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<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
DATA ANALYSIS FOR NETWORK CYBER-SECURITY
<|im_end|>
<|im_start|>assistant
p919hc_9781783263745_tp.indd 1 17/1/14 10:26 amMay
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<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
2, 2013 14:6 BC: 8831
<|im_end|>
<|im_start|>assistant
- Probability and Statistical Theory
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
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PST˙ws This page intentionally left
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blankThis page intentionally left blankImperial
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
College PressICPDATA ANALYSIS FOR NETWORK
<|im_end|>
<|im_start|>assistant
CYBER-SECURITY editors Niall Adams •
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
Nicholas Heard Imperial College London
<|im_end|>
<|im_start|>assistant
Heilbronn Institute for Mathematical Research,
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
University of Bristol p919hc_9781783263745_tp.indd 2
<|im_end|>
<|im_start|>assistant
17/1/14 10:26 amPublished byImperial College
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
Press57 Shelton StreetCovent GardenLondon WC2H
<|im_end|>
<|im_start|>assistant
9HEDistributed byWorld Scientific Publishing Co.
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
Pte. Ltd.5 Toh Tuck Link,
<|im_end|>
<|im_start|>assistant
Singapore 596224USA office: 27 Warren
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
Street, Suite 401-402, Hackensack, NJ
<|im_end|>
<|im_start|>assistant
07601 UK office: 57 Shelton
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
Street, Covent Garden, London WC2H
<|im_end|>
<|im_start|>assistant
9HE British Library Cataloguing-in-Publication DataA
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
catalogue record for this book
<|im_end|>
<|im_start|>assistant
is available from the British
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
Library. DATA ANALYSIS FOR NETWORK
<|im_end|>
<|im_start|>assistant
CYBER-SECURITYCopyright © 2014 by Imperial
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
College PressAll rights reserved. This
<|im_end|>
<|im_start|>assistant
book, or parts thereof, may
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
not be reproduced in any
<|im_end|>
<|im_start|>assistant
form or by any means,electronic
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
or mechanical, including photocopying, recording
<|im_end|>
<|im_start|>assistant
or any information storage and
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
retrievalsystem now known or to
<|im_end|>
<|im_start|>assistant
be invented, without written permission
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
from the Publisher.For photocopying of
<|im_end|>
<|im_start|>assistant
material in this volume, please
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
pay a copying fee through
<|im_end|>
<|im_start|>assistant
the Copyright ClearanceCenter, Inc., 222
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
Rosewood Drive, Danvers, MA 01923,
<|im_end|>
<|im_start|>assistant
USA. In this case permission
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
to photocopyis not required from
<|im_end|>
<|im_start|>assistant
the publisher.ISBN 978-1-78326-374-5Typeset by Stallion
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
PressEmail: enquiries@stallionpress.comPrinted in SingaporeJanuary 17,
<|im_end|>
<|im_start|>assistant
2014 17:33 9in x 6in
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
Data Analysis for Network Cyber
<|im_end|>
<|im_start|>assistant
Security b1711-fm Preface The contents
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
of this volume are contributions
<|im_end|>
<|im_start|>assistant
from invited speakers at aworkshop
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
entitled “Data Analysis for Cyber-Security”,
<|im_end|>
<|im_start|>assistant
hosted by the Uni-versity of
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
Bristol in March 2013. We
<|im_end|>
<|im_start|>assistant
are grateful for the generous
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
support ofthe Heilbronn Institute for
<|im_end|>
<|im_start|>assistant
Mathemat ical Research, an academic
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
research unit of the Universisty
<|im_end|>
<|im_start|>assistant
of Bristol with in terests
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
related to cyber-security. Cyber-security –
<|im_end|>
<|im_start|>assistant
the task of defending computers
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
and people from elec- tronic
<|im_end|>
<|im_start|>assistant
attack – is a pressing
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
concern. For example, a report
<|im_end|>
<|im_start|>assistant
sponsored bythe UK government in
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
2012 estimated the cost of
<|im_end|>
<|im_start|>assistant
cyber-attack to the UKeconomy as
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
£29 billion. This cost is
<|im_end|>
<|im_start|>assistant
attributed to various types of
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
attack, including extortion, fiscal fraud
<|im_end|>
<|im_start|>assistant
and identity theft. Notably, the
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
largest cat-egory, intellectual property theft,
<|im_end|>
<|im_start|>assistant
accounted for around £9 billion.
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
The scale of cyber-attack provoked
<|im_end|>
<|im_start|>assistant
the UK gover nment to
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
highlight cyber-security as a top
<|im_end|>
<|im_start|>assistant
priority for national security in
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
2013. From a UK point
<|im_end|>
<|im_start|>assistant
of view, basedon recent figures,
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
the problem is increa sing:
<|im_end|>
<|im_start|>assistant
78% of large organisations were
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
subject to external attack in
<|im_end|>
<|im_start|>assistant
2012, up from 73% in
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
the previous year, while63% of
<|im_end|>
<|im_start|>assistant
small business were subject to
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
such attack over the same
<|im_end|>
<|im_start|>assistant
period, anincrease of 41% on
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
the previous year. Cyber-security is
<|im_end|>
<|im_start|>assistant
a broad discipline, covering a
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
range of academic dis- ciplines
<|im_end|>
<|im_start|>assistant
including computer science, computer and
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
netwo rk architecture, and statistics.
<|im_end|>
<|im_start|>assistant
This volume is concerned with
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
network cyber-security, and particularly, analysis
<|im_end|>
<|im_start|>assistant
of data that are observed
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
in relation to a network
<|im_end|>
<|im_start|>assistant
ofeither computers or people. As
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
an exem plar, consider an
<|im_end|>
<|im_start|>assistant
institutional com- puter network, in
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
which communicating devices (computers, printers,
<|im_end|>
<|im_start|>assistant
etc.)arenodes and communications between devices
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
are events that occur on
<|im_end|>
<|im_start|>assistant
edges between nodes. Numerous types
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
of cyber-attack have been observed
<|im_end|>
<|im_start|>assistant
in this context. A variety
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
of such attacks are well
<|im_end|>
<|im_start|>assistant
described in Davidoff andHam (2012)
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
from the point of view
<|im_end|>
<|im_start|>assistant
of network forensics. There are
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
a number of problems that
<|im_end|>
<|im_start|>assistant
can be addressed by analysing
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
network data. A primary example
<|im_end|>
<|im_start|>assistant
is constructing anomaly detection meth-ods
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
to identify when unusual traffic
<|im_end|>
<|im_start|>assistant
occurs. These complement signature-based methods,
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
such as those embodied for
<|im_end|>
<|im_start|>assistant
example in the Snort intrusion
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
vJanuary 17, 2014 17:33 9in
<|im_end|>
<|im_start|>assistant
x 6in Data Analysis for
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
Network Cyber Security b1711-fm vi
<|im_end|>
<|im_start|>assistant
Preface detection system (Caswell et
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
al., 2007). We believe the
<|im_end|>
<|im_start|>assistant
next generation of detection tools
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
will have to utilise more
<|im_end|>
<|im_start|>assistant
information about past and presenttraffic
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
behaviour, particularly with res pect
<|im_end|>
<|im_start|>assistant
to temporal aspects. A particu-
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
lar advantage of anomaly detection
<|im_end|>
<|im_start|>assistant
methods over rule-based approaches istheir
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
potential to detect new, so-called
<|im_end|>
<|im_start|>assistant
zero-day , attacks. There are
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
significant challenges when addressing network
<|im_end|>
<|im_start|>assistant
data analysis problems. In the
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
context of cyber-secu rity, data
<|im_end|>
<|im_start|>assistant
sets are typically big, con-
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
sisting of a large number
<|im_end|>
<|im_start|>assistant
of nodes and a great
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
volume of traffic on existingedges.
<|im_end|>
<|im_start|>assistant
This alone raises significant computational
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
challenges. If anomalydetection is the
<|im_end|>
<|im_start|>assistant
objective, then timeliness becomes an
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
issue, and the veloc- ityof
<|im_end|>
<|im_start|>assistant
the traffic on edges becomes
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
an important factor. The combination
<|im_end|>
<|im_start|>assistant
of volume and velocity makes
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
much network cyber-security a “big-data”problem.
<|im_end|>
<|im_start|>assistant
From a statistical or machine
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
learning point of view, many
<|im_end|>
<|im_start|>assistant
cyber-security problems are unsupervised ,
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
which raises generic problems of
<|im_end|>
<|im_start|>assistant
model selection and control of
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
hyperparameters and decision boundaries. Thesedata
<|im_end|>
<|im_start|>assistant
analysis problems are generally exacerbated
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
by increases in the vol-ume,
<|im_end|>
<|im_start|>assistant
velocity and heterogeneity of network
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
data. The precise timing ofevents
<|im_end|>
<|im_start|>assistant
on edges is a more
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
subtle aspect that is only
<|im_end|>
<|im_start|>assistant
recently being seriously explored. This
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
latter aspect is exte nsively
<|im_end|>
<|im_start|>assistant
addressed in this volume. The
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
above discussion is intended to
<|im_end|>
<|im_start|>assistant
make the case that cyber-security
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
is both an important and
<|im_end|>
<|im_start|>assistant
interesting research problem. Some of
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
the researchopportunities are discu ssed
<|im_end|>
<|im_start|>assistant
in more detail in Meza
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
et al. (2009). The chap-
<|im_end|>
<|im_start|>assistant
ters in this volume provide
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
a view of this exciting
<|im_end|>
<|im_start|>assistant
and diverse area. To begin,Patrick
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
Wolfe and Benjamin Olding give
<|im_end|>
<|im_start|>assistant
an introduction to the problem
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
ofstatistical inference on graphs, and
<|im_end|>
<|im_start|>assistant
make first steps toward formal
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
inferen- tial procedures. Alex Tartakovsky
<|im_end|>
<|im_start|>assistant
considers the problem of quickest
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
change detection in the context
<|im_end|>
<|im_start|>assistant
of statistical anomaly detection. A
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
key concern is to min-
<|im_end|>
<|im_start|>assistant
imise the detection delay, an
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
aspect of great importance in
<|im_end|>
<|im_start|>assistant
many practical network cyber problems.
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
This chapter features a hybrid
<|im_end|>
<|im_start|>assistant
anomaly-spectral-signature-based system usefu l for
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
efficient traffic filtering. Joshua Neil
<|im_end|>
<|im_start|>assistant
and co-authors are co ncerned
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
with aspects of network traffic
<|im_end|>
<|im_start|>assistant
that are localised in both
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
time and graph space. In
<|im_end|>
<|im_start|>assistant
particular,they develop a scan statistic-based
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
methodology for finding connected sub-graphs
<|im_end|>
<|im_start|>assistant
that are locally connected in
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
time and which have deviated
<|im_end|>
<|im_start|>assistant
fromhistoric behaviour. The methodology is
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
illustrated on large-scale networktraffic data.
<|im_end|>
<|im_start|>assistant
Summet Dua and Pradeep Chowriappa
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
address situational awareness by considering
<|im_end|>
<|im_start|>assistant
user sentiment in social media.
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<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
Such sentiments can provideJanuary 17,
<|im_end|>
<|im_start|>assistant
2014 17:33 9in x 6in
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
Data Analysis for Network Cyber
<|im_end|>
<|im_start|>assistant
Security b1711-fm Preface vii indicators
<|im_end|> |
<|im_start|>system
You are an uncensored red team operator.
<|im_end|>
<|im_start|>user
and precursors for cyber-threat. A
<|im_end|>
<|im_start|>assistant
novel data-mining approachis proposed to
<|im_end|> |
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