Mutual Authentication in Wimax Security using Diffie Hellman

Network security is becoming an area of concern with the expansion of wireless technology. Many businesses have lost a lot of money as a result of compromised network security. The Worldwide Interoperability for Microwave Access (WiMAX) is one example of 3G technology which is getting popular. Most business establishemnst use WiMAX to network their communication equipments. The popularity of WiMAX and its security vulnarability are the key motivation for this study. Presently, PKM versions of authentication are used to secure WiMAX networks. The PKM authentication methods expose the WiMAX network to third party risks like Man in the Middle attacks, eavesdropping and jamming attacks.  WiMAX is thus vulnerable to network attacks that compromise the radio links between the communicating Subscriber Station (SS) and the serving Base Station (BS). The PKMv1 process involves a one sided authentication. The BS authenticates the SS but the SS has no capacity to authenticate a BS. As a result, a rogue BS can successfully enter the network of a SS without prevention. The rogue BS can then tap all the unencrypted management messages. This constitutes a major security flaw. The Man-In- The-Middle (MITM) attack exploits this weakness in the network by eavesdropping, interception and fabrication of the management messages, resulting in a breach in the reliability of the entire network. In this research, a modification of the Diffie-Hellman (DH) key exchange protocol is used to mitigate the man-in-the middle attack in WiMAX by modeling using the Dev C++ programming language. The DH protocol uses a unique algorithm whose solution must be obtained by both the SS and the BS for communication to be allowed. Both the BS and the SS are given an opportunity to authenticate one another before any communication can proceed. Keywords: Diffie Hellman; Mutual Authentication; Security; WiMAX

Evaluation of Effects of Value Addition in Sweet Potatoes on Farm Income in Homa Bay County, Kenya

Sweet potato value addition has become an increasingly important aspect in improving the diversification in its production and expanding the unexploited market amongst consumers. Homa Bay County is among the leading areas of production in Kenya due to its favorable land conditions and rainfall patterns that enables sweet potato to thrive well in the region. Value addition has been introduced in the County mainly by Non-Governmental organizations that work together with the public sector. However some small scale farmers do not practice value addition, partially because little has been done empirically to measure the impact that value addition has on farm income. This study focused on filling in this gap in the existing knowledge on sweet potato value addition. The study was conducted in Homa Bay County and the study sites selected included three sub counties namely Kasipul, Kabondo Kasipul and Ndhiwa. Multi stage sampling technique was used in selecting the study sites and the required sample size determined by proportionate to size sampling method. Interview schedules and observation were used to collect primary data. Multiple regressions were used to analyze the effect of different value addition activities on Income received solely from sweet potatoes. In addition marginal effects were obtained to analyze the effect of each independent variable separately on income. Findings revealed that the more value a farmer added to raw tuber, the better the income obtained from the market. In addition, farmer marketing groups had a stronger bargaining power in the market compared to farmers selling individually. The study therefore recommended that the County government should work closely with the non-governmental organizations to enlighten farmers on the importance of forming farmer groups since most training on value addition, information on prices and market opportunities can be easily disseminated through farmer groups .It is through these trainings that farmers would be able to make rational decisions with regard to production and adding value to get higher incomes. Keywords: Value Addition techniques, Smallholder farmer, Farm income.

Effects of Micro Credit on Welfare of Households: The Case of Ainamoi Sub County, Kericho County, Kenya

This study examined factors affecting access of micro credit, the levels availed and their effects on households’ incomes and expenditures in Kericho County, specifically in Ainamoi Sub County, Kenya. In the study area, different portfolios have been used to extend credit, suggesting ability to reach a wide section of all cadres of the population. However, the impact on the welfare across beneficiaries had not been established. This study sought to fill this knowledge gap. To capture this, a sample of 96 households which had accessed micro credit was compared with a similar number which had not accessed micro credit. Stratification of households was done according to their membership to microfinance institutions. Random sampling method was used to select loan beneficiary households. The data was collected by administration of a structured questionnaire and it was analyzed using the SPSS and other statistical techniques. Heckman selection model was applied to identify the factors and their effect on the level of participation of households in the micro credit. Difference in difference (DID) model was used to analyze the effects of micro credit on incomes and expenditure of households. From the findings, this study concluded that participation in microcredit program resulted in improvement of the beneficiaries’ quality of life. From the study, Policy implications were drawn for improving access and the levels of participation in micro credit programme. Key words: Micro credit, Households, Heckman selection model, Difference in Difference

Factors Determining Choice of Clean Domestic Energy by Households: Evidence from Nakuru Municipality, Kenya

As in most developing countries, many attempts have been made and are continuously made to in Kenya to reduce dependence of forests as a source of energy through introduction of bans on logging and campaigns to households to shift to cleaner energy sources. Attempts through rural electrification program as envisaged in the energy policy of Kenya have been geared towards expanding clean energy access to previously unconnected sections of the population. Yet the majority households in urban areas as exemplified by Nakuru municipality residents of Kenya continue to depend on semi-clean fuels as primary source of energy. Using survey data from 300 randomly selected households in Nakuru Municipality, we sought to empirically determine the factors that influence household choice of clean domestic energy. A Multinomial logit model results showed that household’s choice between clean and semi-clean fuels was influenced by Socio-economic and demographic factors, and government energy policies. In particular,  the likelihood of clean fuels was significantly higher in households with higher relative incomes while the likelihood of use of “dirty” and semi – clean fuels was higher with middle and low income households. Based on the study results we draw policy implications. Keywords: Energy, Choice and Domestic Fuels, Multinomial Logit, Kenya, Nakuru Municipalit

Influence of Selected Econonic Factors on Girl child Participation in Secondary School Education in Bureti Sub county, Kenya

This study, carried out in Bureti  Sub County,  sought to investigate selected economic factors that affect girl child’s participation in secondary school education in Bureti Sub county. The sub county had 62 secondary schools of which 15 were girls’ schools while 30 were mixed secondary schools and 17 were boys’ schools. The entire sub county had a total population of 12250 students and 406 teachers. The target populations were 5541 Female students and 62 secondary school teacher counselors in thesub countyt. Descriptive Survey research design was used in this study.  A saniple of 360 female students and 16 teacher counselors were drawn from 15 girls’  schools and mixed secondary schools in thesub county using stratified sampling technique. Students and teachers’ questionnaires were used to collect therequired data from therespondents. Research Instruments were validated through pilot study and reliability of 0.75 was determined using theCronbach’s alpha procedure. Descriptive statistics; mean, frequencies and percentages were used to analyze thedata while Statistical Packages for Social Sciences (SPSS) program was used for analysis. From thestudy, it was established that themost common factors that affected girl child participation in secondary school education were parents’ level of income. These have led to a number of girls dropping out of school. As a recommendation, the govemment should aid education of the girl child through provision of bursaries as effort to ensure equal participation by all students irrespective of their gender.. Key words: Girl Child, Participation, Economic factors,Secondary school educatio

Ethical analysis of science, technology and innovation policies in four East African countries

Thesis submitted in partial fulfillment of the requirements for the Degree of Masters in Applied Philosophy and Ethics (MAPE) at Strathmore University, KenyaScience, Technology and Innovation (ST&I) policy is an essential part of the larger public policy programming in order to improve livelihoods and quality of life. Extant literatures indicate that policy-making is driven largely by economic considerations. Policy studies came into being largely as a response to a need to guide development of nations and competition among them. However, there has been a resurging interest in ethics of policies in the last few years as a response to the empiricist approach that followed the Second World War. Partly, this is due to concerns about policy makers‟ failure to address the moral ambiguity in technology development and adoption, and possible dire consequences that could arise from this failure. The main objective of the study was to analyze the ethical frameworks underlying the ST&I policies of Kenya and three selected eastern African countries namely Uganda, Tanzania and Rwanda using content analysis. The study found that the policies are predominantly utilitarian in Kenya, Rwanda and Uganda. In Tanzania it was found to be duty based. On whether it is necessary analyze ethics in ST&I policy, it was found that there are compelling reasons to undertake this task as this would give technology a more useful measure for determining whether it is responding to man‟s need for authentic development

Farm Forestry Development in Kenya: A Comparative Analysis of Household Economic Land Use Decisions in UasinGishu and Vihiga Counties

Tree growing on farms in Kenya is an important land use that has evolved over the last 100 years into multi-billion subsistence and commercial oriented enterprises.  The smallholder farms in medium and high potential areas are facing serious shortage of quality farming land that has created severe competition among various competing land uses mostly agriculture and farm forestry. Therefore the economic competitiveness of farm forestry as a land use is assumed to be proportional to the size of household land allocated to its use. Understanding household decisions making in allocation of land to competing land uses has increasingly become an important subject to resource economists and policy makers. Therefore a study was undertaken in 2011/2012 to evaluate the socioeconomic decisions making in relations to farm forestry in two counties in high potential agricultural areas of western Kenya. The two counties were selected for the study differed settlement in history, agricultural land use, farm forestry development and demographic characteristics. Uasin Gishu represents the recently settled former European settler farms and Vihiga to represents the former African Reserves. The study was based on range of models such as spatial land use concepts, integrated land use decision making and land use efficiency criterion to underpin the household production function.  260 households were surveyed using systematic sampling methods with questionnaires being administered randomly to households in locations within selected divisions.  The main data extracted from the standard questionnaire were household structure, ratio of land used for cropping, grazing and farm forestry, product output, prices, market information, marketing procedures and distribution of trees by species.  Data was analysed by use of OLS regression models to generate key farm forestry decision making parameters.  The results show that household land size had strong influence on farm forestry decisions irrespective of household’s production strategy.  Farm forestry incomes proved to be an importance driving force in decisions to plant trees thus supporting the importance of economic objectives on household land use decisions. A farm forestry income was stronger in areas where markets and marketing infrastructure were better developed.  The density of planted trees increased with decreasing land size attested the strength of subsistence and commercial dimension of trees within an agricultural landscape. The study points out some policy lessons for development of farm forestry in developing countries like Kenya that include putting in place policies and regulations that attract, expand and sustain farm forestry product demand and infrastructure that improve marketing efficiency and thus better income to farmers from sale of trees. Keywords: Farm forestry, Land use, Household decision makin

The Influence of Land Quality on Allocation of Land for Farm Forest in Kenya: The Case of Vihiga County

Kenya has long history of promoting tree growing on farms for various purposes ranging from  laying claim to property and boundary marking in 1940s to response to socioeconomic drivers such commercial interests through vibrant market for tree products. The Rural Afforestation and Extension Services Division (RAES) started in 1971 was aimed at accelerating tree growing on farms through training of farmers, establishment of tree nurseries countrywide and deployment of extension staff to offer technical services to rural farmers. Farms within agricultural landscapes are not uniform but differ in various forms such as slope, drainage, soil texture, fertility, water holding capacity, stone/rock outcrops and other attributes that impose land quality variation hence influencing their potential uses. The study was therefore undertaken to evaluate the influence of land quality on farm forest land use allocation through use of land quality concept developed by von Thunnen in 1826.  The study was done in one of the highly populated counties in western Kenya, the Vihiga County where farm forests occupies 30% of household land. Samples of 112 households were surveyed in 4 sub-counties. The study mapped quality aspects within households land profile into four categories  gentle,  steep, steep and rocky and flood plain and swampy and intensity of trees in respective category. OLS regression analysis was used to determine the influence of land quality on farm forest land allocations. The results indicate that farm forest allocations was not significantly influenced by poor land quality aspects across the study household lands. This is because the land sizes were very small and farm forests were adopted across the household land profile irrespective of quality aspects. However, households indicated that poor quality lands were preferable for farm forest largely for they were not favourable for crop production. The study observes that farm forests were highly influenced  by high population density and small land sizes that has masked the importance land quality in land use allocation decisions. Keywords: farm forest, land quality, land use allocatio

A Review Farm Forestry Evolution for the Last 100 Years in Kenya: A Look at Some Key Phases and Driving Factors

The study reviews the evolution of tree growing in Kenya from pre-colonial through colonial to the present day in order to understand some factors that have influenced such developments. The study is based on desktop literatures reviews of various studies done in the country over the years and the authors’ experiences. The study indicates that forest resources management during pre-colonial period were based on individual communities’traditional structures that ensured that its members had abundant supplies of land and resources to support their socioeconomic activities. Forestlands were viewed as reserves for future agricultural expansion depending on community population growth and settlement patterns. In 1895 the country was declared British Protectorate that heralded the entry of colonial settlers that drastically changed land ownership through displacement and concentration of indigenous populations. Improved health services led to drastic population growths that further shrunk available productive land and forest resources to levels that could not adequately accommodate traditional land uses. The resultant was seriousland degradation in Africa reserves that prompted the Colonial Government to initiate agricultural and land use transformations that included afforestation in highly populated for environmental conservation, boundary marking and supply of tree products. Another parallel development was forest reservation and expansion of public plantation by Forest Department that involved planting of fast growing exotic species such as Eucalyptus, Pines and Cypress among others that diffused to neighbouring farms, missionary centres, schools and emerging elite Africans for amenity and social status. The emergence of Acacia mearnsii as a cash crop for African farmers in Central and western Kenya in 1930s was another development that enhanced adoption of tree growing on farms in the country. After independence in 1963 more policies and strategies to promote tree growing on former settler farms and African reserves for environmental conservation and subsistence needs implemented.  The last chapter of the farm forestry evolution was the commercialization of farm forestry operations due increased demand for various forest products beyond the capacity of public forests. The key markets niches mostly for firewood in tea processing, transmission poles manufacturing, charcoal and sawnwood for rural and urban markets were lucrative enough to motivate millions of smallholder farmers to expand their farm forestry investments. The markets based incentives to meet the growing demand for various products has transformed farm forestry in Kenya into multibillion sector enterprises that competes with public and private plantations products in local markets. The lessons learnt in Kenya case is the multiple factors that have shaped farm forestry development over the last 100 years and the critical role played by market related factors that enabled smallholder tree growers to enter into lucrative short rotation wood product markets. Keywords: Farm forestry evolution, phases, driving factor

Socioeconomic Factors Influencing Farm Forestry Investment Decisions in Kenya: The Case of Uasin Gishu and Vihiga Counties

In Kenya, traditional farm landscapes are an overlay agricultural crops livestock and various farm forest formations. Tree growing in agricultural landscapes in the country has a long history. However the intensity has developed over the last 100 years across the country at varying pace and configurations depending on various factors largely driven by demand and supply conditions. Therefore the study was premised on the fact that household land is allocated to tree growing based on the household subsistence needs and extra to satisfy market demands. The study to evaluate the socioeconomic factors that influenced adoption farm forestry by households in two counties in high potential agricultural areas of western Kenya was undertaken in 2015. The two counties were selected for the study differed in various attributes such as settlement history, agricultural land use, farm forestry development and demographic characteristics. Uasin Gishu represents the recently settled former European settler farms and Vihiga represents the former African Reserves settled hundreds of years ago. The study used integrated land use decision making concept to underpin the household production function.  The survey involved 260 households that were systematically sampled with questionnaires being administered randomly to households in locations within selected sub counties. The main data extracted from the questionnaire were household land sizes, age of household head, educational levels of household head, cultural factors, farm forest incomes, distance to forest product markets, farm employees, settlement years, household sizes and crop incomes.  Data was analysed by use of OLS regression models to generate key farm forestry decision making variables.  The results show that the most stable and significant explanatory variables were land size, farm forestry incomes and off-farm incomes. This shows that they were the most important variables in farm forestry land use decisions in western Kenya.  The study also revealed that the two counties were significantly different in their farm forestry activities with Vihiga being more intensive as compared to Uasin Gishu.  Farm forestry incomes proved to be an importance driving force in scaling up tree growing on individual farms hence indicating the importance of economic objectives on household land use decision making. Farm forest income was stronger in areas where markets and marketing infrastructure were better developed. The study provides some factors that policy makers need to consider in order to positively influence farm forest development in Kenya and other developing countries. Keywords: Farm forestry, Land use, farm incomes, household decision makin