Summary Scour around bridge foundations is regarded as one of the predominant causes of bridge failures. Traditional methods primarily employ underwater instruments to detect bridge scour depths, which thus have difficulties in instrument installations and operations. The concept of scour detection derived from vibration‐based damage detection has been explored in recent years to address such difficulties by investigating the natural frequency spectrum of a bridge or a bridge component. This paper presents a comprehensive review of existing studies on scour detection using the natural frequency spectrum of a bridge or a bridge component. Underlying mechanisms, laboratory and field tests, numerical studies, and data processing schemes are reviewed to summarize the state of the art, which are absent but urgently needed. Updates on recently developed scour monitoring sensors are also provided to complement the introduction. Based on the review, in‐depth discussions in existing studies are made regarding a few controversial and unsolved issues to shed light on future research, highlighting issues such as the soil–structure interaction, locations of the sensor installation, and the influence of shapes of scour holes.

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With the rapid development of networks, network security is a serious problem. To evaluate a network accurately, this paper proposes a network risk evaluation method based on a differential manifold (DM) and research on traditional methods. The DM divides the network risk evaluation into network structure risk and network behavior risk evaluations. Network structure risk evaluates the network identity, and network behavior risk evaluates the attack and defense of the network. Network assets and asset vulnerabilities characterize a network, and the analytic hierarchy process (AHP) and the Common Vulnerability Scoring System (CVSS) are combined to evaluate the network identity. Network behavior causes high-dimensional indicator changes, and DMs are used to measure network behavior. To examine the effectiveness and accuracy of DMs, two experiments were performed. The experimental results show that the DM method is valid and accurate for evaluating network risk.INDEX TERMS Network risk evaluation, differential manifold, Riemannian manifold, analytic hierarchy process, common vulnerability scoring system.

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