12,098 research outputs found
Time is of the Essence: Machine Learning-based Intrusion Detection in Industrial Time Series Data
The Industrial Internet of Things drastically increases connectivity of
devices in industrial applications. In addition to the benefits in efficiency,
scalability and ease of use, this creates novel attack surfaces. Historically,
industrial networks and protocols do not contain means of security, such as
authentication and encryption, that are made necessary by this development.
Thus, industrial IT-security is needed. In this work, emulated industrial
network data is transformed into a time series and analysed with three
different algorithms. The data contains labeled attacks, so the performance can
be evaluated. Matrix Profiles perform well with almost no parameterisation
needed. Seasonal Autoregressive Integrated Moving Average performs well in the
presence of noise, requiring parameterisation effort. Long Short Term
Memory-based neural networks perform mediocre while requiring a high training-
and parameterisation effort.Comment: Extended version of a publication in the 2018 IEEE International
Conference on Data Mining Workshops (ICDMW
Tangled String for Multi-Scale Explanation of Contextual Shifts in Stock Market
The original research question here is given by marketers in general, i.e.,
how to explain the changes in the desired timescale of the market. Tangled
String, a sequence visualization tool based on the metaphor where contexts in a
sequence are compared to tangled pills in a string, is here extended and
diverted to detecting stocks that trigger changes in the market and to
explaining the scenario of contextual shifts in the market. Here, the
sequential data on the stocks of top 10 weekly increase rates in the First
Section of the Tokyo Stock Exchange for 12 years are visualized by Tangled
String. The changing in the prices of stocks is a mixture of various timescales
and can be explained in the time-scale set as desired by using TS. Also, it is
found that the change points found by TS coincided by high precision with the
real changes in each stock price. As TS has been created from the data-driven
innovation platform called Innovators Marketplace on Data Jackets and is
extended to satisfy data users, this paper is as evidence of the contribution
of the market of data to data-driven innovations.Comment: 16 pages and 7 figures. The author started to write this paper as an
extension of the paper [20] in the reference list, but the content came to be
changed substantially, not by only minor extension but to a new pape
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