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首页> 外文期刊>International journal of information privacy, security and integrity >Using non-verbal social signals and degree centrality to optimise a covert actor's detection scheme for a healthy networked community
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Using non-verbal social signals and degree centrality to optimise a covert actor's detection scheme for a healthy networked community

机译：使用非语言社交信号和程度中心性来优化隐蔽演员的检测方案，以建立健康的网络社区

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摘要

Passive attacks are of the nature of eavesdropping on, monitoring of, transmissions where the attacker's goal is to unnoticeably obtain the information in transmission. Passive attacks are difficult to detect and therefore hard to prevent. The main focus for most research in this area has been on preventing the attacks rather than detecting the attacker for example by data encryption. But encryption by itself falls short because passive attack can occur in more ways than just observing exposed data. Encryption is also not always applicable for example in open wireless communication protocols. With these observations, we aim to design a scheme that reduces such attackers' capability. We introduce the non-verbal social signal deception detection in the investigative module while we optimise the scheme by putting in consideration a participant's centrality given the topology. The results are an intuitive scalable and optimised scheme that detects, investigates, and expels the guilty suspects.
机译：被动攻击具有窃听，监视传输的性质，攻击者的目标是显着地获取传输中的信息。被动攻击很难检测到，因此很难预防。该领域大多数研究的主要重点是防止攻击，而不是例如通过数据加密来检测攻击者。但是，加密本身就不够用，因为被动攻击可能以多种方式发生，而不仅仅是观察公开的数据。加密也不总是适用于例如开放无线通信协议中。基于这些观察，我们旨在设计一种降低此类攻击者能力的方案。我们在调查模块中介绍了非语言社交信号欺骗检测，同时通过考虑给定拓扑的参与者的中心性来优化方案。结果是一种直观的可扩展且经过优化的方案，可检测，调查和驱逐有罪嫌疑人。

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