Spoiled Onions: Exposing Malicious Tor Exit Relays

Several hundred Tor exit relays together push more than 1 GiB/s of network traffic. However, it is easy for exit relays to snoop and tamper with anonymised network traffic and as all relays are run by independent volunteers, not all of them are innocuous. In this paper, we seek to expose malicious exit relays and document their actions. First, we monitored the Tor network after developing a fast and modular exit relay scanner. We implemented several scanning modules for detecting common attacks and used them to probe all exit relays over a period of four months. We discovered numerous malicious exit relays engaging in different attacks. To reduce the attack surface users are exposed to, we further discuss the design and implementation of a browser extension patch which fetches and compares suspicious X.509 certificates over independent Tor circuits. Our work makes it possible to continuously monitor Tor exit relays. We are able to detect and thwart many man-in-the-middle attacks which makes the network safer for its users. All our code is available under a free license

Structural Measurement Errors in Nonseparable Models

This paper considers measurement error from a new perspective. In surveys, response errors are often caused by the fact that respondents recall past events and quantities imperfectly. We explore the consequences of recall errors for such key econometric is- sues as the identification of marginal effects or economic restrictions in structural models. Our identification approach is entirely nonparametric, using Matzkin-type nonseparable models that nest a large class of potential structural models. We establish that measurement errors due to poor recall are generally likely to exhibit nonstandard behavior, in particular be nonclassical and differential, and we provide means to deal with this situation. Moreover, our findings suggest that conventional wisdom about measurement errors may be misleading in many economic applications. For instance, under certain conditions left-hand side recall errors will be problematic even in the linear model, and quantiles will be less robust than means. Finally, we apply the main concepts put forward in this paper to real world data, and find evidence that underscores the importance of focusing on individual response behavior

Structural Measurement Errors in Nonseparable Models

This paper considers measurement error from a new perspective. In surveys, response errors are often caused by the fact that respondents recall past events and quantities imperfectly. We explore the consequences of recall errors for such key econometric is- sues as the identification of marginal effects or economic restrictions in structural models. Our identification approach is entirely nonparametric, using Matzkin-type nonseparable models that nest a large class of potential structural models. We establish that measurement errors due to poor recall are generally likely to exhibit nonstandard behavior, in particular be nonclassical and differential, and we provide means to deal with this situation. Moreover, our findings suggest that conventional wisdom about measurement errors may be misleading in many economic applications. For instance, under certain conditions left-hand side recall errors will be problematic even in the linear model, and quantiles will be less robust than means. Finally, we apply the main concepts put forward in this paper to real world data, and find evidence that underscores the importance of focusing on individual response behavior.Measurement Error; Nonparametric; Survey Design; Nonseparable Model; Identification; Zero Homogeneity; Demand

Fairness and Cheating

We present evidence from a laboratory experiment showing that individuals who believe they were treated unfairly in an interaction with another person are more likely to cheat in a subsequent unrelated game. Specifically, subjects first participated in a dictator game. They then flipped a coin in private and reported the outcome. Subjects could increase their total payoff by cheating, i.e., lying about the outcome of the coin toss. We found that subjects were more likely to cheat in reporting the outcome of the coin flip when: 1) they received either nothing or a very small transfer from the dictator; and 2) they claimed to have been treated unfairly. This is consistent with the view that experiencing a norm violation is sufficient to justify the violation of another norm at the expense of a third party. This result extends the growing literature on social norms

Fairness and Cheating

We present evidence from a laboratory experiment showing that individuals who believe they were treated unfairly in an interaction with another person are more likely to cheat in a subsequent unrelated game. Specifically, subjects first participated in a dictator game. They then flipped a coin in private and reported the outcome. Subjects could increase their total payoff by cheating, i.e., lying about the outcome of the coin toss. We found that subjects were more likely to cheat in reporting the outcome of the coin flip when: 1) they received either nothing or a very small transfer from the dictator; and 2) they claimed to have been treated unfairly. This is consistent with the view that experiencing a norm violation is sufficient to justify the violation of another norm at the expense of a third party. This result extends the growing literature on social norms.cheating; social norms; experimental design

Limitations on Quantum Key Repeaters

A major application of quantum communication is the distribution of entangled particles for use in quantum key distribution (QKD). Due to noise in the communication line, QKD is in practice limited to a distance of a few hundred kilometres, and can only be extended to longer distances by use of a quantum repeater, a device which performs entanglement distillation and quantum teleportation. The existence of noisy entangled states that are undistillable but nevertheless useful for QKD raises the question of the feasibility of a quantum key repeater, which would work beyond the limits of entanglement distillation, hence possibly tolerating higher noise levels than existing protocols. Here we exhibit fundamental limits on such a device in the form of bounds on the rate at which it may extract secure key. As a consequence, we give examples of states suitable for QKD but unsuitable for the most general quantum key repeater protocol.Comment: 11+38 pages, 4 figures, Statements for exact p-bits weakened as non-locking bound on measured relative entropy distance contained an erro

Risk attitudes and Medicare Part D enrollment decisions

The new Medicare Part D program provides prescription drug coverage for older Americans through highly subsidized and tightly regulated plans offered by private insurance firms. For most eligible individuals without coverage from other sources, obtaining Part D coverage would be rational, but it requires active enrollment and plan choice decisions. We investigate if non-enrollment in Medicare Part D can partly be explained by risk aversion. Data are taken from a national online survey conducted just after the introduction Part D. The survey included a context-free and a context-related hypothetical lottery to measure an individual’s attitude towards risk. Respondents who are risk tolerant according to these measures were significantly less likely to enroll in Part D. We also illustrate that hypothetical choice questions designed to elicit risk attitudes are subject to reference-point effects. Even minor differences in the priming of respondents can result in potentially misleading conclusions about the role of risk aversion in the insurance decisions

Generating Compact Geometric Track-Maps for Train Positioning Applications

In this paper, we present a method to generate compact geometric track-maps for train-borne localization applications. Therefore, we first give a brief overview on the purpose of track maps in train-positioning applications. It becomes apparent that there are hardly any adequate methods to generate suitable geometric track-maps. This is why we present a novel map generation procedure. It uses an optimization formulation to find the continuous sequence of track geometries that fits the available measurement data best. The optimization is initialized with the results from a localization filter developed in our previous work. The localization filter also provides the required information for shape identification and measurement association. The presented approach will be evaluated on simulated data as well as on real measurements

Risk attitudes and Medicare Part D enrollment decisions

The new Medicare Part D program provides prescription drug coverage for older Americans through highly subsidized and tightly regulated plans offered by private insurance firms. For most eligible individuals without coverage from other sources, obtaining Part D coverage would be rational, but it requires active enrollment and plan choice decisions. We investigate if non-enrollment in Medicare Part D can partly be explained by risk aversion. Data are taken from a national online survey conducted just after the introduction Part D. The survey included a context-free and a context-related hypothetical lottery to measure an individual’s attitude towards risk. Respondents who are risk tolerant according to these measures were significantly less likely to enroll in Part D. We also illustrate that hypothetical choice questions designed to elicit risk attitudes are subject to reference-point effects. Even minor differences in the priming of respondents can result in potentially misleading conclusions about the role of risk aversion in the insurance decisions.Risk aversion; Medicare Part D; heterogeneous preferences; insurance demand; survey design