Biblio

The robustness of supply chain networks (SCNs) against sequential topology attacks is significant for maintaining firm relationships and activities. Although SCNs have experienced many emergencies demonstrating that mixed failures exacerbate the impact of cascading failures, existing studies of sequential attacks rarely consider the influence of mixed failure modes on cascading failures. In this paper, a reinforcement learning (RL)-based sequential attack strategy is applied to SCNs with cascading failures that consider mixed failure modes. To solve the large state space search problem in SCNs, a deep Q-network (DQN) optimization framework combining deep neural networks (DNNs) and RL is proposed to extract features of state space. Then, it is compared with the traditional random-based, degree-based, and load-based sequential attack strategies. Simulation results on Barabasi-Albert (BA), Erdos-Renyi (ER), and Watts-Strogatz (WS) networks show that the proposed RL-based sequential attack strategy outperforms three existing sequential attack strategies. It can trigger cascading failures with greater influence. This work provides insights for effectively reducing failure propagation and improving the robustness of SCNs.

As the increasing demands of social services, unmanned aerial vehicles (UAVs)-assisted networks promote the promising prospect for implementing high-rate information transmission and applications. The sensing data can be collected by UAVs, a large number of applications based on UAVs have been realized in the 5G networks. However, the malicious UAVs may provide false information and destroy the services. The 5G UAV communication systems face the security threats. Therefore, this paper develops a novel trust-based security scheme for 5G UAV communication systems. Firstly, the architecture of the 5G UAV communication system is presented to improve the communication performance. Secondly, the trust evaluation scheme for UAVs is developed to evaluate the reliability of UAVs. By introducing the trust threshold, the malicious UAVs will be filtered out from the systems to protect the security of systems. Finally, the simulation results have been demonstrated the effectiveness of the proposed scheme.

The group merging/splitting event is different to the joining/leaving events in which only a member joins or leaves group, but in the group merging/splitting event two small groups merge together into a group or a group is divided into two independent parts. Rekeying is an importance issue for key management whose target is to guarantee forward security and backward security in case of membership changes, however rekeying efficiency is related to group scale in most existing group key management schemes, so as to those schemes are not suitable to the applications whose rekeying time delay is limited strictly. In particular, multiple members are involved in the group merging/splitting event, thus the rekeying performance becomes a worried problem. In this paper, a high performance group merging/splitting group key management scheme is proposed based on an one-encryption-key multi-decryption-key key protocol, in the proposed scheme each member has an unique decryption key that is corresponding to a common encryption key so as to only the common encryption key is updated when the group merging/splitting event happens, however the secret decryption key still keeps unchanged. In efficiency aspect, since no more than a message on merging/splitting event is sent, at time the network load is reduced since only a group member’s key material is enough for other group members to agree a fresh common encryption key. In security aspect, our proposed scheme achieves the key management security requirements including passive security, forward security, backward security and key independence. Therefore, our proposed scheme is suitable to the dynamitic networks that the rekeying time delay is limited strictly such as tolerate delay networks.