Attributing hacks with survival trend filtering
نویسندگان
چکیده
منابع مشابه
Attributing Hacks
In this paper, we describe an algorithm for estimating the provenance of hacks on websites. That is, given properties of sites and the temporal occurrence of attacks, we are able to attribute individual attacks to joint causes and vulnerabilities, as well as estimating the evolution of these vulnerabilities over time. Specifically, we use hazard regression with a time-varying additive hazard fu...
متن کاملAdditive Models with Trend Filtering
We consider additive models built with trend filtering, i.e., additive models whose components are each regularized by the (discrete) total variation of their (k+1)st (discrete) derivative, for a chosen integer k ≥ 0. This results in kth degree piecewise polynomial components, (e.g., k = 0 gives piecewise constant components, k = 1 gives piecewise linear, k = 2 gives piecewise quadratic, etc.)....
متن کاملl1 Trend Filtering
The problem of estimating underlying trends in time series data arises in a variety of disciplines. In this paper we propose a variation on Hodrick-Prescott (H-P) filtering, a widely used method for trend estimation. The proposed l1 trend filtering method substitutes a sum of absolute values (i.e., an l1-norm) for the sum of squares used in H-P filtering to penalize variations in the estimated ...
متن کامل1 Trend Filtering
The problem of estimating underlying trends in time series data arises in a variety of disciplines. In this paper we propose a variation on Hodrick–Prescott (H-P) filtering, a widely used method for trend estimation. The proposed !1 trend filtering method substitutes a sum of absolute values (i.e., !1 norm) for the sum of squares used in H-P filtering to penalize variations in the estimated tre...
متن کاملTrend Filtering on Graphs
Yu-Xiang Wang1,2 [email protected] James Sharpnack3 [email protected] Alexander J. Smola1,4 [email protected] Ryan J. Tibshirani1,2 [email protected] 1 Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA 15213 2 Department of Statistics, Carnegie Mellon University, Pittsburgh, PA 15213 3 Mathematics Department, University of California at San Diego, La Jolla, CA 10280 ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Electronic Journal of Statistics
سال: 2017
ISSN: 1935-7524
DOI: 10.1214/17-ejs1380si