Covenant Journal of Informatics and Communication Technology

Concept of Cryptographic Operations Based on Code Division Multiple Access

Akhigbe-mudu Thursday Ehis — 2023-12-05

It is a given that numerous users connect to a single satellite transponder on a daily basis in order to communicate while discussing any satellite-based technology. As a result, they must all share the resources that are available without compromising the privacy of one another. Thus, the multiple access strategy is employed to achieve this. This paper focuses on code division multiple access, which does not require time slots or frequency slots to be shared across numerous users. The primary source of communication problems is multipath fading; and if the signal undergoes any multipath fading, then the total signal may be distorted. This work presents improved correlation features of the current Walsh code through one simple yet powerful algorithm. Here, a simulation-based method is used to evaluate performance. Utilizing power delay profiles in several mobile radio propagation channels, measurement-based channel models for indoor, outdoor, suburban, and urban environments are derived. The number of taps and tap gains are then estimated using statistics on the path loss characteristics. Since the source, output is known it is compared with a delayed version of the decision device output to obtain an empirical basis for the error rate. The suggested code’s performance is then compared to a few existing orthogonal and semi- orthogonal codes using a variety of performance criteria, and the conclusion is that this proposal is superior.

Enhancing Lifetime of Wireless Sensor Networks: A Review

Babagana Sadiq — 2023-12-05

Low Energy Adaptive Clustering Hierarchy (LEACH) is a network of wireless sensors made up of tiny sensor nodes that are capable of sensing, processing, and transmitting information and feedback. These sensor nodes are distributed at random in a sensing environment or sensor field to sense real-world phenomena like heat, moisture, humidity, sound, vibration, etc., and then aggregate and send to the base station (BS). The significance of energy energy-effective routing algorithm has risen, since the energy constrain is the major factor affecting sensor nodes. To control and manage the energy consumption of sensor nodes, a significant number of techniques have been proposed by various scholars. This review paper presents published works that have been proposed for increasing the lifespan of wireless networks at the very beginning of this paper, a brief overview of Wireless networks, its architecture working and the problems associated with it are discussed. After the detailed overview of the approaches that have been presented for overcoming various limitations of current wireless systems. Lastly, in the conclusion of this paper the reviewed results were compared with earlier techniques, the results thus far show a notable improvement in the node mortality rate and network lifetime.

Combating Cybercrime Perpetrated Via Social Media Channels Using Individual Resilience Techniques

Francis Alexander Aleke Onyibe — 2024-01-01

Cybercrime is a social vice associated with modern society due to the rapid development of technology. Various studies over the years have shown that there is no society without an element of cybercrime. Cybercrime also has negative economic implications for nations and businesses globally. Over the years, several approaches have been employed to reduce the rate of cybercrime by employing various combating techniques. Hence, this study explores individual resilience techniques used in combating cybercrime perpetrated via social media channels in Abuja. Three goals and research agendas were developed to guide the research toward achieving the stated goal: a review of relevant literature, a qualitative and quantitative survey design involving about seven million, one hundred and ten thousand internet subscribers that use social media in Abuja, and a sample size of four hundred respondents from the study area were selected using the Taro Yamane purposive sampling technique. The respondents’ data were collected using a twelve-item structured questionnaire. Completed instruments of the sample size were analysed using mean values and standard deviations designed using Google Forms. The results showed that identity theft, cyberstalking, malware attacks, and cyber-casing are major cybercrimes perpetrated online by cyber attackers, and these attacks have led to harassment, child exploitation, digital piracy, and intentional damage to individuals’ online reputations. However, anti-malware, outlier detection, password managers, and multi-factor authentication (MFA) are various individual resilience techniques social media users can employ to combat cybercrime on social media. Creating more awareness of cybercrime and the various individual resilience techniques required in protecting social media accounts on web-enabled devices and setting up a special task force void of bias to help cybercrime victims regain their assets were recommended.

Mel-Frequency Cepstral Coefficients and Convolutional Neural Network for Genre Classification of Indigenous Nigerian Music

Akinosho Oluwadamilola — 2023-12-04

Music genre classification is a field of study within the broader domain of Music Information Retrieval (MIR) that is still an open problem. This study aims at classifying music by Nigerian artists into respective genres using Convolutional Neural Networks (CNNs) and audio features extracted from the songs. To achieve this, a dataset of 524 Nigerian songs was collected from different genres. Each downloaded music file was converted from standard MP3 to WAV format and then trimmed to 30 seconds. The Librosa sc library was used for the analysis, visualization and further pre-processing of the music file which includes converting the audio signals to Mel-frequency cepstral coefficients (MFCCs). The MFCCs were obtained by taking performing a Discrete Cosine Transform on the logarithm of the Mel-scale filtered power spectrum of the audio signals. CNN architecture with multiple convolutional and pooling layers was used to learn the relevant features and classify the genres. Six models were trained using a categorical cross-entropy loss function with different learning rates and optimizers. Performance of the models was evaluated using accuracy, precision, recall, and F1-score. The models returned varying results from the classification experiments but model 3 which was trained with an Adagrad optimizer and learning rate of 0.01 had accuracy and recall of 75.1% and 84%, respectively. The results from the study demonstrated the effectiveness of MFCC and CNNs in music genre classification particularly with indigenous Nigerian artists.

GIS-Based Flood Vulnerability Assessment Using Integral Value of Inverse Function Ranked Fuzzy-AHP Technique.

Atijosan Abimbola — 2023-11-30

Flooding is a common natural disaster which often causes extensive agricultural, infrastructural and socio-economic damages. In this study, a Geographic Information System (GIS) based flood vulnerability assessment using an improved integral value of inverse function ranked, Fuzzy Analytical Hierarchical Process (FAHP) technique for fast and accurate computation of flood vulnerability assessment across Oyo State, Southwest Nigeria is presented. The flood vulnerability assessment focuses on determining the spatial extent and flood vulnerability class of cultivated lands, settlements and road infrastructures across the study area for effective flood management. Based on the literature review, six prominent flood causative factors namely, elevation, slope, soil, rainfall, drainage density and land use/land cover were used as input criteria in this study. The improved integral value ranked FAHP technique uses both the left and right inverse function of a triangular membership function with an index of optimistic function to derive the weight for each input criterion. A flood vulnerability map for the study area was created using Geographic Information System (GIS) techniques based on the aggregation of the input causative criteria and their derived weights. Furthermore, maps showing the spatial extent and the flood vulnerability classes of cultivated lands, settlements and paved road infrastructures across the study area were made. The output vulnerability maps serve as an early warning system that would further assist policymakers and stakeholders in minimizing the effects of flooding on food security, road infrastructures, lives and properties across the study area.