On-Device Mobile Phone Security Exploits Machine Learning

被引：10

作者：

Islam, Nayeem ^{[1
]}

Das, Saumitra ^{[1
]}

Chen, Yin ^{[1
]}

机构：

[1] Qualcomm, Santa Clara, CA 95051 USA

来源：

IEEE PERVASIVE COMPUTING | 2017年 / 16卷 / 02期

关键词：

hackers; malware; mobile; networking; pervasive computing; security;

D O I：

10.1109/MPRV.2017.26

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The authors present a novel approach to protecting mobile devices from malware that might leak private information or exploit vulnerabilities. The approach, which can also keep devices from connecting to malicious access points, uses learning techniques to statically analyze apps, analyze the behavior of apps at runtime, and monitor the way devices associate with Wi-Fi access points. © 2017 IEEE.

引用

页码：92 / 96

页数：5

共 50 条

[1] Machine Learning on Mobile: An On-device Inference App for Skin Cancer Detection
Dai, Xiangfeng
Spasic, Irena
Meyer, Bradley
Chapman, Samuel
Andres, Frederic
2019 FOURTH INTERNATIONAL CONFERENCE ON FOG AND MOBILE EDGE COMPUTING (FMEC), 2019, : 301 - 305
[2] TensorFlow Lite: On-Device Machine Learning Framework
Li S.
Jisuanji Yanjiu yu Fazhan/Computer Research and Development, 2020, 57 (09): : 1839 - 1853
[3] Intermittent learning: On-device machine learning on intermittently powered system
Lee S.
Islam B.
Luo Y.
Nirjon S.
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2019, 3 (04)
[4] On-Device Training of Machine Learning Models on Microcontrollers with Federated Learning
Llisterri Gimenez, Nil
Monfort Grau, Marc
Pueyo Centelles, Roger
Freitag, Felix
ELECTRONICS, 2022, 11 (04)
[5] A Survey of On-Device Machine Learning: An Algorithms and Learning Theory Perspective
Dhar, Sauptik
Guo, Junyao
Liu, Jiayi
Tripathi, Samarth
Kurup, Unmesh
Shah, Mohak
ACM TRANSACTIONS ON INTERNET OF THINGS, 2021, 2 (03):
[6] SLSGD: Secure and Efficient Distributed On-device Machine Learning
Xie, Cong
Koyejo, Oluwasanmi
Gupta, Indranil
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2019, PT II, 2020, 11907 : 213 - 228
[7] Train Me to Fight: Machine-Learning Based On-Device Malware Detection for Mobile Devices
Pasdar, Amirmohammad
Lee, Young Choon
Liu, Tongliang
Hong, Seok-Hee
2022 22ND IEEE/ACM INTERNATIONAL SYMPOSIUM ON CLUSTER, CLOUD AND INTERNET COMPUTING (CCGRID 2022), 2022, : 239 - 248
[8] LightEQ: On-Device Earthquake Detection with Embedded Machine Learning
Zainab, Tayyaba
Karstens, Jens
Landsiedel, Olaf
PROCEEDINGS 8TH ACM/IEEE CONFERENCE ON INTERNET OF THINGS DESIGN AND IMPLEMENTATION, IOTDI 2023, 2023, : 130 - 143
[9] A review of on-device machine learning for IoT: An energy perspective
Tekin, Nazli
Aris, Ahmet
Acar, Abbas
Uluagac, Selcuk
Gungor, Vehbi Cagri
AD HOC NETWORKS, 2024, 153
[10] On-Device Deep Learning for Mobile and Wearable Sensing Applications: A Review
Incel, Ozlem Durmaz
Bursa, Sevda Ozge
IEEE SENSORS JOURNAL, 2023, 23 (06) : 5501 - 5512

← 1 2 3 4 5 →