Titlebook: Data and Applications Security and Privacy XXXIV; 34th Annual IFIP WG Anoop Singhal,Jaideep Vaidya Conference proceedings 2020 IFIP Intern

Obsolescent

书目名称Data and Applications Security and Privacy XXXIV影响因子(影响力)




书目名称Data and Applications Security and Privacy XXXIV影响因子(影响力)学科排名




书目名称Data and Applications Security and Privacy XXXIV网络公开度




书目名称Data and Applications Security and Privacy XXXIV网络公开度学科排名




书目名称Data and Applications Security and Privacy XXXIV被引频次




书目名称Data and Applications Security and Privacy XXXIV被引频次学科排名




书目名称Data and Applications Security and Privacy XXXIV年度引用




书目名称Data and Applications Security and Privacy XXXIV年度引用学科排名




书目名称Data and Applications Security and Privacy XXXIV读者反馈




书目名称Data and Applications Security and Privacy XXXIV读者反馈学科排名

Culmination

braggadocio

homeostasis

insipid

K. Michielsen,H. De Raedt,T. Kawakatsuaudulent calls at the moment of their establishment, thereby preventing IRSF from happening. Specifically, we investigate the use of Isolation Forests for the detection of frauds before calls are initiated and compare the results to an existing industrial post-mortem anti-fraud solution.

commodity

G. Korniss,P. A. Rikvold,M. A. Novotnybehavior of installed applications, however, the methods suggested had limited accuracy. In this study, we propose a machine learning-based method for detecting PUAs. Our approach can be applied on the target endpoint directly and thus can provide protection against PUAs in real-time.

commodity

Managing Secure Inter-slice Communication in 5G Network Slice Chainsd properties that the Network Slice Chain must comply with in order to be chosen as a valid path for the traffic to flow through. This way, it respects security constraints and assures inter-slice communication obeying the rules stated in the policy.

Hearten

Provably Privacy-Preserving Distributed Data Aggregation in Smart Gridst towards the system, we model the concept and provide a formal proof of its confidentiality properties. We discuss the attacker models of colluding and non-colluding adversaries on the data flow and show how our scheme mitigates these attacks.

Constitution

Mnemonics

PUA Detection Based on Bundle Installer Characteristicsbehavior of installed applications, however, the methods suggested had limited accuracy. In this study, we propose a machine learning-based method for detecting PUAs. Our approach can be applied on the target endpoint directly and thus can provide protection against PUAs in real-time.