Network moving target defense technology can effectively defend against attacker monitoring of the service. The technology makes it more difficult for attackers to attack and can ensure secure communication for services. However, there may be multiple network attacks in the network. As a result, there may be security problems with the trustworthiness of the network resource mutation space required for network moving target defense technology. The focus of current researches is mostly on the mutation timing and cost optimization of the resource mutation space. It may lead to the possibility that the resources in the resource mutation space have been already under network attacks. In this paper, we propose a hybrid routing mutation mechanism based on mutation cost and resource trustworthiness in SDN networks. The mechanism is able to evaluate the routing mutation space selected by the routing-based network moving target defense technology. In terms of both mutation cost and resource trustworthiness, the optimal weighting ratio of the two factors will be to discovered. Simulation results show that the proposed mechanism can effectively enhance the ability of the routing mutation space to avoid attacked nodes and links and improve the transmission success rate of services.

A Hybrid Routing Mutation Mechanism based on Mutation Cost and Resource Trustworthiness in Network Moving Target Defense

Location-based service recommendations usually need to collect and analyze the location information of trajectories generated by users with smart phones or wearable devices. It is easy to cause the location privacy leaks. The current location privacy protection methods usually confuse the adversary by adding fake locations into real trajectories to achieve the goal of privacy protection. However, these methods fail to consider the utility of user trajectories in service recommendations. In this paper, we propose a privacy-preserving trajectory generation algorithm based on service semantic similarity. To improve the utility of privacy-preserving trajectories for service recommendations, the algorithm constructs a series of service semantic grid maps and generates fake individuals with privacy-preserving trajectories considering both utility and privacy. Simulation results show that the proposed algorithm can effectively hide the locations in real trajectories of individuals and obtain higher effectiveness for service recommendations.

Yibo Gao

Papers

A Hybrid Routing Mutation Mechanism based on Mutation Cost and Resource Trustworthiness in Network Moving Target Defense

Privacy-preserving Trajectory Generation Algorithm Considering Utility based on Semantic Similarity Awareness