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Security & the Infinite Capacity to Rationalize
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DHorse2
DHorse2,
 User Rank: Strategist
8/7/2019 | 8:32:12 PM
Rationalization is lazy?
No, it isn't. If you are going to solve this issue the first requirement is to understand it. And... well... that's a lazy, overly simplistic view as well as incorrect. Human thought reflects our nature as rapid response probabilistic state prediction biologicals. That was a lot of words. However note that neither logic nor laziness was in there. Logic is something applied selectively, judiciously and sparingly. Now, while agree that laziness is the mother of invention, thoughts are fleshed out emotions just as emotions are primitive thoughts. Your choice is made early and emotionally. Rationalization is how you justify it variously. That my friends is hard work!
tdsan
tdsan,
 User Rank: Ninja
8/6/2019 | 3:47:04 PM
Wonderful commentary

I agree with the statements made, we need to look at security from a logic standpoint where we start looking at the attacks from a mathematical perspective. For example, most of the files that come across are associated with a hash and the locations on the filesystem are related to inodes and hashes. We need to start looking at the file as a number, baseline all the numbers on the filesystem. The files can be identified by the changes associated with specific system files (pgp, kernel, binaries), that information is then gathered by creating an index; from the index we should be able to identify the changes in files, directories and file-types based on the number associated with that specific file (MD5 or SHA256). There is only a finite number of files that are essential to the system's function, once we isolate the files, then we can start to create an algorithm to index files based on purpose and location (SELinux does something very similar - files, directories, filesystem, policies, characteristics).

This will help with the machine learning and identification process because we will be able to identify the change(s) easier than using existing methods.




Some companies are doing this (pattern matching), we just need to do this type of analyis at the atomic level (using inodes and hashes), by developing equations to identify changes based on patterns or relationships, we can create ML structures that look at the system as an algorithic pattern (data flows).


Just a thought.


T


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