The QoS and privacy trade-off of adversarial deep learning: An evolutionary game approach-Reference-Cited by-同舟云学术

The QoS and privacy trade-off of adversarial deep learning: An evolutionary game approach

Published:2020-09 Issue: Volume:96 Page:101876
ISSN:0167-4048
Container-title:Computers & Security
language:en
Short-container-title:Computers & Security

Author:

Sun Zhe^ORCID,Yin Lihua,Li Chao,Zhang Weizhe,Li Ang,Tian Zhihong^ORCID

Funder

National Key R&D Program of China

Key-Area Research and Development Program of Guangdong Province

National Natural Science Foundation of China

Guangdong Province Universities and Colleges

Publisher

Elsevier BV

Subject

Law,General Computer Science

Reference46 articles.

1. The accuracy-privacy trade-off of mobile crowdsensing;Alsheikh;IEEE Commun. Mag.,2017

2. Convex Optimization;Boyd,2004

3. Stackelberg games for adversarial prediction problems;Bruckner,2011

4. Dasgupta, P., Collins, J.B. A survey of game theoretic approaches for adversarial machine learning in cybersecurity tasks. arXiv preprint arXiv:1912.02258, 2019.

5. Biddingin sealed-bid and English multi-attribute auctions;David;Decis. Support Syst.,2006

Cited by 15 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Game-theoretic analytics for privacy preservation in Internet of Things networks: A survey;Engineering Applications of Artificial Intelligence;2024-07

2. Ransomware Detection Model Based on Adaptive Graph Neural Network Learning;Applied Sciences;2024-05-27

3. Real-Time Ransomware Detection Method Based on TextGCN;2023 6th International Conference on Artificial Intelligence and Big Data (ICAIBD);2023-05-26

4. Fractional-Ant Lion Optimization Algorithm for Privacy Protection in Cloud with MapReduce Framework;Cybernetics and Systems;2023-01-20

5. A game-theoretic approach for federated learning: A trade-off among privacy, accuracy and energy;Digital Communications and Networks;2023-01