-=[ Learning to Detect and Classify Malicious Executables in the Wild ]=-

year 2006
by J. Zico Kolter, Marcus A. Maloof
at n/a
type paper
hash a2317e962e66762fe22945d7c6a5cc784ed6b8fb3576666a0f6321a614ad94f2

-=[ Building a Machine Learning Classifier for Malware Detection ]=-

year 2014
by Zane Markel and Michael Bilzor
at n/a
type paper
hash ecee915b722e5a7e81e458a72f66f9a386fd70d98b1f206c86a73c8e0715eb40

-=[ Automatic classification of object code using machine learning ]=-

year 2015
by John Clemens
at n/a
type paper
hash 6bd22b061dee5a79c70fc2d4b1490268b7fc5943ccc09b8d016003a2ee3f5936

-=[ Automatic classification of object code using machine learning ]=-

year 2015
by John Clemens
at n/a
type slides
hash 24d468f36ca300727738ae312e8ee110d525a8772d7fb34cdc09eb53efc364fe

-=[ ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R ]=-

year 2017
by Marvin N. Wright, Andreas Ziegler
at n/a
type paper
hash b0a45a456f72a1692a93b2ae934b22ec277d0eec855245cf32ceed450a8e5d88

-=[ Applied Machine Learning & Data Science for Cybersecurity ]=-

year 2018
by Austin Taylor
at n/a
type slides
hash 2867fa0118348208554eb47e5121c84f8ab018b667a4b66837f0b1bf8150acaa

-=[ Binary Similarity Detection Using Machine Learning ]=-

year 2018
by Noam Shalev, Nimrod Partush
at n/a
type paper
hash b4fb494a8103619b233828064be1b4476388996347005fb079f0058621504554

-=[ ALFRED, FIND THE ATTACKER - A primer on AI & ML applications in the IT Security Domain ]=-

year 2019
by Matthias Meidinger
at Troopers
type slides
hash 6c8042be54f8c0265e5cb12deb0470f8cbef622578ce98a2827f639152927519

-=[ Machine Learning Implementation Security in the Wild ]=-

year 2019
by Denis Kolegov, Anton Nikolaev
at POC
type slides
hash 94650f3e7602b45c73d0b8ff4b872ebc81692c4a1330beac37ad7d1336de86c2

-=[ Checking Defects in Deep Learning AI Models ]=-

year 2019
by Li,Kang & Zhang,Yan & Qian,Jiayu & Liu,Zhao
at POC
type slides
hash 27a9585a7ae447a785ea080a6c2f417e4174315f4bd3fadd80e5193dea5315e8