Mobile ad hoc networks (MANETs) are faced with various security challenges emanating from malicious attacks. Their dynamic nature make nodes more vulnerable to attacks from either malicious nodes or intruders since there is no fixed infrastructure resulting in each node acting as router to transmit data. Currently, several solutions have been proposed and implemented in different ways aimed at eliminating or reducing these malicious attacks. However, the attacks still persist. Therefore, this paper proposes an efficient security mechanism based on machine learning as a solution that detects and identifies malicious attacks in real-time basis by classifying packets data as either normal or abnormal. To achieve this, we conducted experiments using logistic regression (LR) and a support vector machine (SVM) to choose the best predictive model utilizing the Iris data set. The results obtained show that LR performed better than SVM with an accuracy of 100% detection rate. Thus, LR is better suited for the identification of malicious attacks in MANETs. Furthermore, we proposed and designed a framework to detect malicious attacks in real-time in MANETs based on packet behavior using the LR model and the components were presented. We believe that, if this framework is implemented in MANETs, it could go a long way to reduce the rate of attacks in the infrastructure less network.

Drink-driving and over-speeding of vehicles are the major causes of injuries and deaths on the road globally and South Africa (SA) is not an exception. Different systems which are currently used in detecting high alcohol concentration in drivers’ breath and detecting vehicles that exceeds stipulated speed limit are not effective, efficient and poses health risks to traffic personnel. In an attempt to provide effective solutions to these challenges, this paper proposed a smart transportation system for real-time detection of drink-driving and over-speeding on the roads using technology of vehicular networks. The objective is to allow for early intervention by traffic personnel aim at saving lives before actual accident occurred. We designed a theoretical framework of the system and implemented an application prototype which is web-based for use by traffic personnel to monitor the detection of traffic offenders in the capacity of drink-driving and over-speeding. We presented and discussed the operation of the system as well as the functionalities it offers. Additionally, we utilized the application to simulate the actual system and based on its working, we found that the system is feasible and can accomplish the tasks of road safety more effective than the existing approaches.

Software Defined Networks (SDNs) is a network technology developed to deal with several limitations faced by the current traditional networks. However, SDN itself is confronted with security challenges which emanates specifically from its platform, given the explosive growth in network attacks and threats. Though many solutions have been developed and proposed, the continual lack of trust between the SDN controller and the applications running atop the control plane poses a great security challenge. SDN controller can easily be attacked by malicious/compromised applications which can result in network failure as the controller represents a single point of failure. Though trust mechanisms to certify network devices exist, mechanisms to certify management applications are still not well developed. Therefore, this paper proposes a novel direct trust establishment framework between an OpenFlow-based SDN controller and applications. The objective is to ensure that SDN controller is protected and diverse applications that consumes network resources are always trusted throughout their lifetime. Additionally, the paper introduce the concept of trust access matrix and application identity to ensure efficient control of network resources. We believe that, if the proposed trust model is adopted in the OpenFlow architecture, it could go a long way to improve the security of the SDN.

Refactoring is used to improve deteriorated software design, code and their maintainability. In object-oriented (OO) code, before refactoring is performed, its opportunities must be identified and several approaches exist this regard. Among the approaches is the software metric-based approach where quality software metrics are used. Therefore, this paper provide analysis of existing empirical studies that utilized software metrics to identify refactoring opportunities in OO software systems. We performed a comprehensive analysis on 16 studies to identify the state-of-the-practice. The focal point was on the workings, refactoring activities, the programming language and the impact on software quality. The results obtained shows approaches were not unique, each was designed either for a single refactoring activity or couple of them, move method and extract class dominated the refactorings activities, and most approaches were fully automated while few were semi-automated. Moreover, OO metrics played acritical role in both opportunities detection and factoring decisions. Based on the results, it would be beneficial if generic refactoring approach is developed that is capable of identifying needs for all refactoring activities.

Effective and efficient public service delivery like healthcare services are very important in today’s society, especially in the rural areas. People in rural areas are expected to have access to public facilities at all times. However, these services are not always available when they are needed. This paper discusses the problems faced by rural areas of Mafikeng in South Africa (SA) when public and basic healthcare facilities like medical ambulance transports are needed during emergency situation. The challenges ranges from poor communication, poor road network and unstructured address to non-arrival of ambulances leading loss of lives that are preventable. This paper designed and implemented a system prototype using mobile application technologies to offer cost-effective services to patients during emergencies. It is intended to reduce long queues in hospitals and long waiting periods for an ambulance via location-based services. By using this application, lives in the rural areas can be made easier and loss of lives prevented by providing timely response from the appropriate healthcare providers during emergencies.

Object-oriented (OO) software have complex dependencies and different change types which frequently affect their maintenance in terms of ripple-effects identification or may likely introduce some faults which are hard to detect. As change is both important and risky, change impact analysis (CIA) is a technique used to preserve the quality of the software system. Several CIA techniques exist but they provide little or no clear information on OO software system representation for effective change impact prediction. Additionally, OO classes are not faults or failures-free and their fault-proneness is not considered during CIA. There is no known CIA approach that incorporates both change impact and fault prediction. Consequently, making changes to software components while neglecting their dependencies and fault-proneness may have some unexpected effects on their quality or may increase their failure risks. Therefore, this paper proposes a novel framework for OO software CIA that allows for impact and fault predictions. Moreover, an intermediate OO program representation that explicitly represents the software and allows its structural complexity to be quantified using complex networks is proposed. The objective is to enhance static CIA and facilitate program comprehension. To assess its effectiveness, a controlled experiment was conducted using students’ project with respect to maintenance duration and correctness. The results obtained were promising, indicating its importance for impact analysis.

The teaching of computer programming is one of the greatest challenges that have remained for years in Computer Science Education. A particular case is computer programming course for the beginners. While the traditional objectivist lecture-based approaches do not actively engage students to achieve their learning outcome, we believe that integrating some cutting-edge processes and practices like agile method into the teaching approaches will be leverage. Agile software development has gained widespread popularity and acceptance in the software industry and integrating the ideas into teaching will be constructive. In the educational system, while the positive impact of agile principles has been felt on students’ projects, none has been experienced on the teaching aspect. Therefore, this paper proposes the use of agile process in the teaching of first year programming courses. The goal is to help the beginners develop their programming skills, proffer a teaching technology that maximizes students’ chances of engagement, improve teaching as teachers reflects on what they are teaching and what the students are learning. Additionally, beginners will be able to operate the computer, program, and improve their programming skills through active team collaboration as well as managing large classes effectively by the teacher.