Gullet
发表于 2025-3-21 18:25:01
书目名称Decision and Game Theory for Security影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0264324<br><br> <br><br>书目名称Decision and Game Theory for Security影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0264324<br><br> <br><br>书目名称Decision and Game Theory for Security网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0264324<br><br> <br><br>书目名称Decision and Game Theory for Security网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0264324<br><br> <br><br>书目名称Decision and Game Theory for Security被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0264324<br><br> <br><br>书目名称Decision and Game Theory for Security被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0264324<br><br> <br><br>书目名称Decision and Game Theory for Security年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0264324<br><br> <br><br>书目名称Decision and Game Theory for Security年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0264324<br><br> <br><br>书目名称Decision and Game Theory for Security读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0264324<br><br> <br><br>书目名称Decision and Game Theory for Security读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0264324<br><br> <br><br>
Little
发表于 2025-3-21 22:36:56
http://reply.papertrans.cn/27/2644/264324/264324_2.png
Galactogogue
发表于 2025-3-22 03:19:34
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/d/image/264324.jpg
GNAT
发表于 2025-3-22 07:06:04
http://reply.papertrans.cn/27/2644/264324/264324_4.png
刚开始
发表于 2025-3-22 11:13:27
https://doi.org/10.1007/978-90-313-9129-5ic nature of losses. It is recognised that this information asymmetry may lead to a “market for lemons” in which suppliers face no incentive to provide higher quality products. Some security vendors have begun to offer cyber-warranties—voluntary ex-ante obligations to indemnify the customer in the e
Rankle
发表于 2025-3-22 15:15:17
http://reply.papertrans.cn/27/2644/264324/264324_6.png
Rankle
发表于 2025-3-22 20:04:18
https://doi.org/10.1007/978-90-313-9129-5llicit machine learning classification task. Alice wants Bob (a machine learning system) to learn the task. However, sending either the training set or the trained model to Bob can raise suspicion if the communication is monitored. Training set camouflage allows Alice to compute a second training se
CHASE
发表于 2025-3-22 21:38:41
http://reply.papertrans.cn/27/2644/264324/264324_8.png
ineffectual
发表于 2025-3-23 04:09:33
https://doi.org/10.1007/978-90-313-9129-5 architecture or augmenting the training set with adversarial examples, but both have inherent limitations. Motivated by recent research that shows outliers in the training set have a high negative influence on the trained model, we studied the relationship between model robustness and the quality o
CRAB
发表于 2025-3-23 06:56:06
http://reply.papertrans.cn/27/2644/264324/264324_10.png