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# machine-learning

4 results found across projects, research, and posts.

2019
project

Trapdroid

Trapdroid is a bare-metal Android malware analysis framework that runs unknown apps on real phones, captures their kernel-level behavior, and classifies them as malicious or benign with over 98% accuracy.

+17
#android#arch-linux#cnn#deep-learning#elasticsearch#flask#gradient-boosting#lkm#machine-learning#malware#mongodb#python#random-forest#raspberry-pi#scapy#selinux#svm
2016
project

Leiurus

AI-powered vulnerability scanner that fingerprints pages and prioritizes attack vectors.

+6
#dast#fuzzing#machine-learning#penetration-testing#python#vulnerability-assessment
2020
research

Towards prioritizing vulnerability testing

QRS-C 2020

A machine learning approach to accelerate vulnerability scanning by prioritizing security tests based on web page features.

+7
#automated-testing#cwe#machine-learning#neural-network#test-prioritization#vulnerability#vulnerability-assessment
2019
research

Bare-metal android malware behavior analysis framework

ICACT 2019

A scalable dynamic malware analysis framework focused on capturing unified behavior profiles of Android applications by analyzing them on physical devices in real-time.

+8
#android#bare-metal#binder#dynamic-analysis#lkm#machine-learning#malware#pmu
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