Chinedum Amaechi^1,*, Onyemelukwe Nnaemeka², Charity N. Onyechi³

Journal of Cyber Security, Vol.8, pp. 357-371, 2026, DOI:10.32604/jcs.2026.084201 - 18 June 2026

Abstract Background: In March 2026, Nigeria’s financial sector experienced a cascading cybersecurity breach that compromised both a commercial bank and the nation’s primary government payment infrastructure. Objective: This paper provides the first academic analysis of the Sterling Bank–Remita chain breach, examining how a single unpatched vulnerability led to the exposure of approximately 900,000 customer records and 3 terabytes of national payment data. Methods: Using open-source intelligence (OSINT) methodology and the MITRE ATT&CK framework (version 16), the attack chain was reconstructed from actor-published artefacts on the spear.cx cybercrime forum, cross-referenced with regulatory statements and vulnerability databases. The… More >

Yunkeun Song¹, Samuel Woo², Suji Lee³, Yousik Lee^3,*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.083267 - 15 June 2026

Abstract Software-Defined Vehicles (SDVs) increase cybersecurity complexity through the combination of external connectivity, software-intensive functions, and distributed development across vehicle manufacturers and suppliers. Although United Nations (UN) Regulation No. 155 and ISO/SAE 21434 require Threat Analysis and Risk Assessment (TARA) throughout the vehicle lifecycle, conventional TARA methodologies remain largely system-focused and often provide limited procedural guidance for coordinating supplier-derived TARA results at the vehicle level. This paper proposes an orchestration model for TARA across vehicle manufacturers and suppliers that structures TARA activities into the concept phase and the product development phases. The model defines interactions between… More >

Jiangyong Yu, Chuanping Hu^*, Runnan Wang

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.082810 - 15 June 2026

Abstract With the proliferation of Internet of Things (IoT) devices, accurate device fingerprinting of highly encrypted traffic has emerged as a critical challenge for ensuring network security. Existing deep learning models are either difficult to deploy in real-time due to excessive computational complexity (e.g., Transformers) or are limited in performance because their structure does not match the inherent hierarchy of traffic data (e.g., flattened state space models). Furthermore, a general lack of transparency in their decision-making processes restricts their trustworthiness in security-critical scenarios. To address these challenges, this paper proposes a Hierarchical Mamba with Gated Attribution More >

Danilo Greco^*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.082708 - 15 June 2026

Abstract The Enhanced Graph Neural Network Autoencoder (Enhanced GNN-AE), recently proposed for unsupervised cybersecurity monitoring in battery energy storage systems (BESSs), builds a multiscale k-nearest neighbour graph over measurement samples and learns compact latent representations via manifold-regularised training. Its spatial encoder, however, employs the original Graph Attention Network (GAT), which has been formally shown to compute a rank-1 attention function equivalent to graph convolutional networks on many graph structures. This work investigates whether replacing the GAT encoder with the strictly more expressive GATv2 formulation—which applies the attention vector after a joint, asymmetric linear transformation of source… More >

Qiuguo Guan, Zhiyu Ren^*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.082704 - 15 June 2026

Abstract To address trust-score drift and unsafe online adaptation under cross-domain attack-contaminated streams in Industrial Internet of Things (IIoT) edge environments, this paper proposes a risk-aware lightweight test-time adaptation (TTA) framework, named RaL-TTA, for dynamic trust evaluation of edge nodes. RaL-TTA constructs a low-dimensional robust feature space and a source-domain normal-entropy reference baseline, and performs selective online maintenance in the target domain through Kolmogorov–Smirnov (KS) drift detection, SafeBrake risk gating, Adaptive Batch Normalization (AdaBN) anchor protection, and budgeted sample-level safeguards. Low-risk batches are adapted by updating only lightweight Batch Normalization (BN) parameters, whereas high-risk batches freeze… More >

Sajad Homayoun^*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.082332 - 15 June 2026

Abstract Intrusion detection systems depend on detailed security telemetry, yet such telemetry is often too sensitive to share or reuse outside controlled environments. Differential Privacy (DP) offers formal protection by injecting randomness, but its practical impact on detection utility is not well understood, especially under class imbalance and for rare attacks. This paper presents a controlled empirical study of feature-level DP applied to security telemetry for intrusion detection. Using a fixed model and a fixed train–test split, we vary only the privacy budget and quantify how performance changes across standard metrics, including macro-averaged scores and per-class More >

Taghreed Alkhodaidi^1,*, Wadee Alhalabi¹, Miada Almasre²

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.081665 - 15 June 2026

Abstract The rapid growth of the IoMT has resulted in critical security threats to healthcare infrastructure, which require highly sophisticated IDSs that can detect a wide range of and unbalanced attack patterns. This study has addressed a critical challenge faced by network security data, which is class imbalance, by presenting a comprehensive evaluation of data balancing techniques on both a real-world standard data set, CICIoMT2024, and a synthetic data set, SynIoMT2026, which we generated to mimic the characteristics of the standard data set for developing a highly controlled data set. Three data balancing techniques, ADASYN, Sample… More >

Chao Zhang¹, Weidong Zhong¹, Xu An Wang¹, Weiwei Jiang^2,*, Ziteng Wang², Miao Tian¹, Jianhong Ling¹, Hangjiang Du¹, Yunhui Duan¹

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.081399 - 15 June 2026

Abstract The integrity risks posed by data outsourcing in cloud storage have driven the development of remote data integrity auditing (RDIA) technologies. However, traditional schemes rely on trusted third-party auditors (TPAs), leading to potential collusion and single-point failure vulnerabilities. The integration of blockchain alleviates these issues through decentralization and transparency, yet existing blockchain-based certificateless auditing schemes still suffer from security flaws in the tag generation phase. Addressing the tag forgery vulnerability in Miao et al.’s scheme, which stems from the absence of random parameters in the hash function input, this paper proposes a lightweight enhancement mechanism: More >

Akmalbek Abdusalomov¹, Kudratjon Zohirov², Sojida Ochilova², Jakhongir Oramov³, Zafar Ruziyev³, Malika Rustamova⁴, Gulrukh Sherboboyeva⁵, Komil Tashev^6,7, Young Im Cho^1,*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.081292 - 15 June 2026

Abstract Unmanned aerial vehicles (UAVs) are also increasingly becoming more often in the transportation infrastructure of smart cities, so that they can successfully achieve real-time observation of traffic, emergency coordination, and two-way communication relaying. However, the security and privacy risks arising in open, highly mobile intelligent transportation systems (ITS) enabled by UAVs are critical, as they pose threats of impersonation, replay, Sybil, and tracking attacks. Secondly, standard static authentication mechanisms are unable to support dynamic risk environments and excessive resource consumption on UAV platforms with limited capacity. To address these challenges, this study introduces a Generative-AI-assisted… More >

Peiying Zhang^1,2, Yihong Yu^1,2, Lizhuang Tan^3,4,*, Shuqing He⁵, Jian Wang⁶, Ameer El-Sayed⁷

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.081224 - 15 June 2026

Abstract As a core information infrastructure in the 6G era, the Space-Air-Ground Integrated Network (SAGIN) integrates space-based, air-based, and ground-based network resources to achieve seamless communication across all domains. However, its characteristics such as heterogeneous node coupling and dynamic topology changes make it prone to cascading failures, severely threatening critical business continuity in Internet of Things (IoT) applications spanning smart cities, healthcare, transportation, and industrial automation. This paper conducts systematic research addressing challenges including modeling difficulties in SAGIN cascading failure propagation, insufficient coordination of defense strategies, and poor resource adaptability. First, a multi-factor coupled dynamic model… More >