Omitted-variable bias | EPFL Graph Search

In statistics, omitted-variable bias (OVB) occurs when a statistical model leaves out one or more relevant variables. The bias results in the model attributing the effect of the missing variables to those that were included. More specifically, OVB is the bias that appears in the estimates of parameters in a regression analysis, when the assumed specification is incorrect in that it omits an independent variable that is a determinant of the dependent variable and correlated with one or more of the included independent variables. In linear regression Intuition Suppose the true cause-and-effect relationship is given by: :y=a+bx+cz+u with parameters a, b, c, dependent variable y, independent variables x and z, and error term u. We wish to know the effect of x itself upon y (that is, we wish to obtain an estimate of b). Two conditions must hold true for omitted-variable bias to exist in linear regression:

the omitted variable must be a determinan

Applied stream ciphers in mobile communications

Yi Lu

This dissertation is concerned with cryptanalysis of E0, the stream cipher used in the short-range wireless radio standard Bluetooth, and of its generalization by means of correlation attacks. It consists of three parts. In the first part, we propose an E0-like combiner with memory as the core stream cipher. First, we formulate a systematic and simple method to compute the correlations. An upper bound of the correlations is given. Second, we show how to build either a uni-bias-based or multi-bias-based distinguisher to distinguish the keystream produced by the combiner from a truly random sequence, once correlations are found. The data complexity of either distinguisher is analyzed for performance comparison. The keystream distinguisher is then upgraded for use in the key-recovery attack. The latter reduces to the well-known maximum likelihood decoding problem given the keystream long enough. In the second part, the core stream cipher is transformed into the dedicated stream cipher by attaching the one-level or two-level initialization scheme. We show that the correlation attack on the core stream cipher leads to the correlation attack on the dedicated stream cipher with the one-level initialization scheme (with equal bias), but not necessarily so with the two-level initialization scheme. In the last part, we generalize the existing concept of conditional correlations and study conditional correlation attacks against stream ciphers and other cryptosystems. A general framework is developed for smart distinguishers, which exploit those generalized conditional correlations. Based on the theory of the traditional distinguisher, we derive the number of samples necessary for a smart distinguisher to succeed. It allows to prove that the smart distinguisher improves on the traditional basic distinguisher. As an application of all our analysis, it leads to the fastest (and only) practical known-plaintext attack on Bluetooth encryption so far. Our attack recovers the encryption key using the first 24 bits of 223.8 frames and with 238 computations.

EPFL2006

The geometrical edge barrier in type I superconductors

Bertrand Dutoit

The magneto-optical technique was used to study the edge barrier for flux entry in type I superconducting strips (In, Pb). The width of the flux-free zones appearing at the sample edges, due to the barrier, was measured at different applied fields and temperatures. Standard I–V measurements allowed us to study the critical current originated by the edge barrier in these pinning-free samples and its dependence on different parameters like magnetic field, temperature and sample's size. Our results confirm the geometrical origin of this edge barrier and show its dependence on different relevant variables.

1997

Applied stream ciphers in mobile communications

Yi Lu

EPFL2006