Defence & Military
❯
Cybersecurity
❯Non-intrusive detection of malware
Non-intrusive detection of malware
For:
General users of Internet-connected devices
Scope:
Build an AI solution that detects malware activities.
Goal:
Other
Automated threat enrichment intelligence in Cyber security
Goal:
Improve Operation Efficiency
AI (swarm intelligence) solution for attack detection in IoT environment
For:
End users of smart metering, utility companies
Scope:
Anomaly-based attack detection in an IoT environment using swarm
Intelligence.
Goal:
Other
Non-intrusive detection of malware
For:
General users of Internet-connected devicesGoal:
OtherProblem addressed
Use ML to flag activities induced by malware without access to personal data on
local devices.
Scope of use case
Build an AI solution that detects malware activities.
Description
Off the shelf malware detection software has two limitations.
One is that it is limited by the security features created by
mobile device manufacturers, in particular for Android
devices. And the second is that the software is necessary to
have access to device owners' personal data like name,
phone number, international mobile equipment identity
(IMEI) or authentication credentials. As such, a non-intrusive
ML-based detection is a more sustainable and better
accepted malware detection service, which can flag out
anomalies in the local devices generic activities like battery
usage, data use, location services, camera or microphone.
Machine Learning
AI: Understand