Titlebook: Computer Security; ESORICS 2018 Interna Sokratis K. Katsikas,Frédéric Cuppens,Christos Kal Conference proceedings 2019 Springer Nature Swit

無法修復

書目名稱Computer Security影響因子(影響力)




書目名稱Computer Security影響因子(影響力)學科排名




書目名稱Computer Security網絡公開度




書目名稱Computer Security網絡公開度學科排名




書目名稱Computer Security被引頻次




書目名稱Computer Security被引頻次學科排名




書目名稱Computer Security年度引用




書目名稱Computer Security年度引用學科排名




書目名稱Computer Security讀者反饋




書目名稱Computer Security讀者反饋學科排名

Adjourn

Improving SIEM for Critical SCADA Water Infrastructures Using Machine Learninged in building and evaluating the model. The model classifies different anomaly events including hardware failures (e.g. sensor failures), sabotage and cyber-attacks (e.g. DoS and Spoofing). Unlike other detection systems, our proposed work helps in accelerating the mitigation process by notifying t

追蹤

修飾語

SDN-Enabled Virtual Data Diodelution was evaluated by means of a prototype implementation built on top of a distributed SDN controller and designed for multi-tenant network environments. This prototype, which was developed with a focus in performance and availability quality attributes, is able to deploy a virtual data diode in

GEST

Run-Time Monitoring of Data-Handling Violationsvocations) expressed by Data Subjects regarding use of their personal data, and also violations of any related obligations that might be placed upon data handlers (data controllers and processors). Our approach seeks to enable detection of both accidental and malicious compromises of privacy propert

吸氣

吸氣

F. Bouvier,A. S. Mialoundama,B. Camaranctionality which will be based on attribute aggregation. This is structured in accordance to a risk-based framework, which has been developed in order to aggregate the risk values that the individual attributes encapsulate into a unified risk value. These architectural enhancements are utilized in

Ointment

平項山

The High-Affinity Choline Uptake Systemvocations) expressed by Data Subjects regarding use of their personal data, and also violations of any related obligations that might be placed upon data handlers (data controllers and processors). Our approach seeks to enable detection of both accidental and malicious compromises of privacy propert

FIN