Machine learning–based cyber attacks targeting on controlled information: A survey

Y Miao, C Chen, L Pan, QL Han, J Zhang… - ACM Computing Surveys …, 2021 - dl.acm.org
Stealing attack against controlled information, along with the increasing number of
information leakage incidents, has become an emerging cyber security threat in recent …

The role of the adversary model in applied security research

Q Do, B Martini, KKR Choo - Computers & Security, 2019 - Elsevier
Adversary models have been integral to the design of provably-secure cryptographic
schemes or protocols. However, their use in other computer science research disciplines is …

[PDF][PDF] JavaScript Template Attacks: Automatically Inferring Host Information for Targeted Exploits.

M Schwarz, F Lackner, D Gruss - NDSS, 2019 - attacking.systems
Today, more and more web browsers and extensions provide anonymity features to hide
user details. Primarily used to evade tracking by websites and advertisements, these …

Android {SmartTVs} vulnerability discovery via {log-guided} fuzzing

Y Aafer, W You, Y Sun, Y Shi, X Zhang… - 30th USENIX Security …, 2021 - usenix.org
The recent rise of Smart IoT devices has opened new doors for cyber criminals to achieve
damages unique to the ecosystem. SmartTVs, the most widely adopted home-based IoT …

[PDF][PDF] Post-GDPR Threat Hunting on Android Phones: Dissecting OS-level Safeguards of User-unresettable Identifiers.

MH Meng, Q Zhang, G Xia, Y Zheng, Y Zhang, G Bai… - NDSS, 2023 - baigd.github.io
Ever since its genesis, Android has enabled apps to access data and services on mobile
devices. This however involves a wide variety of user-unresettable identifiers (UUIs), eg, the …

DNN model architecture fingerprinting attack on CPU-GPU edge devices

K Patwari, SM Hafiz, H Wang… - 2022 IEEE 7th …, 2022 - ieeexplore.ieee.org
Embedded systems for edge computing are getting more powerful, and some are equipped
with a GPU to enable on-device deep neural network (DNN) learning tasks such as image …

Magneticspy: Exploiting magnetometer in mobile devices for website and application fingerprinting

N Matyunin, Y Wang, T Arul, K Kullmann… - Proceedings of the 18th …, 2019 - dl.acm.org
Recent studies have shown that aggregate CPU usage and power consumption traces on
smartphones can leak information about applications running on the system or websites …

Magspy: Revealing user privacy leakage via magnetometer on mobile devices

Y Fu, L Yang, H Pan, YC Chen… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Various characteristics of mobile applications (apps) and associated in-app services can
reveal potentially-sensitive user information; however, privacy concerns have prompted third …

Hidden in plain sight: Exploring privacy risks of mobile augmented reality applications

SM Lehman, AS Alrumayh, K Kolhe, H Ling… - ACM Transactions on …, 2022 - dl.acm.org
Mobile augmented reality systems are becoming increasingly common and powerful, with
applications in such domains as healthcare, manufacturing, education, and more. This rise …

See no evil: phishing for permissions with false transparency

GS Tuncay, J Qian, CA Gunter - 29th USENIX Security Symposium …, 2020 - usenix.org
Android introduced runtime permissions in order to provide users with more contextual
information to make informed decisions as well as with finer granularity when dealing with …