Abstract: The integration of Advanced Encryption Standard (AES) encryption into the Routing protocol known as Ad Hoc On-Demand Distance Vector (AODV) enhances the security and confidentiality of control messages exchanged between nodes. This work explores the implementation of AES-128 bits encryption in AODV called Lightweight AODV (LwAODV) to protect critical routing information from unauthorized access
Abstract: The growing deployment of Unmanned Aerial Vehicles (UAVs) in critical infrastructures introduces a complex web of security, trust, and performance challenges particularly as networks scale and interact with heterogeneous edge environments. This paper presents BUAS, a novel Blockchain enabled UAV Architecture that integrates Bayesian trust m odeling, encrypted UAV to ground station communication, and
Abstract: Anomaly detection in heterogeneous High Performance Computing (HPC) systems is challenging because the environment of multi-component hardware is complex. Traditional detection methods are not compatible with high-dimensional data and are heterogeneous. This study proposes a new hybrid approach by combining deep learning and symbolic artificial intelligence techniques to improve the accuracy and interpretability of
Abstract: The financial sector has seen a significant rise in fraudulent activities, costing businesses billions of naira annually. Fraudulent transactions often involve unautho rized account access, manipulation of transaction data, or theft, leaving businesses and consumers vulnerable. This study aims to enhance financial fraud detection using a deep learning approach combining Bidirectional Long Short Term
Abstract A developing biometric technique called brainwave authentication uses the distinctive electrical patterns produced by the human brain to identify a person. When it comes to security and durability, brainwave authentication surpasses standard biometrics as it utilizes an individual’s own neural signatures, rather than depending on exterior physical or behavioural traits. The proposed brainwave authentication
Abstract False alarms in network intrusion detection systems (NIDS) can lead to unnecessary and costly investigations and reduce the credibility of the system. Network intrusion detection systems (NIDS) are tools that monitor network traffic and detect malicious or anomalous behaviours. However, NIDS face many challenges, such as the high dimensionality of network data, class imbalance,
Abstract The Internet of Things (IoT) has become an integral part of our daily lives, with the increasing usage of interconnected devices. However, with this increased connectivity comes the risk of security breaches and intrusions. To address this issue, many researchers have proposed intrusion detection systems (IDS) that utilize deep learning techniques. Therefore, this study
Abstract Nigeria have a huge population with diverse ethnical and religious groups, an ample territory with unguarded borders shared with neighbouring countries which gives insurgent a vast amount of space to carry out their terror acts. The continuous rise of insecurity in Nigeria claims many innocence lives and the destruction of properties of the citizens
Abstract Communication is as old as mankind and is extremely vital to human survival. As time passed, humanity evolved, so did our tools and technologies. Now, in this fast-paced world, we live in, information must be transmitted securely, as fast as possible, and without transmission delays; hence the advent of real-time communication. However, security breaches
Abstract Fully Homomorphic Encryption (FHE) represents a sophisticated cryptographic method that permits computations on encrypted data without the necessity for prior decryption. Substantial progress has been achieved in the realm of FHE and its application since 2015, yielding enhanced efficacy, heightened security, and augmented feasibility. The review paper critically evaluates diverse FHE schemes/libraries, and the