Cyberattacks continue to grow more advanced, making it increasingly difficult for traditional cybersecurity systems to detect and prevent harmful activities in real time. Many existing security solutions depend on predefined rules and known attack signatures, which limits their ability to identify unfamiliar...

Voice over Wi-Fi (VoWiFi) enables economical, high-quality voice communications through IP multimedia services over WLAN infrastructure. With the stringent real-time quality requirements, however, it is especially susceptible to breaches of security. This article provides an in-depth review of Wi-Fi...

In this datacentric world, almost all organizations produce prodigious amount of information that will be useful for artificial intelligence- based analytics. But, sharing sensitive data across all the organizations introduces challenges in privacy, security, and trust. This manuscript proposes a Federated...

Blockchain technology offers strong potential for solving key challenges in Electronic Health Record (EHR) systems. This paper proposes the Elastic Byzantine Consensus Protocol (ElaBy‑CP), an adaptive consensus mechanism that dynamically manages node participation, optimizes transaction batching, and...

The increasing reliance on Supervisory Control and Data Acquisition (SCADA) structures for handling important infrastructure makes them prone to cyber-assaults, posing significant dangers to operational security. To deal with this, a sophisticated Intrusion Prevention System (IPS) the use of Artificial...

The rapid advancement of quantum computing poses a significant threat to the security of current asymmetric cryptographic techniques, jeopardizing their availability, confidentiality, and integrity. Given the prolonged lifespan of vehicles, the automotive industry becomes increasingly susceptible to...

The move toward cloud-provided-software-as-a-service (SaaS) key management systems (KMS) introduces new, pressing security threats of quantum computing. The novelty of this work is to hybrid combine CRYSTALS-Kyber, NIST standardised, and Dilithium algorithm both for key encapsulation and digital signature...

Transfer of shares from one person to another happens in two ways, namely On-Market trade and Off-Market trade. On-Market trades are anonymous, meaning, both the seller and the buyer do not know each other. In an off- market trade, both parties know each other and to initiate the transfer of shares,...

Ontology-based methods provide a semantically rich and context-aware approach for cyber investigation, enabling structured representation of entities, relationships, and behavioural patterns across diverse threat landscapes. This review emphasises recent developments in ontology-driven phishing detection,...

The Railway safety systems continue to face significant challenges from undetected track defects, infrastructure obstacles, and potential collision scenarios. Traditional manual inspection protocols and conventional sensor-based monitoring systems frequently demonstrate limitations in terms of processing...

The rapid expansion of internet-connected devices and IoT infrastructures has significantly increased the scale and sophistication of botnet attacks, making them a major threat to modern digital environments. Traditional signature-based and heuristic detection systems struggle to identify evolving, stealthy,...

The city’s traffic is difficult to predict because congestion may suddenly occur due to accidents or shutdowns of roads. Current devices are either very slow, do not understand how roads connect, or do not see these unexpected problems as they occur. We need a system that can estimate both normal traffic...

In the silent corridors of the internet lies a digital underworld – the Dark Web, where anonymity empowers illicit trade, hidden communications and crimes that transcend physical borders. This study delves into the intersection of technology, law and deviance, examining how India’s existing legal frameworks,...

Cyber harassment is a significant concern for victims of dig ital communication platforms. Systematically compiling evidence that is legally acceptable is an insurmountable challenge for victims. Most traditional detection methods fail because harassment tactics evolve, abuse language is contextually...

High-frequency algorithmic trading environments are prime targets for cyber-enabled attacks such as spoofing, layering, and order injection, which threaten market integrity. Conventional fraud detection methods such as Logistic Regression (LR), Support Vector Machines (SVM), and Random Forests (RF) struggle...

Supply Chain Analytics (SCA) has become a strategic enabler for optimizing procurement, logistics, and distribution activities in modern supply networks. As organizations increasingly depend on data-driven decision-making, the scale and sensitivity of data being generated, shared, and analysed have grown...

The Internet of Medical Things (IoMT) generates continuous streams of highly sensitive patient data that demand both strong confidentiality and real-time tamper detection during transmission and cloud storage. Traditional encryption algorithms such as AES and RSA provide strong security but are computationally...

E-commerce platforms are increasingly exposed to diverse cyber threats such as fraudulent transactions, fake reviews, account takeovers, and abnormal user behaviors, all of which compromise security and diminish user confidence. Existing detection mechanisms, primarily based on ensemble methods such...

Electronic Health Records (EHR) systems face critical security challenges in maintaining patient privacy while enabling authorized healthcare professionals to access medical data efficiently. Traditional access control mechanisms often lack granular patient-controlled permissions and fail to provide...

This survey provides an overview of insider threat detection in cybersecurity, with a particular emphasis on clustering-based techniques for identifying malicious user behaviour. It reviews traditional methods such as K-means Clustering and DBSCAN, highlighting its limitations in handling high-dimensional...

Regular coding practice is essential for placement preparation, yet manual monitoring of large student groups is inefficient, error-prone, and difficult to scale [1]. This paper presents an automated system that uses Python-based web scraping, platform APIs, and rule-based analytics to track daily coding...

The Agricultural Food Supply Chain (AFSC) is a crucial aspect of the agricultural food industry, with stakeholders increasingly involved in decision-making processes. The use of chemicals in production and the constant flow of low-quality agricultural products have a significant impact on product quality...

The creation of hyper-realistic deepfakes using the Generative Adversarial Networks (GANs) is rapidly becoming one of the most severe threats to privacy, digital trust, and security, so much so that they give rise to massive misinformation, impersonation, and manipulation. The paper reviews the development...

Secure communication has become a critical requirement with the rapid advancement of digital systems and the increasing exposure of sensitive information to cyber threats. Conventional cryptographic mechanisms primarily rely on mathematical key generation techniques, which are vulnerable to key theft,...

Email spam endures to pose a momentous cybersecurity threat by manipulating polymorphism, complication, and multimodal content to detour traditional detection mechanisms. Prevailing rule-based and single-modality-based machine learning methods characterize the limitations in becoming accustomed to budding...