Hidden data attack detection method based on fog computing and layered trust evaluation mechanism

Abstract

The invention provides a hidden data attack detection method based on fog computing and a layered trust evaluation mechanism, and belongs to the field of network information safety, specifically a method for guaranteeing that node behaviors in wireless sensor networks (WSNs) are credible through the layered trust evaluation mechanism based on the fog computing, guaranteeing that nodes are credibleat a data level base on the above, i.e., detecting the attack performance of hidden data. According to the invention, the method enables the computing and storage task in the trust evaluation mechanism to be transferred to a fog layer, can remarkably reduce the network resources consumed by the trust evaluation mechanism, can maintain the network performances in a better way, and is superior in the expansibility of the trust evaluation mechanism. Meanwhile, the method can be applied to the dynamic and stationary WSNs, guarantees the trust state of the sensing nods at the data level, and prevents the hidden data attach from causing the economic loss of a sensing cloud application.

Description

technical field [0001] The invention relates to the technical field of network information security, and more specifically, to a hidden data attack detection method based on fog computing and a hierarchical trust evaluation mechanism in a sensor cloud. Background technique [0002] Sensing cloud is a research hotspot now, but it still has some security problems, such as internal attack. Internal attack refers to a security threat in which malicious nodes / devices enter the sensor cloud with legitimate identities and may launch malicious attacks. Since malicious attacks can reduce network performance, reduce network life, destroy network functions, and cause network service errors, it will cause greater harm to the development of the sensor cloud and social and economic benefits. Among these internal attacks, there is a special attack method, which is the hidden data attack. Hidden data attacks refer to malicious nodes / devices that behave normally during the network life cyc...

AI Technical Summary

Problems solved by technology

However, these two architectures have different disadvantages: the establishment of the first kind of trust is local, it cannot guarantee the trustworthiness of nodes / devices from a global perspective, and it is easily affected by environmental factors

The second type of trust is established at a higher level, but it increases the burden on intermediate devices in computing, storage, communication, etc.

These two also have some common shortcomings: they are not suitable for wireless sensor networks WSNs with mobility; they cannot guarantee the security and trustworthiness of WSNs at the sensory data level (the trust evaluation mechanism based on sensory data needs to consume more network resources, which are less suitable for implementation in WSNs)

[0004] However, the cloud is far away from WSNs and has a certain delay. Obviously, it is not suitable for data-level trust evaluation in the cloud.

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