26,081 research outputs found
A Methodology for the Diagnostic of Aircraft Engine Based on Indicators Aggregation
Aircraft engine manufacturers collect large amount of engine related data
during flights. These data are used to detect anomalies in the engines in order
to help companies optimize their maintenance costs. This article introduces and
studies a generic methodology that allows one to build automatic early signs of
anomaly detection in a way that is understandable by human operators who make
the final maintenance decision. The main idea of the method is to generate a
very large number of binary indicators based on parametric anomaly scores
designed by experts, complemented by simple aggregations of those scores. The
best indicators are selected via a classical forward scheme, leading to a much
reduced number of indicators that are tuned to a data set. We illustrate the
interest of the method on simulated data which contain realistic early signs of
anomalies.Comment: Proceedings of the 14th Industrial Conference, ICDM 2014, St.
Petersburg : Russian Federation (2014
Towards Vulnerability Discovery Using Staged Program Analysis
Eliminating vulnerabilities from low-level code is vital for securing
software. Static analysis is a promising approach for discovering
vulnerabilities since it can provide developers early feedback on the code they
write. But, it presents multiple challenges not the least of which is
understanding what makes a bug exploitable and conveying this information to
the developer. In this paper, we present the design and implementation of a
practical vulnerability assessment framework, called Melange. Melange performs
data and control flow analysis to diagnose potential security bugs, and outputs
well-formatted bug reports that help developers understand and fix security
bugs. Based on the intuition that real-world vulnerabilities manifest
themselves across multiple parts of a program, Melange performs both local and
global analyses. To scale up to large programs, global analysis is
demand-driven. Our prototype detects multiple vulnerability classes in C and
C++ code including type confusion, and garbage memory reads. We have evaluated
Melange extensively. Our case studies show that Melange scales up to large
codebases such as Chromium, is easy-to-use, and most importantly, capable of
discovering vulnerabilities in real-world code. Our findings indicate that
static analysis is a viable reinforcement to the software testing tool set.Comment: A revised version to appear in the proceedings of the 13th conference
on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA),
July 201
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