The resource allocation solution offered based on Non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) schemes are sub-optimal to address the challenging quality of service (QoS) and higher data rate viz-a-viz energy efficiency (EE) requirements in 5th generation (5G) cellular networks. In this work, we maximize the EE using user equipment (UE) clustering (UE-C) with downlink hybrid NOMA (H-NOMA) assisted beyond 5G (B5G) HetNets. We formulate an optimization problem incorporating UE admission in a cluster, UE association with a base station (BS), and power allocation assisted by H-NOMA, i.e., OMA and NOMA schemes in the macro base station (MBS) only and heterogeneous networks (HetNets) environments. The problem formulated is a type of non-linear concave fractional programming (CFP) problem. The Charnes-Cooper transformation (CCT) is applied to the formulated non-linear CFP problem to convert it into a concave optimization, i.e., mixed-integer non-linear programming (MINLP) problem. A two-phase ϵ-optimal outer approximation algorithm (OAA) is used to solve the MINLP problem. The simulation results show that H-NOMA with HetNets outperforms H-NOMA with MBS only in terms of UE admission, UE association, throughput, and EE.

Beyond fifth-generation (5G) heterogeneous networks (HetNets) are facing the challenge of accommodating enormous mobile users and data traffic with scarce spectrum resources in the microWave (μWave) band. In this work, we consider both challenges in HetNets comprising large size, high power base station (LHB) and relay operating in μWave band and small size, low power base station (SLB) and device-to-device (D2D) operating in millimeter wave (mmWave) band. We formulate user association optimization problems to pitch user association schemes based on downlink uplink decoupled (DU-DPL) access against traditional downlink uplink coupled (DU-CPL) access in HetNets to gauge the performance of these access schemes in terms of accommodating users and spectrum efficiency in μWave and mmWave bands. Formulated problems are non-deterministic polynomial-time hard (NP-hard) and solved using ϵ-optimal algorithm. Simulation results show the edge of DU-DPL access over DU-CPL access in terms of users association and spectrum efficiency.

Advanced Persistent Threats commonly use Domain Generation Algorithms to evade advanced detection methods to establish communication with their command and control servers. To overcome the DNS protocol legitimacy breach, several Domain Generation Algorithms detection methods have been proposed. To solve the problem of DGA malware detection amicably, Deep Learning based detection schemes attracted researchers’ interest recently. However, Deep Learning has already achieved optimal results and the gap is identified as fine-tuning of Deep Learning model hyper-parameters. The proposed solution is focusing on a model specific hyper-parameter known as the gradient optimizer. Gradient Optimisers are broadly categorised into Stochastic Gradient and Adaptive Moment based Gradient. Moment-based Gradient optimizer approaches are identified with suffering from weight decay and leading to poor generalization. Adaptive Moment (Adam) has improved with weight Decay as AdamW. To optimise moment-based gradient optimizers, Adam and AdamW are analyzed deeply. To optimize the functioning of AdamW, we present AdamW+, a novel solution for detecting DGA algorithms through re-implementing and nullifying the weight decay in AdamW. AdamW+ has been successfully implemented and shown promising results compared to Adam and AdamW optimizers in practice. AdamW+ preserved the properties of Adaptive Optimizer Adam while simplifying the weight decay implementation of AdamW. Empirical analysis has proved that AdamW+ has outperformed Adam and AdamW. The experimental result have substantiated that the proposed algorithm achieves the best accuracy result.

The invention of transistors in the 1940s marked the beginning of a technological revolution that has impacted every aspect of our lives. However, along with the positive advancements, the malicious use of computing technologies has become a serious concern. The international community has been actively collaborating to develop digital forensics techniques to combat the unlawful use of these technologies. However, the evolution of digital forensics has often lagged behind the rapid developments in computing technologies. In addition to their harmful use, computing devices are increasingly involved in crime scenes and accidents, necessitating digital forensics to reconstruct events. This paper provides a comprehensive review of the development of computing technologies from the 1940s to the present, highlighting the trends in their malicious use and the corresponding advancements in digital forensics. The paper also discusses various institutes, laboratories, organizations, and training setups established at national and international levels for digital forensics purposes. Furthermore, it explores the initial legislations related to computer-related crimes and the standards associated with digital forensics. These reviews and discussions conclude at identifying the shortfalls in digital forensics and proposes an all-inclusive digital forensics process model meeting these shortfalls while complying to international standards and meeting regulatory and legal requirements of digital forensics.