Mobile Money Services (MMS), enabled by the wide adoption of mobile phones, offered an opportunit... more Mobile Money Services (MMS), enabled by the wide adoption of mobile phones, offered an opportunity for financial inclusion for the unbanked in developing nations. Meanwhile, the risks of cybercrime are increasing, becoming more widespread, and worsening. This is being aggravated by the inadequate security practises of both service providers and the potential customers' underlying criminal intent to undermine the system for financial gain. Predicting potential mobile money cyber threats will afford the opportunity to implement countermeasures before cybercriminals explore this opportunity to impact mobile money assets or perpetrate financial cybercrime. However, traditional security techniques are too broad to address these emerging threats to Mobile Financial Services (MFS). Furthermore, the existing body of knowledge is not adequate for predicting threats associated with the mobile money ecosystem. Thus, there is a need for an effective analytical model based on intelligent sof...
Cognitive Radio Networks (CRNs) have been conceived to improve the efficiency of accessing the sp... more Cognitive Radio Networks (CRNs) have been conceived to improve the efficiency of accessing the spectrum. However, these networks are prone to various kinds of attacks and failures that can compromise the security and performance of their users. One of the notable malicious attacks in cognitive radio networks is the Primary User Emulation (PUE) attack, which results in underutilization and unavailability of the spectrum and low operational efficiency of the network. This study developed an improved technique for detecting PUE attacks in cognitive radio networks and further addressed the characteristics of sparsely populated cognitive radio networks and the mobility of the primary users. A hybrid signal processing-based model was developed using the free space path loss and additive Gaussian noise models. The free space path loss model was used to detect the position of the transmitter, while the additive Gaussian noise model was used to analyze the signal transmitted, i.e., energy de...
In this paper, a paradigm of a Bayesian Network–based performance prediction model for computer n... more In this paper, a paradigm of a Bayesian Network–based performance prediction model for computer networks security risk management was emulated. Model simulation was carried out for the prediction model formulated. Java programming language tools were used to simulate, validate and verify the model. The core of simulation program was written in Java programming language. Some jar files were created in the code logic for all the modules in the prediction model. MS-DOS or command prompt was used to compile and run java and jar files. Batch scripts i.e. .bat files were written to compile the jar files. The output of the execution is shown using Java API files. Simulation technology was used in this study to evaluate network performance since it is very costly to deploy a complete test bed containing multiple networked computers, routers and data links to validate and verify the prediction model. The resulting risk impact on network confidentiality, Integrity and availability determine t...
International Journal of Communication Networks and Information Security (IJCNIS)
Insider threat in cyberspace is a recurring problem since the user activities in a cyber network ... more Insider threat in cyberspace is a recurring problem since the user activities in a cyber network are often unpredictable. Most existing solutions are not flexible and adaptable to detect sudden change in user’s behaviour in streaming data, which led to a high false alarm rates and low detection rates. In this study, a model that is capable of adapting to the changing pattern in structured cyberspace data streams in order to detect malicious insider activities in cyberspace was proposed. The Computer Emergency Response Team (CERT) dataset was used as the data source in this study. Extracted features from the dataset were normalized using Min-Max normalization. Standard scaler techniques and mutual information gain technique were used to determine the best features for classification. A hybrid detection model was formulated using the synergism of Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU) models. Model simulation was performed using python programming language. ...
The volume of cyber-attack targeting network resources within the cyberspace is steadily increasi... more The volume of cyber-attack targeting network resources within the cyberspace is steadily increasing and evolving. Network intrusions compromise the confidentiality, integrity or availability of network resources causing reputational damage and the consequential financial loss. One of the key cyber-defense tools against these attacks is the Intrusion Detection System. Existing anomalous intrusion detection models often misclassified normal network traffics as attacks while minority attacks go undetected due to an extreme imbalance in network traffic data. This leads to a high false positive and low detection rate. This study focused on improving the detection accuracy by addressing the class imbalanced problem which is often associated with network traffic dataset. Live network traffic packets were collected within the test case environment with Wireshark during normal network activities, Syncflood attack, slowhttppost attack and exploitation of known vulnerabilities on a targeted ma...
One of the key challenges faced in a Data Communication Network (DCN) is in managing the network.... more One of the key challenges faced in a Data Communication Network (DCN) is in managing the network. DCN consists of heterogeneous network, therefore controlling and managing the traffic in these networks is complex and difficult. One of the efficient routing schemes is the application of mobile agents in managing and optimizing the network resources. Deployment of mobile agents in a network decentralizes and distributes the network management functions and proactively carries out administrative tasks thereby improving the reliability and quality of service. They also reduce the bandwidth and the traffic need for the network management. Although, mobile agent reduces traffic, but the increase in the number of mobile agents and those with random route on the network consumes network bandwidth, introduces too much update overhead to host, and therefore, leads to a traffic deadlock. This book provides the need for improvement on the migration scheme of the mobile agent routing in a DCN to...
Bio-inspired intrusion detection solutions provide better detection accuracy than conventional so... more Bio-inspired intrusion detection solutions provide better detection accuracy than conventional solutions in securing cyberspace. However, existing bio-inspired anomaly-based intrusion detection sys...
Privacy and Security Challenges in Location Aware Computing
Currently in Nigeria, different crimes ranging from ethnic clashes, domestic violence, burglary, ... more Currently in Nigeria, different crimes ranging from ethnic clashes, domestic violence, burglary, financial fraud, kidnapping, pipe-line vandalism, and random killings by terrorist organizations, to mention a few, continue to plague the country. The conventional system of intelligence and crime record have failed to live up to the expectations as a result of limited security personnel, deficiency in effective information technology strategies, and infrastructures for gathering, storing, and analyzing data for accurate prediction, decision support, and prevention of crimes. There is presently no information system in Nigeria that provides a central database that is capable of storing the spatial distribution of various acts of terrorism based on the location where the crime is committed. This chapter presents the design of an information system that can be used by security agents for the storage and retrieval of criminal acts of terrorism in order to provide improved decision support ...
Privacy and Security Challenges in Location Aware Computing
Currently in Nigeria, different crimes ranging from ethnic clashes, domestic violence, burglary, ... more Currently in Nigeria, different crimes ranging from ethnic clashes, domestic violence, burglary, financial fraud, kidnapping, pipe-line vandalism, and random killings by terrorist organizations, to mention a few, continue to plague the country. The conventional system of intelligence and crime record have failed to live up to the expectations as a result of limited security personnel, deficiency in effective information technology strategies, and infrastructures for gathering, storing, and analyzing data for accurate prediction, decision support, and prevention of crimes. There is presently no information system in Nigeria that provides a central database that is capable of storing the spatial distribution of various acts of terrorism based on the location where the crime is committed. This chapter presents the design of an information system that can be used by security agents for the storage and retrieval of criminal acts of terrorism in order to provide improved decision support ...
Mobile Money Services (MMS), enabled by the wide adoption of mobile phones, offered an opportunit... more Mobile Money Services (MMS), enabled by the wide adoption of mobile phones, offered an opportunity for financial inclusion for the unbanked in developing nations. Meanwhile, the risks of cybercrime are increasing, becoming more widespread, and worsening. This is being aggravated by the inadequate security practises of both service providers and the potential customers' underlying criminal intent to undermine the system for financial gain. Predicting potential mobile money cyber threats will afford the opportunity to implement countermeasures before cybercriminals explore this opportunity to impact mobile money assets or perpetrate financial cybercrime. However, traditional security techniques are too broad to address these emerging threats to Mobile Financial Services (MFS). Furthermore, the existing body of knowledge is not adequate for predicting threats associated with the mobile money ecosystem. Thus, there is a need for an effective analytical model based on intelligent sof...
Cognitive Radio Networks (CRNs) have been conceived to improve the efficiency of accessing the sp... more Cognitive Radio Networks (CRNs) have been conceived to improve the efficiency of accessing the spectrum. However, these networks are prone to various kinds of attacks and failures that can compromise the security and performance of their users. One of the notable malicious attacks in cognitive radio networks is the Primary User Emulation (PUE) attack, which results in underutilization and unavailability of the spectrum and low operational efficiency of the network. This study developed an improved technique for detecting PUE attacks in cognitive radio networks and further addressed the characteristics of sparsely populated cognitive radio networks and the mobility of the primary users. A hybrid signal processing-based model was developed using the free space path loss and additive Gaussian noise models. The free space path loss model was used to detect the position of the transmitter, while the additive Gaussian noise model was used to analyze the signal transmitted, i.e., energy de...
In this paper, a paradigm of a Bayesian Network–based performance prediction model for computer n... more In this paper, a paradigm of a Bayesian Network–based performance prediction model for computer networks security risk management was emulated. Model simulation was carried out for the prediction model formulated. Java programming language tools were used to simulate, validate and verify the model. The core of simulation program was written in Java programming language. Some jar files were created in the code logic for all the modules in the prediction model. MS-DOS or command prompt was used to compile and run java and jar files. Batch scripts i.e. .bat files were written to compile the jar files. The output of the execution is shown using Java API files. Simulation technology was used in this study to evaluate network performance since it is very costly to deploy a complete test bed containing multiple networked computers, routers and data links to validate and verify the prediction model. The resulting risk impact on network confidentiality, Integrity and availability determine t...
International Journal of Communication Networks and Information Security (IJCNIS)
Insider threat in cyberspace is a recurring problem since the user activities in a cyber network ... more Insider threat in cyberspace is a recurring problem since the user activities in a cyber network are often unpredictable. Most existing solutions are not flexible and adaptable to detect sudden change in user’s behaviour in streaming data, which led to a high false alarm rates and low detection rates. In this study, a model that is capable of adapting to the changing pattern in structured cyberspace data streams in order to detect malicious insider activities in cyberspace was proposed. The Computer Emergency Response Team (CERT) dataset was used as the data source in this study. Extracted features from the dataset were normalized using Min-Max normalization. Standard scaler techniques and mutual information gain technique were used to determine the best features for classification. A hybrid detection model was formulated using the synergism of Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU) models. Model simulation was performed using python programming language. ...
The volume of cyber-attack targeting network resources within the cyberspace is steadily increasi... more The volume of cyber-attack targeting network resources within the cyberspace is steadily increasing and evolving. Network intrusions compromise the confidentiality, integrity or availability of network resources causing reputational damage and the consequential financial loss. One of the key cyber-defense tools against these attacks is the Intrusion Detection System. Existing anomalous intrusion detection models often misclassified normal network traffics as attacks while minority attacks go undetected due to an extreme imbalance in network traffic data. This leads to a high false positive and low detection rate. This study focused on improving the detection accuracy by addressing the class imbalanced problem which is often associated with network traffic dataset. Live network traffic packets were collected within the test case environment with Wireshark during normal network activities, Syncflood attack, slowhttppost attack and exploitation of known vulnerabilities on a targeted ma...
One of the key challenges faced in a Data Communication Network (DCN) is in managing the network.... more One of the key challenges faced in a Data Communication Network (DCN) is in managing the network. DCN consists of heterogeneous network, therefore controlling and managing the traffic in these networks is complex and difficult. One of the efficient routing schemes is the application of mobile agents in managing and optimizing the network resources. Deployment of mobile agents in a network decentralizes and distributes the network management functions and proactively carries out administrative tasks thereby improving the reliability and quality of service. They also reduce the bandwidth and the traffic need for the network management. Although, mobile agent reduces traffic, but the increase in the number of mobile agents and those with random route on the network consumes network bandwidth, introduces too much update overhead to host, and therefore, leads to a traffic deadlock. This book provides the need for improvement on the migration scheme of the mobile agent routing in a DCN to...
Bio-inspired intrusion detection solutions provide better detection accuracy than conventional so... more Bio-inspired intrusion detection solutions provide better detection accuracy than conventional solutions in securing cyberspace. However, existing bio-inspired anomaly-based intrusion detection sys...
Privacy and Security Challenges in Location Aware Computing
Currently in Nigeria, different crimes ranging from ethnic clashes, domestic violence, burglary, ... more Currently in Nigeria, different crimes ranging from ethnic clashes, domestic violence, burglary, financial fraud, kidnapping, pipe-line vandalism, and random killings by terrorist organizations, to mention a few, continue to plague the country. The conventional system of intelligence and crime record have failed to live up to the expectations as a result of limited security personnel, deficiency in effective information technology strategies, and infrastructures for gathering, storing, and analyzing data for accurate prediction, decision support, and prevention of crimes. There is presently no information system in Nigeria that provides a central database that is capable of storing the spatial distribution of various acts of terrorism based on the location where the crime is committed. This chapter presents the design of an information system that can be used by security agents for the storage and retrieval of criminal acts of terrorism in order to provide improved decision support ...
Privacy and Security Challenges in Location Aware Computing
Currently in Nigeria, different crimes ranging from ethnic clashes, domestic violence, burglary, ... more Currently in Nigeria, different crimes ranging from ethnic clashes, domestic violence, burglary, financial fraud, kidnapping, pipe-line vandalism, and random killings by terrorist organizations, to mention a few, continue to plague the country. The conventional system of intelligence and crime record have failed to live up to the expectations as a result of limited security personnel, deficiency in effective information technology strategies, and infrastructures for gathering, storing, and analyzing data for accurate prediction, decision support, and prevention of crimes. There is presently no information system in Nigeria that provides a central database that is capable of storing the spatial distribution of various acts of terrorism based on the location where the crime is committed. This chapter presents the design of an information system that can be used by security agents for the storage and retrieval of criminal acts of terrorism in order to provide improved decision support ...
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