We find that stable stellar structures can exist arbitrarily close to the event horizon. Thus stable stars can exist with extra mass in this theory compared to five dimensional general relativity. For $α<0$ it is found that the Buchdahl bound is more restrictive than the general relativistic case.

gr-qc↗

arXiv2016

Fusing Loop and GPS Probe Measurements to Estimate Freeway Density

In an age of ever-increasing penetration of GPS-enabled mobile devices, the potential of real-time "probe" location information for estimating the state of transportation networks is receiving increasing attention. Much work has been done on using probe data to estimate the current speed of vehicle traffic (or equivalently, trip travel time). While travel times are useful to individual drivers, the state variable for a large class of traffic models and control algorithms is vehicle density. Our goal is to use probe data to supplement traditional, fixed-location loop detector data for density estimation. To this end, we derive a method based on Rao-Blackwellized particle filters, a sequential Monte Carlo scheme. We present a simulation where we obtain a 30\% reduction in density mean absolute percentage error from fusing loop and probe data, vs. using loop data alone. We also present results using real data from a 19-mile freeway section in Los Angeles, California, where we obtain a 31\% reduction. In addition, our method's estimate when using only the real-world probe data, and no loop data, outperformed the estimate produced when only loop data were used (an 18\% reduction). These results demonstrate that probe data can be used for traffic density estimation.

eess.SY↗

arXiv2016

Conformal transformations in modified teleparallel theories of gravity revisited

It is well known that one cannot apply a conformal transformation to $f(T)$ gravity to obtain a minimally coupled scalar field model, and thus no Einstein frame exists for $f(T)$ gravity. Furthermore nonminimally coupled "teleparallel dark energy models" are not conformally equivalent to $f(T)$ gravity. However, it can be shown that $f(T)$ gravity is conformally equivalent to a teleparallel phantom scalar field model with a nonminimal coupling to a boundary term only. In this work, we extend this analysis by considering a recently studied extended class of models, known as $f(T,B)$ gravity, where $B$ is a boundary term related to the divergence of a contraction of the torsion tensor. We find that nonminimally coupled "teleparallel dark energy models" are conformally equivalent to either an $f(T,B)$ or $f(B)$ gravity model. Finally conditions on the functional form of $f(T,B)$ gravity are derived to allow it to be transformed to particular nonminimally coupled scalar field models.

gr-qc↗

arXiv2016

Teleparallel quintessence with a nonminimal coupling to a boundary term

We propose a new model in the teleparallel framework where we consider a scalar field nonminimally coupled to both the torsion $T$ and a boundary term given by the divergence of the torsion vector $B=\frac{2}{e}\partial_μ(eT^μ)$. This is inspired by the relation $R=-T+B$ between the Ricci scalar of general relativity and the torsion of teleparallel gravity. This theory in suitable limits incorporates both the nonminimal coupling of a scalar field to torsion, and the nonminimal coupling of a scalar field to the Ricci scalar. We analyse the cosmology of such models, and we perform a dynamical systems analysis on the case when we have only a pure coupling to the boundary term. It is found that the system generically evolves to a late time accelerating attractor solution without requiring any fine tuning of the parameters. A dynamical crossing of the phantom barrier is also shown to be possible.

gr-qc↗

arXiv2016

Correspondence of $F(R)$ Gravity Singularities in Jordan and Einstein Frames

We study the finite time singularity correspondence between the Jordan and Einstein frames for various $F(R)$ gravity theories. Particularly we investigate the ordinary pure $F(R)$ gravity case and the unimodular $F(R)$ gravity cases, in the absence of any matter fluids. In the ordinary $F(R)$ gravity cases, by using specific illustrative examples, we show that it is possible to have various correspondences of finite time singularities, and in some cases it is possible a singular cosmology in one frame might be non-singular in the other frame. In the unimodular $F(R)$ gravity case, the unimodular constraint is affected from the conformal transformation, so this has an effect on the metric we choose. Moreover, we study the Einstein frame counterpart theory of the unimodular $F(R)$ gravity case, and we investigate the correspondences of the singularities in the two theories by considering specific illustrative examples. Finally, a brief dynamical system analysis is performed for the vacuum unimodular $F(R)$ gravity and we demonstrate how the dynamical system behaves near the future Big Rip singularity.

gr-qc↗

arXiv2015

Interactive Visualization of 2-D Persistence Modules

The goal of this work is to extend the standard persistent homology pipeline for exploratory data analysis to the 2-D persistence setting, in a practical, computationally efficient way. To this end, we introduce RIVET, a software tool for the visualization of 2-D persistence modules, and present mathematical foundations for this tool. RIVET provides an interactive visualization of the barcodes of 1-D affine slices of a 2-D persistence module $M$. It also computes and visualizes the dimension of each vector space in $M$ and the bigraded Betti numbers of $M$. At the heart of our computational approach is a novel data structure based on planar line arrangements, on which we can perform fast queries to find the barcode of any slice of $M$. We present an efficient algorithm for constructing this data structure and establish bounds on its complexity.

math.AT↗