EvoSec 2025W Lecture 11

Lecture 11
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For Thursday
 - I'll set up an assignment for submitting PDFs for slides
   (1-3 slides at most), this is optional
 - whatever you present is not binding, you can change it!
 - this is a participation grade, so it is a grade for effort

Questions
 - where is tech like that described in today's papers being used?
   - how close is it?
 - how about, trying to detect attackers when we don't know exactly how they will attack
   - so, catching novel attacks as well as regular ones

Candidates
 - anomaly-based network monitoring
   - not common
 - spam detection
   - but you have examples of spam and ham (regular msgs)
   - and still doesn't work great against novel spam
 - ML applied to malware detection
   - but that isn't real time and is mostly focused on classifying samples

There isn't much!

Note that this work is not obscure
 - the "evolution of system call monitoring" was an invited paper
 - sense of self received a "test of time" award at IEEE SSP

All of you: WHY?

 - too many false positives
 - takes too long to create "normal" databases?
 - mimicry attacks are too easy?
 - normal can change
 - cost
 - graduated responses are not useful in fast computers
 - logistical difficulty in replacing current systems
 - lacks scalability
 - not enough work done to make it commercially viable
 - not adaptable/robust enough to justify changes
 - industry cannot sell it
 - too many false positives, waste of employee time
 - lacks adaptability, unable to adapt to changes over time
 - frequency of re-training or learning
 - experimental environment is complex, situation different for different OSs
 - local, system specific means it cannot scale/extend to other systems


None of the above is true
 - the basic tech works, and plenty of scope for improvement!

But what did the evolution paper say?
 - different methods for monitoring system calls
   - but they are all much slower, and almost no gain in accuracy
 - applied to other systems
   - but barely followed up on
 - bit of work on use in real time, automated response
   - but that's basically my work

HUGE amounts of follow-up work, almost no progress

Do you disagree?

I changed much of my focus to theory because I couldn't understand what was happening

What would you like to learn more about?

 - other systems I've built
 - limitations of past systems I've built
 - more alife, evolutionary systems
 - game theory in security
 - anomaly detection evasion techniques (mimicry attacks)
 - how to apply these ideas to crytography?
 - more bio-inspired systems
 - practical implementations of adaptive security, why aren't we doing this?
 - system call monitoring using arguments
 - defense mechanisms to address evolving threats
 - human interactions with autonomous security systems
 - programming language vuln detection
 - specific attack mechanisms to be addressed
 - new immune system security research
 - evolution of cloud security systems - diversity, selection?