For the selective forwarding attack behavior generated by malicious nodes in wireless sensor networks, an efficient detection method is proposed. The simplified cloud model is introduced into the trust evaluation model, and the improved K/N voting algorithm is used to obtain the trust value of the target node. Then, the trust value of the target node is compared with the trust threshold to identify the attack node. The simulation results show that when the trust threshold is 0.8 and after 5 time periods, the proposed method can effectively detect the selective forwarding attack nodes, and it has high detection rate and low fault rate.

In order to deploy fault-tolerant Software-Defined Networks(SDN), many controllers must be physically distributed among different network devices. However, a large number of controllers bring huge costs, which limits severely the application of the fault-tolerant control plane to the real networks. In order to solve the above problems, the fault-tolerant control plane is analyzed and a mathematical model that covers all switches using the least number of controllers is constructed. Then, a heuristic controller placement algorithm based on the local search strategy is proposed to avoid the local optimal solution. The experimental results show that compared with other algorithms, the proposed algorithm can effectively reduce the number of required controllers while ensuring network fault tolerance requirements in different scale networks.

For the faultiness that the recent branch obfuscation method is only efficient on branch condition formed by integer comparison. The relations between the binary representation and big or small comparison of floats are analyzed. The idea that the floats in float interval has prefix matching relation with the prefix set which comes from the binary representation interval of the floats is proved. By protecting the prefix set with Hash function, and based on the comparison of prefix-Hash, a new branch obfuscation method which works well on the branch formed by float number comparison is proposed. The new obfuscation method is powerful on symbolic execution combating and obfuscation recovery combating. At last, the obfuscation proposed in this paper is confirmed to be practical, and is useful to be against symbolic execution and obfuscation recovery.

The change trend of multi-index of wheat reflects the deterioration state of storage quality, while the predicted multi-index data will produce large errors due to its correlation and interaction. For this reason, an improved Long Short-Term Memory and Generative Adversarial Network(LSTM-GAN) model is proposed. The deterioration trend of different time series data of multi-index is predicted by Long Short-Term Memory(LSTM) network, and the improved model may reduce comprehensive prediction error by using Generative Adversarial Network(GAN) according to the correlation of multi-index. Finally, the prediction results obtained by optimizing the objective function and model structure. The experimental analysis shows that the training sequence length and structural parameters of the optimization model can effectively reduce the error of the prediction result. The deterioration of wheat quality under certain conditions will increase the prediction error of multi-index. Therefore, the influence of environmental changes during storage period on multi-index data should be fully considered. The comprehensive error of the LSTM-GAN model is reduced by 9.745% compared with the LSTM prediction and lower than multiple comparison models, which can improve the prediction of wheat quality indexes.

The design of authentication protocol is a hot topic in the field of the security of Vehicular Ad hoc NETwork (VANET). There are security problems caused by key escrow in the existing authentication schemes. In order to solve this problem and achieve secure and efficient verification, an efficient pairing-free certificateless authentication  scheme with batch verification is proposed, in which the key of the vehicle is generated by the vehicle itself and a key generation center, which solves the problem that the key needs to be managed to the third party for maintenance. The bilinear pairing operation, one of the most complex operations in modern cryptography, is not used in the generation of vehicle’s signatures to reduce the computation cost of message verification. Unforgebility of the schemes against adaptively chosen-message and identity attack is proved under the difficulty of computing the discrete logarithm problem in the random oracle model to guarantee resistancy against modification and impersonation attacks, and has the characteristics of anonymity and traceability. Compared to the existing schemes, the proposed scheme is more efficient.

The transmission performance of nodes in the satellite Internet of Things(IoT) is limited due to the long-distance transmission and the power-constrained terminal. A collaborative beamforming technique is proposed based on the node selection algorithm to improve the transmission performance of nodes. An average far-field beampattern for collaborative beamforming is derived by considering the location information error in practical scenario. Furthermore, the difference between average beampattern and instantaneous beampattern is analyzed by the system parameters. On this basis, a node selection algorithm is proposed based on region grouping not only to meet the requirement of satellite link, but also to suppress the sidelobe. Simulation results show better performance of the proposed algorithm compared with the traditional node selection algorithms in the actural error model.

With the rapid development of the Internet of Things (IoT), Mobile Edge Computing (MEC) becomes increasingly effective in improving processing capacity and providing low-latency computing services. However, in the time-varying MEC-IoT environment, heterogeneous devices and applications cause serious challenges on efficient task offloading and resource allocation. A Distributed Dynamic Heterogeneous task offloading Methodology (D2HM) algorithm is proposed in this paper by exploiting game theory and Lyapunov optimization, which can achieves heterogeneous control and allocation of computation resources by dynamic quote price mechanism. Simulation results show that the proposed algorithm can meet the diverse computing needs of heterogeneous tasks and reduce the average delay of the system while ensuring network stability.

In the ultra-dense heterogeneous wireless network composed of heterogeneous cellular networks and wireless local area networks, vehicle terminals with variable speeds will face more frequent handovers, resulting in the deterioration of user’s Quality of Service (QoS). For the above problems, firstly, the Gauss Markov mobility model is used to predict the position of the vehicle terminal at the next moment, and the candidate network set that meets the terminal service quality is selected to make the intersection with the current candidate network set. Secondly, if the current access network is not in the intersection, the variable-step firefly algorithm is used to find the best network. Thirdly, the terminal that fails to switch due to the prediction error is migrated to the macro cellular to ensure the continuity of communication. Simulation results show that the proposed algorithm can reduce the frequent handoff phenomenon, such as ping pong handoff in the ultra-dense heterogeneous wireless network. Meanwhile, it can improve the user service quality and network throughput.

The physical-layer security transmission scheme based on Simultaneous Wireless Information and Power Transfer (SWIPT) and artificial noise-aided is proposed to solve the energy-constrained and information security issues upon the two-way untrusted relay networks. The Power Splitting (PS) strategy is adopted by the untrusted relay to assist the confidential communication, where a full-duplex jammer is assigned to send the artificial noise while harvesting energy, to ensure the system security. The PS factor is optimized to maximize the secrecy performance, and then the closed-form expressions of the secrecy sum-rate and optimal PS ratio are derived in the high signal-to-noise ratio regime. Besides, the impacts of the channel estimation error on the system security are analyzed for the imperfect channel state information. Simulation results validate the correctness of the theoretical derivation and demonstrate that the proposed transmission scheme based on PS strategy and friendly jammer outperforms that based on the Time Switching (TS) strategy or destination-aided jamming.

In the Device-to-Device (D2D) communication assisted Narrow Band Internet of Things (NB-IoT), in order to maximize the transmission success probability, the D2D relay device needs to reserve more communication time slots (multiple retransmissions can be allowed to increase the transmission success probability). However, this increases significantly the power consumption of the User Equipment (UE), especially in the case of poor channel conditions or severe interference. An optimization problem based on the relay and energy consumption models is constructed to seek a compromise between transmission success probability and energy consumption, and a communication slot optimal configuration algorithm based on dichotomy is proposed in this paper. The numerical results show that the larger number of reserved time slots can lead to an excessive increase in energy consumption without significantly increasing the transmission success probability. Compared with other algorithms such as multi-relay transmission, random relay transmission and 100% successful transmission, the proposed reserved time slot optimal configuration algorithm can obtain the least energy consumption and almost the highest transmission success probability (it is only lower than that under 100% successful transmission scheme).

A joint security routing and power optimization algorithm for wireless multi-hop Ad hoc network is proposed in an eavesdropping environment. Firstly, the Secrecy Outage Probability (SOP) and expressions of Connection Outage Probability (COP) are derived under the assumption that the distribution of the eavesdroppers follows the Poisson Cluster Process (PCP). Then, in view of minimizing COP with the constraint of SOP, the optimal transmission power of each hop is derived for any given path. Based on that, the optimal route from the source to the destination is obtained. The simulations on COP and SOP show that the derived theoretical results agree well with the Monte-Carlo simulations. It is also shown that the security performance of the proposed algorithm is close to that of exhaustive searching, and also outperforms the traditional method.

In view of the current deployment of the Service Function Chain (SFC), the failure importance of the Virtual Network Function (VNF) is not considered,an SFC reliable deployment algorithm based on deep reinforcement learning is proposed. Firstly, a reliable mapping model of VNF and virtual links is establised, high reliability requirements is set for important VNFs, and the reliability requirements of virtual links is ensured as much as possible through link deployment length restrictions. Secondly, taking load balancing as the resource coordination principle, joint optimization the VNF reliability is jointly optimized. Finally, the deep reinforcement learning is used to get the service function chain deployment strategy. In addition, node backup and link backup strategies based on importance are proposed to deal with situations where VNF/link reliability is difficult to meet during deployment. Simulation results show that the reliable deployment algorithm in this paper can effectively reduce the failure SFC loss on the basis of ensuring the reliability requirements, and at the same time make the virtual network more stable and reliable.

Considering power allocation of D2D (Device to Device) communication in fully loaded cellular networks, a multi-to-one multiplexing D2D communication power allocation algorithm based on the Nash equilibrium solution of non-cooperative complete information game is proposed. The communication quality of cellular users and the access rate of D2D users are guaranteed first, and the uplink frame structure of D2D communication system is given. Then, the non-cooperative complete information game model is established. After that, the pricing mechanism is introduced into the power distribution game model, and the existence and uniqueness of the Nash equilibrium solution are analyzed. Finally, the paper gives a distributed iterative algorithm for the model. The simulation results show that with the increase of the number of D2D pairs, the algorithm not only improves the system throughput, but also controls the internal interference of the system effectively, reduces the total energy consumption of the system greatly.

The existing key generation scheme requires additional key reconciliation protocol in a communication process, resulting in the limited application to the communication system, such as the Fifth-Generation mobile communication (5G). A physical layer secure transmission scheme with a joint polar code and non-reconciliation secret keys is proposed. Firstly, the non-reconciliation physical layer keys are extracted from the channel feature, and then the polar code is designed based on the equivalent channel, which is formed by the physical channel and the key encryption channel. Finally, the encoded sequence is simply modular plus encrypted and transmitted using the non-reconciliation physical layer key. Key differences and noise-induced bit errors are corrected through a targeted design of polarization codes to achieve reliable and secure transmission. The simulation shows that the polar code based on the equivalent channel can ensure the reliable transmission between two legitimate users at the optimal code rate.

To solve the problem of blind identification of polar codes’ parameters, a blind recognition algorithm of polar codes based on zero space matrix matching is proposed. The construction of polar codes’ generation matrix is certain, and all the generation matrices are full rank square matrices, first the rows corresponding to the frozen bit codes are deleted by using the channel reliability estimation in the polar code encoding. Then, the null space matrix of this matrix in the binary field is found out as the supervision matrix under the code length. The code word is iteratively multipied by the supervision matrix of different code lengths, according to the proportion of "1" in the product result, the code length, number and position distribution of information bits of the code word are determined. The simulation results show that for the 200 groups of polar code with 64-code-length and 30-information-bits, the recognition rate can be kept above 80% when the maximum bit error rate is less than 0.06.

In massive Machine-Type Communication (mMTC) systems, when the user activity is exploited as a priori information for the receiver, the Sparsity-aware Maximum A Posteriori probability (S-MAP) criterion can be used to recover the sparse multi-user vectors over the uplink mMTC systems. In order to reduce the computational complexity of S-MAP detection, based on interference cancellation mechanism, an Improved Activity-aware Sorted QR Decomposition (IA-SQRD) algorithm is proposed in this paper. The IA-SQRD algorithm utilizes the final solution of the A-SQRD algorithm as the initial solution and the iterative interference cancellation operation is performed to improve further the detection performance. Following the same philosophy in improving the A-SQRD algorithm, the conventional Sparsity-Aware Successive Interference Cancellation (SA-SIC), Sorted QR Decomposition (SQRD), and Data-Dependent Sorting and regularization (DDS) algorithms are modified to enhance the performance, respectively. Simulation results verify that compared with the A-SQRD algorithm, a 3 dB gain is achieved by the proposed IA-SQRD algorithm when the Bit Error Rate (BER) is

, without significantly increasing the computational complexity. In addition, given different system configurations in terms of active probability and the length of spread spectrum sequence, the proposed IA-SQRD also exhibits better performance than that of the other algorithms mentioned in this paper.

In view of secret communication among unmanned aerial vehicles under the strong electromagnetic interference environment, this paper proposes the energy balance algorithm for wireless ultraviolet secret communication in Unmanned Aerial Vehicle (UAV) formation. The proposed algorithm combines the advantages of ultraviolet in non-line-of-sight and low eavesdropping, overcomes the disadvantage of the traditional radio, which can easily be monitored. It can provide reliable assurance for the leader to collect information of wingmen while balancing the energy consumption. The improved algorithm is proposeal based on cluster mechanism via introducing the priority function, which considers distance and residual energy. Adopting the improved algorithm to simulate under two scenarios in which UAVs are deployed randomly or UAVs are deployed in circle formation respectively, the simulation results show that the time of 50% death nodes occurring in UAV network is prolongal by 12% and 16% respectively under two types of deployment, and the improved algorithm can effectively balance the communication energy consumption of the network and prolong the survival time of UAV network.