Journal of Cyber Security and Mobility

A Novel Secure and Energy-efficient Routing Method for the Agricultural Internet of Things Using Whale Optimization Algorithm

Yanling Wang, Yong Yang — Fri, 14 Jun 2024 00:00:00 +0200

The Internet of Things (IoT) is an all-encompassing system that tracks and monitors real-world activities by gathering, handling, and interpreting data from IoT equipment. It has successfully been applied in several fields, particularly smart agriculture since there is a high demand for high-quality foodstuffs worldwide. It is essential to develop new agricultural production schemes to meet these demands. The heterogeneity of IoT devices makes security essential for IoT communication. Also, IoT devices are restricted in terms of processing, memory, and power capacities. Therefore, energy is a key factor in extending the life of an agricultural IoT network. This study presented a novel energy-aware and secure routing scheme using the Whale Optimization Algorithm (WOA) for IoT, referred to as SRWOA. The simulation results indicate that SRWOA uniformly distributes energy consumption in IoT and maximizes the packet delivery ratio.

The Homology Determination System for APT Samples Based on Gene Maps

Rui-chao Xu, Yue-bin Di, Zeng Shou, Xiao Ma, He-qiu Chai, Long Yin — Fri, 14 Jun 2024 00:00:00 +0200

At present, there are fewer types of homology determination methods for advanced persistent threat (APT) samples detection, and most existing determination schemes have problems such as high cost, low accuracy, and difficulty in identifying unknown APT samples. Therefore, we proposed a homology determination system for APT samples based on gene maps by integrating deep learning and gene maps. Firstly, we extract the software gene features from the samples uploaded by the user and apply the TF-IDF algorithm to clean the extracted software genes. The Word2Vec algorithm is used to vectorize all the genes to construct the gene sample vectors. And we use a LSTM-based classifier to detect APT attack samples. Finally, the K-nearest neighbor algorithm is used to determine the homology of gene-sharing APT samples. The detailed construction process of the scheme is given in this paper, including APT sample gene extraction, cleaning, clustering, sample detection, and homology determination. Experimental validation showcases our model outperforming existing methodologies with an accuracy of 95%, precision of 94%, and recall of 95%. When compared to previous models, the superiority of our approach is evident. These results underscore our model’s high efficiency and accuracy, confirming its potential for significant application in the field of cybersecurity.

Analysis and Research on Secure Access Control Technology of Industrial Internet of Things Based on ZTM Model

Yanliu Nie — Fri, 14 Jun 2024 00:00:00 +0200

The security threat of IIoT is becoming increasingly serious. In order to address this challenge, security access control technology based on the ZTM model has become a hot research topic. The aim of this study is to conduct in-depth analysis and research on the security access control technology applied by the ZTM model in industrial Internet of Things environments. By analyzing the current challenges of IIOT security and the limitations of traditional security models, this paper proposes a series of security access control technologies related to the ZTM model, aiming to quantify and evaluate the effectiveness of access control policies, zero trust of the system, and comprehensive risk assessment. By using empirical research methods, this study verified the feasibility of the proposed technology in actual industrial Internet of Things environments and demonstrated the significant effect of the ZTM model in reducing security risks and improving system credibility. The experimental results showed that the optimized security access control technology improved security performance by 28% and the missed detection rate was as low as 3.2%. This study provides useful insights for practical applications in the field of secure access control and provides a solid foundation for future research.

Application of Intelligent Cloud Computing Technology in Optical Communication Network Security of Smart Grid

Botao Hou, Zhefeng Li, Xiaojun Zuo, Yuling Guo, Jianchun Zhou — Fri, 14 Jun 2024 00:00:00 +0200

In order to improve the security of smart grid optical communication network, this paper combines intelligent cloud computing technology to build a security system of optical communication network of power grid. In the aspect of improving communication security performance, multi-user access is realized by non-orthogonal power domain segmentation, and different users use different powers to add and superimpose the same spectrum resources, so as to increase spectrum utilization. At the sending end, this paper improves the safe channel capacity of users by means of pre-coding and artificial noise, and realizes the safe transmission of information. In terms of transmission stability, the cloud computing platform is used as a data processing platform, and multiple nodes are processed synchronously through optical communication state identification, which can more effectively improve the speed of optical communication state identification data. In order to test the performance of the power grid information dispatching model designed in this paper in optimizing power grid configuration and improving power grid load, simulation experiments are carried out. Through the experimental analysis, we can see that the communication method proposed in this paper can accurately identify the intrusion factors, and can effectively improve the security of smart grid optical communication network.

Encryption Technology of Optical Communication Network Based on Artificial Intelligence Technology

Ying Wang, Xiaojun Zuo, Yuling Guo, Huiying Liu, Jianchun Zhou — Fri, 14 Jun 2024 00:00:00 +0200

At present, research on enhancing information transmission security by addressing the two key issues of time delay signal elimination and key space expansion in chaotic secure communication systems has become a hot topic. In order to improve the encryption effect of optical communication network, this paper analyzes the encryption technology of optical communication network with AIT (artificial intelligence technology), designs the encryption scheme of optical communication network with the help of AIT, and takes the digital random sequence as the key. Moreover, this paper uses the digital signal processor to control the arbitrary wave generator to generate multi-ary step square wave, modulate the optical feedback and realize the highly random change of external cavity delay, thus eliminating the long external cavity delay information. This article proposes a chaotic secure communication system using digital sequences as keys and external cavity optical feedback, a device for forming a chaotic source through arbitrary wave phase modulation and single loop feedback, and a chaotic secure communication system with single feedback key phase modulation and injection synchronization. At the same time, this paper proposes a system scheme using single-loop optical feedback phase modulation, the CS(chaotic signal) with complex dynamic behavior is output, and the time-delay signal is effectively eliminated. This paper analyzes the strength and phase information of CS by autocorrelation and mutual information technology, and verifies the effect of optical communication network encryption technology. Through the analysis of experimental results, it can be seen that the optical communication network encryption technology based on AIT proposed in this paper can effectively improve the encryption effect of optical communication network. The algorithm model camera proposed in this article can be used in subsequent practice to improve communication encryption performance

Analysis and Application of Chaotic Genetic Algorithm Based on Network Security in The Research of Resilience of Cluster Networks

Xiaobo Song — Fri, 14 Jun 2024 00:00:00 +0200

With the wide application of UAV, in the actual flight process, UAV needs to calculate the safe path according to its own position, environment, obstacles and other information. Due to the complex and changeable scene and environment of UAV mission execution, it is very important to select an appropriate UAV path planning algorithm. This paper aims at the path planning problem of multiple UAVs in a complex three-dimensional environment to ensure that multiple UAVs reach the mission location from different angles. Taking the chaotic genetic algorithm in network security protection as the main body, the operation difficulty of the algorithm is reduced, and the solution speed and accuracy of the algorithm are improved. The path length obtained by the proposed algorithm is 8.4% less than that of the ABC algorithm, 11.3% less than that of the PSO algorithm, and 4.2% less than that of the BABC algorithm. The system running time of the improved algorithm is also reduced by 27% to 45% compared with other algorithms. In terms of unmanned cooperation, this paper proposes a system capability based on network modeling to improve the cooperative combat capability of multiple UAVs. By establishing a network model, information sharing, collaborative decision-making and collaborative decision-making between drones are realized, thereby improving the effectiveness of the entire system. At the same time, this paper also considers the problem of network survivability. By introducing redundant design and fault recovery mechanism, the robustness and reliability of the system are enhanced.

Design and Implementation of IPsec VPN IoT Gateway System in National Secret Algorithm

Yan Jiang, Jing Huang, Yunsong Fan, Xiaobin Zhu — Fri, 14 Jun 2024 00:00:00 +0200

With the development of Internet of Things technology, the security threats faced by the industrial control field are increasing, and strengthening the security protection capabilities of intelligent systems on IoT highways is becoming increasingly important. IPSec VPN tunneling technology can achieve identity authentication and encrypted data transmission, and is an important means to achieve secure data transmission in intelligent systems on Expressway intelligent tunnel system. The commonly used IPSec VPN gateway uses a traditional Linux protocol stack-based approach for data capture, which requires multiple data copies and context switching, resulting in low efficiency of IPSec services. In addition, the commonly used IPSec VPN security gateway is implemented on the basis of the open-source IPSec framework, using internationally recognized algorithms for encryption and decryption, which poses security risks. This article is based on the IPSec protocol, and studies the high-speed network packet capture framework PFRING technology, the fusion technology of national secret algorithm and IPSec protocol. It designs and implements an IPSec VPN IoT security gateway based on national secret algorithm. After experimental verification, the IPSec VPN gateway system constructed in this article has complete functions and better performance than the common open-source IPSec frameworks OpenSwan and strongSwan, and can meet the application requirements of IoT data encryption transmission.

Improving Incident Management Processes with Feature Models

Karam Mustafa Ignaim, João M. Fernandes — Fri, 14 Jun 2024 00:00:00 +0200

A cybersecurity incident is any event that directly or indirectly affects the confidentiality, availability, or integrity of a system or a service (or its data). The aim of a cyber-incident management process is to restore normal service levels as quickly as possible, by mitigating or eliminating the effects of system service disruptions. During the different phases of a cyber-incident management process, the documentation can be confusing and difficult to comprehend, making it ineffective. This paper aims to improve cyber-incident management processes that already exist by introducing feature models in order to handle incident documentation, classification, prioritisation, and mitigation. An example of an improved cyber-incident process is evaluated with respect to its efficiency and effectiveness, by conducting two case studies. The results of this work reveal that the improved process increases efficiency in addressing and repairing cyber-incidents by reducing the incident response time.

Campus Network Security Intrusion Detection Based on Feature Segmentation and Deep Learning

Zhe Chen — Fri, 14 Jun 2024 00:00:00 +0200

At present, the secure campus network strategy adopts technical means such as distinguishing applications and limiting them separately, but they have triggered other new problems, greatly affecting the unity of network resources and data. The relatively dispersed network architecture will inevitably limit the further development and expansion of the campus network. Therefore, when universities plan their networks, they must consider whether the network is safe, complete, smooth, and sustainable for smooth upgrading and development. In order to improve the effect of campus network security intrusion detection, this paper combines feature segmentation and deep learning technology to construct a campus network security intrusion detection model. To reduce the transmission time of query requirements in the grid, this paper improves the replica management mechanism and requires the information server to cache the Bloom Filter structure of nodes in its successor node list. Moreover, this paper uses the Compressed Bloom Filter algorithm to compress the Bloom Filter structure that needs to be transmitted, therefore reducing the network traffic generated during the update process of the Bloom Filter structure copy and avoiding network congestion. It also constructs a campus network security intrusion detection model based on feature segmentation and deep learning. Through experimental verification, the effectiveness of the system in intrusion detection, user evaluation, information processing, and other aspects is verified, and it has certain advantages compared to traditional algorithms. Through experimental research, it can be seen that the campus network security intrusion detection model based on feature segmentation and deep learning proposed in the paper can effectively improve the effect of campus network security monitoring. The method proposed in this article can not only be applied to campus network security, but also to the network security management of enterprises and other units, with certain scalability

Intrusion Detection in Wireless Sensor Networks Based on IPSO-SVM Algorithm

Zhimin Lv, Jun Wan — Fri, 14 Jun 2024 00:00:00 +0200

To optimize node energy consumption and improve its security, this paper uses the DEEC algorithm to layer WSN and reduce the probability of channel information collision and uses the weighted probability of cluster head election to optimize node energy expenditure, so that WSN can obtain a longer lifecycle. Improved Particle Swarm Optimization-based Support Vector Machine (IPSO-SVM) algorithm is used for intrusion detection and experimental testing in WSN. The results showed that the IPSO-SVM algorithm exhibited good convergence, with a convergence step size of 5 steps, which converged earlier than the Support Vector Machine Algorithm based on Particle Swarm Optimization (PSO-SVM), which had a convergence step size of 10 steps. The IPSO-SVM algorithm performed best in WSN intrusion detection, with the highest detection rate of 96.20% in Probe attack data detection, which was 0.80% higher than the Support Vector Machine Algorithm based on Genetic Algorithm (GA-SVM). The PSO-SVM algorithm had the lowest detection rate of 95.20%. The IPSO-SVM algorithm had a minimum false positive rate of 1.54% in Dos attack data detection. In terms of average training time, the IPSO-SVM algorithm had a minimum average training time of 323.45 seconds. Compared to the Low Energy Adaptive Clustering Hierarchy (LEACH) algorithm, the Distributed Energy Efficient Clustering (DEEC) algorithm performs better, has less energy consumption, and retains more nodes. The method adopted in this study can make WSN have a longer life cycle and ensure its security.