Computer Science & Communications
http://repository.embuni.ac.ke/handle/123456789/822
2024-03-29T15:53:04ZEnhancing Multi-Factor Authentication in Modern Computing
http://repository.embuni.ac.ke/handle/123456789/1323
Enhancing Multi-Factor Authentication in Modern Computing
Iwuoha, Obioha2; Emmanuel, Nwabueze1; Ekwonwune, Emmanuel
Most network service providers like MTN Nigeria, currently use two-factor authentication for their 4G wireless networks. This exposes the network subscribers to identify theft and users data to security threats like snooping, sniffing, spoofing and phishing. There is need to curb these problems with the use of an enhanced multi-factor authentication approach. The objective of this work is to create a multi-factor authentication software for a 4G wireless network. Multi-factor authentication involves user’s knowledge factor, user’s possession factor and user’s inherence factor; that is who the user is to be presented before system access can be granted. The research methodologies used for this work include Structured System Analysis and Design Methodology, SSADM and Prototyping. The result of this work will be a Multi-factor authentications software. This software was designed with programming languages like ASP. NET, C# and Microsoft SQL Server for the database.
2017-07-01T00:00:00ZTowards the Development of Best Data Security for Big Data
http://repository.embuni.ac.ke/handle/123456789/1319
Towards the Development of Best Data Security for Big Data
Yuan, Tian
Big data is becoming a well-known buzzword and in active use in many areas. Because of the velocity, variety, and volume of big data, security and privacy issues are magnified, which results in the traditional protection mechanisms for structured small scale data are inadequate for big data. Sensitivities around big data security and privacy are a hurdle that organizations need to overcome. In this paper, we review the current data security in big data and analysis its feasibilities and obstacles. Besides, we also introduced intelligent analytics to enhance security with the proposed security intelligence model. This research aims to summarize, organize and classify the information available in the literature to identify any gaps in current research and suggest areas for scholars and security researchers for further investigation.
2017-11-01T00:00:00ZPractical Approaches to Securing an IT Environment
http://repository.embuni.ac.ke/handle/123456789/1317
Practical Approaches to Securing an IT Environment
John C, Fuller; Cofie, Penrose; Warsame H, Ali; Emmanuel S., Kolawole
There are a number of IT Security journals available in the literature but none of these research papers have practically specified approaches to secure the IT environment at large. In this paper, more emphases will be laid on the practical ways to secure our IT environments and with some useful real-life scenarios. In today, securing our IT environment has become the key factor in the industry due to an increasing number of attackers invading and stealing the intellectual properties; thereby, rendering most IT industries to go out of businesses. They may find that understanding and translating IT security recommendations to implementable practices can be overwhelming. While this is a worthwhile and important task, there are also more practical ways to ensure you are using IT security best practices in your business. Therefore, the need to properly secure our IT environments in order to mitigate those attacks by using the right tools in all IT domains will be fully discussed in this research. This paper will focus more on protection of LAN-WAN Domain as a use case.
2017-11-01T00:00:00ZIntelligent and Predictive Vehicular Networks
http://repository.embuni.ac.ke/handle/123456789/1243
Intelligent and Predictive Vehicular Networks
Chintu, Schmidt S.; Anthony, Richard; Roshanaei, Maryam; Ierotheou, Constantinos
Seeking shortest travel times through smart algorithms may not only optimize the travel times but also reduce carbon emissions, such as CO2, CO and Hydro-Carbons. It can also result in reduced driver frustrations and can increase passenger expectations of consistent travel times, which in turn points to benefits in overall planning of day schedules. Fuel consumption savings are another benefit from the same. However, attempts to elect the shortest path as an assumption of quick travel times, often work counter to the very objective intended and come with the risk of creating a “Braess Paradox” which is about congestion resulting when several drivers attempt to elect the same shortest route. The situation that arises has been referred to as the price of anarchy! We propose algorithms that find multiple shortest paths between an origin and a destination. It must be appreciated that these will not yield the exact number of Kilometers travelled, but favourable weights in terms of travel times so that a reasonable allowable time difference between the multiple shortest paths is attained when the same Origin and Destinations are considered and favourable responsive routes are determined as variables of traffic levels and time of day. These routes are selected on the paradigm of route balancing, re-routing algorithms and traffic light intelligence all coming together to result in optimized consistent travel times whose benefits are evenly spread to all motorist, unlike the Entropy balanced k shortest paths (EBkSP) method which favours some motorists on the basis of urgency. This paper proposes a Fully Balanced Multiple-Candidate shortest path (FBMkP) by which we model in SUMO to overcome the computational overhead of assigning priority differently to each travelling vehicle using intelligence at intersections and other points on the vehicular network. The FBMkP opens up traffic by fully balancing the whole network so as to benefit every motorist. Whereas the EBkSP reserves some routes for cars on high priority, our algorithm distributes the benefits of smart routing to all vehicles on the network and serves the road side units such as induction loops and detectors from having to remember the urgency of each vehicle. Instead, detectors and induction loops simply have to poll the destination of the vehicle and not any urgency factor. The minimal data being processed significantly reduce computational times and the benefits all vehicles. The multiple-candidate shortest paths selected on the basis of current traffic status on each possible route increase the efficiency. Routes are fewer than vehicles so possessing weights of routes is smarter than processing individual vehicle weights. This is a multi-objective function project where improving one factor such as travel times improves many more cost, social and environmental factors.
2014-05-01T00:00:00Z