Faculty Candidate: Jonathon T. Giffin/University of Wisconsin-Madison Two Sides of Intrusion Detection: Strengthening and Attacking Model-Based Detectors in ACES 2.302
There is a signup schedule for th
is event.
Speaker Name/Affiliation: Jonathon T. Giffin/University o
f Wisconsin-Madison Computer Sciences Department
Talk Title: Two S
ides of Intrusion Detection: Strengthening and Attacking Model-Based Detect
ors
Date/Time: March 9 2006 at 11:00 a.m.
Coffee: 10:45 a.m
.
Location: ACES 2.302
Host: Vitaly Shmatikov
Talk A
bstract:
Model-based anomaly detectors discover computer system attacks
that cause malicious process execution. The detectors verify
system
calls invoked by a process against a model of expected
behavior. Execu
tion that deviates from the model indicates
that the process is under a
n attacker''s control. Existing
model-based detectors produce false ala
rms require manual
effort cause significant performance degradation
and miss
attacks masked as normal execution. I will present a strong <
br>usable intrusion detection system that addresses
many of these defici
encies.
I eliminate false positives and the need for manual work
by automatically extracting models using static binary program
analysi
s. Statically-constructed models historically traded
accuracy for dete
ction speed. I will show that my Dyck model
a new stack-deterministic
push-down automaton eliminates
the trade-off by reducing the complexit
y of accurate model
enforcement from cubic time to linear time. The Dyc
k model
pushes model-based detection into the realm of real-world
f
easibility.
I then evaluate the ability of a program model to detect
intrusions. I find undetected attacks: malicious system
call seque
nces erroneously allowed by a model as valid execution.
Using model-che
cking I automatically discover attacks previously
found only with manu
al inspection of a program model. These
undetected attacks demonstrate<
br>deficiencies of model-based detection that future research
will need
to address.
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