Enhancing the robustness of block ciphers through a graphical S-box evolution scheme for secure multimedia applications by Abdul Razaq, Muhammad Mahboob Ahsan, Hanan Alolaiyan, Musheer Ahmad, Qin Xin

“…Block ciphers are essential for the secure exchange of data and communication, as they are one of the primary components of network security systems. Modern-day block ciphers are most significantly reliant on substitution-boxes (S-boxes). …”
Get full text

A Comprehensive Review of AI’s Current Impact and Future Prospects in Cybersecurity by Abdullah Al Siam, Moutaz Alazab, Albara Awajan, Nuruzzaman Faruqui

“…This study offers a comprehensive literature review on the role, effect, and future prospects of AI across five critical areas of cybersecurity: threat detection, endpoint security, phishing and fraud detection, network security, and adaptive authentication. The study examines contemporary developments in AI for cybersecurity, highlighting the use of these technologies to enhance security protocols. …”
Get full text

Intrusion detection using synaptic intelligent convolutional neural networks for dynamic Internet of Things environments by Hui Chen, Zhendong Wang, Shuxin Yang, Xiao Luo, Daojing He, Sammy Chan

“…The swift proliferation of IoT devices has brought about a multitude of complex cyberattacks that breach network security and compromise user privacy. To address these threats, this paper proposes a synaptic intelligent convolutional neural network (SICNN) model for intrusion detection in dynamic IoT environments. …”
Get full text

Multi-Relational Graph Representation Learning for Financial Statement Fraud Detection by Chenxu Wang, Mengqin Wang, Xiaoguang Wang, Luyue Zhang, Yi Long

Get full text

Transferability Evaluation in Wi-Fi Intrusion Detection Systems Through Machine Learning and Deep Learning Approaches by Saud Yonbawi, Adil Afzal, Muhammad Yasir, Muhammad Rizwan, Natalia Kryvinska

“…Intrusion Detection System (IDS) plays a pivotal role in safeguarding network security. The efficacy of these systems is rigorously assessed through established metrics including precision, recall, F1 score, and AUC score. …”
Get full text

Personalized lightweight distributed network intrusion detection system in fog computing by Tianpeng YE, Xiang LIN, Jianhua LI, Xuankai ZHANG, Liwen XU

“…With the continuous development of Internet of Things (IoT) technology, there is a constant emergency of new IoT applications with low latency, high dynamics, and large bandwidth requirements.This has led to the widespread aggregation of massive devices and information at the network edge, promoting the emergence and deep development of fog computing architecture.However, with the widespread and in-depth application of fog computing architecture, the distributed network security architecture deployed to ensure its security is facing critical challenges brought by fog computing itself, such as the limitations of fog computing node computing and network communication resources, and the high dynamics of fog computing applications, which limit the edge deployment of complex network intrusion detection algorithms.To effectively solve the above problems, a personalized lightweight distributed network intrusion detection system (PLD-NIDS) was proposed based on the fog computing architecture.A large-scale complex network flow intrusion detection model was trained based on the convolutional neural network architecture, and furthermore the network traffic type distribution of each fog computing node was collected.The personalized model distillation algorithm and the weighted first-order Taylor approximation pruning algorithm were proposed to quickly compress the complex model, breaking through the limitation of traditional model compression algorithms that can only provide single compressed models for edge node deployment due to the high compression calculation overhead when facing a large number of personalized nodes.According to experimental results, the proposed PLD-NIDS architecture can achieve fast personalized compression of edge intrusion detection models.Compared with traditional model pruning algorithms, the proposed architecture achieves a good balance between computational loss and model accuracy.In terms of model accuracy, the proposed weighted first-order Taylor approximation pruning algorithm can achieve about 4% model compression ratio improvement under the same 0.2% model accuracy loss condition compared with the traditional first-order Taylor approximation pruning algorithm.…”
Get full text

Payload State Prediction Based on Real-Time IoT Network Traffic Using Hierarchical Clustering with Iterative Optimization by Hao Zhang, Jing Wang, Xuanyuan Wang, Kai Lu, Hao Zhang, Tong Xu, Yan Zhou

“…IoT (Internet of Things) networks are vulnerable to network viruses and botnets, while facing serious network security issues. The prediction of payload states in IoT networks can detect network attacks and achieve early warning and rapid response to prevent potential threats. …”
Get full text

Detection of SSL/TLS protocol attacks based on flow spectrum theory by Shize GUO, Fan ZHANG, Zhuoxue SONG, Ziming ZHAO, Xinjie ZHAO, Xiaojuan WANG, Xiangyang LUO

“…Network attack detection plays a vital role in network security.Existing detection approaches focus on typical attack behaviors, such as Botnets and SQL injection.The widespread use of the SSL/TLS encryption protocol arises some emerging attack strategies against the SSL/TLS protocol.With the network traffic collection environment that built upon the implements of popular SSL/TLS attacks, a network traffic dataset including four SSL/TLS attacks, as well as benign flows was controlled.Considering the problems that limited observability of existing detection and limited separation of the original-flow spatiotemporal domains, a flow spectrum theory was proposed to map the threat behavior in the cyberspace from the original spatiotemporal domain to the transformed domain through the process of “potential change” and obtain the “potential variation spectrum”.The flow spectrum theory is based on a set of separable and observable feature representations to achieve efficient analysis of network flows.The key to the application of flow spectrum theory in actual cyberspace threat behavior detection is to find the potential basis matrix for a specific threat network flow under the condition of a given transformation operator.Since the SSL/TLS protocol has a strong timing relationship and state transition process in the handshake phase, and there are similarities between some SSL/TLS attacks, the detection of SSL/TLS attacks not only needs to consider timing context information, but also needs to consider the high-separation representation of TLS network flows.Based on the flow spectrum theory, the threat template idea was used to extract the potential basis matrix, and the potential basis mapping based on the long-short-term memory unit was used to map the SSL/TLS attack network flow to the flow spectrum domain space.On the self-built SSL/TLS attack network flow data set, the validity of the flow spectrum theory is verified by means of classification performance comparison, potential variation spectrum dimensionality reduction visualization, threat behavior feature weight evaluation, threat behavior spectrum division assessment, and potential variation base matrix heatmap visualization.…”
Get full text

ASAD: A Meta Learning-Based Auto-Selective Approach and Tool for Anomaly Detection by Nadia Rashid, Rashid Mehmood, Fahad Alqurashi, Saad Alqahtany, Juan M. Corchado

“…It is trained using 139 datasets built upon 60 base datasets from 11 diverse domains (finance, healthcare, network security) and 80 ML and DL models composed of 22 base anomaly detection algorithms. …”
Get full text

Network Intrusion Detection and Prevention System Using Hybrid Machine Learning with Supervised Ensemble Stacking Model by Godfrey A. Mills, Daniel K. Acquah, Robert A. Sowah

“…The detection performance of the proposed hybrid intrusion detection system suggests that it can be deployed in network security applications to detect packets that exhibit suspicious behaviour or indicate potential threats and respond appropriately to attacks. …”
Get full text

Research on power plant security issues monitoring and fault detection using attention based LSTM model by Shengda Wang, Zeng Dou, Danni Liu, Han Xu, Ji Du

“…This will help to successfully enhance the security and service quality of the power data communication network, effectively cope with network security threats in the new environment, and ensure the security of the power plant network access. …”
Get full text

A Survey on Event Tracking in Social Media Data Streams by Zixuan Han, Leilei Shi, Lu Liu, Liang Jiang, Jiawei Fang, Fanyuan Lin, Jinjuan Zhang, John Panneerselvam, Nick Antonopoulos

“…Event tracking in social networks finds various applications, such as network security and societal governance, which involves analyzing data generated by user groups on social networks in real time. …”
Get full text

IMCMK-CNN: A lightweight convolutional neural network with Multi-scale Kernels for Image-based Malware Classification by Dandan Zhang, Yafei Song, Qian Xiang, Yang Wang

“…Pursuing research in this direction is not only vital for enhancing network security defenses and safeguarding user data, but it will also foster the advancement of related state-of-the-art technologies and further mitigate the economic and societal repercussions of malware attacks. …”
Get full text

MANAGING FRAUD IN CONTEMPORARY BUSINESS ENVIRONMENT, THE ROLE OF INFORMATION SECURITY MANAGEMENT: A STUDY OF QUOTED DEPOSIT MONEY BANKS (DMBs) IN NIGERIA by Onajero Kensington OHWO

“…Utilizing a regression model, the research examines three key proxies of information security management: Application Security Control (ASC), Access/Authentication Control (AAC), and Network Security Control (NSC) and one proxy (Fraud risk governance - FRG) for fraud risk management The model reveals that both ASC and AAC have significant positive effects on FRG, with coefficients of 0.216 and 0.247, respectively, while NSC, with a coefficient of 0.080, does not significantly influence FRG. …”

Studi Empiris terhadap Kinerja & Keamanan Wifi (Studi Kasus di Kota Depok) by Ahmad Fajri

“…Therefore, performance assessment and wifi network security in Depok City are considered to be good in accordance with the IEEE 802.11i standard which is about increasing security on Wifi networks using WPA2 and 802.11b regarding wifi channel settings that do not cause interference. …”
Get full text

Deep learning-based algorithm for classifying high-resolution computed tomography features in coal workers’ pneumoconiosis by Hantian Dong, Biaokai Zhu, Xiaomei Kong, Xuesen Su, Ting Liu, Xinri Zhang

Get full text

Evaluasi Manajemen Keamanan Informasi Menggunakan Indeks Keamanan Informasi (KAMI) pada Jaringan (Studi Kasus: UIN Sunan Kalijaga Yogyakarta) by Rizki Dewantara, Bambang Sugiantoro

“…Abstract Attacks on networks today are very common, with more and more ways to access data and the development of technology used, they will certainly cause an increase in network security threats. Evaluation of information security management using the information security index (KAMI) conducted on the network at UIN Sunan Kalijaga Yogyakarta obtained an index result of 407, which is considered still not optimal. …”
Get full text

A Review on Blockchain Applications in Operational Technology for Food and Agriculture Critical Infrastructure by Chengliang Zheng, Xiangzhen Peng, Ziyue Wang, Tianyu Ma, Jiajia Lu, Leiyang Chen, Liang Dong, Long Wang, Xiaohui Cui, Zhidong Shen

“…Blockchain technology (BT) has emerged as a transformative solution for addressing these challenges by enhancing network security, traceability, and system resilience. …”
Get full text

Survei Penelitian Metode Kecerdasan Buatan untuk Mendeteksi Ancaman Teknologi Serangan Siber by Eza Yolanda Fitria, Kusprasapta Mutijarsa

“…The types of cyberattacks discussed in this study focus on attacks on the host system and the network security layer. In previous SLR research, these matters were discussed separately or even just one of them. …”
Get full text

On-demand and efficient scheduling scheme for cryptographic service resource by Wenlong KOU, Yuyang ZHANG, Fenghua LI, Xiaogang CAO, Jiamin LI, Zhu WANG, Kui GENG

“…How to deal with random cross and large peak difference cryptographic service requests has gradually become a bottleneck problem restricting various network security applications.A model of cryptographic service scheduling system is proposed to explore the differential dynamic on-demand scheduling of cryptographic service resources. …”
Get full text