Apk2vec : semi-supervised multi-view representation learning for profiling Android applications
Building behavior profiles of Android applications (apps) with holistic, rich and multi-view information (e.g., incorporating several semantic views of an app such as API sequences, system calls, etc.) would help catering downstream analytics tasks such as app categorization, recommendation and malw...
Saved in:
Main Authors: | Narayanan, Annamalai, Soh, Charlie, Chen, Lihui, Liu, Yang, Wang, Lipo |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2020
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/142658 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Post2Vec: Learning distributed representations of stack overflow posts
by: XU, Bowen, et al.
Published: (2022) -
Build2Vec: Building Representation in Vector Space
by: Abdelrahman, Mahmoud, et al.
Published: (2021) -
Dual semi-supervised convex nonnegative matrix factorization for data representation
by: Peng, Siyuan, et al.
Published: (2022) -
Info2vec: an aggregative representation method in multi-layer and heterogeneous networks
by: Yang, Guoli, et al.
Published: (2022) -
TOWARDS CONCISE REPRESENTATION LEARNING ON DEEP NEURAL NETWORKS
by: YUAN LI
Published: (2021)