https://repository.seku.ac.ke/handle/123456789/82 2026-03-17T13:09:53Z 2026-03-17T13:09:53Z Kasyoka, Philemon https://repository.seku.ac.ke/handle/123456789/7493 2024-01-19T08:45:19Z 2022-01-01T00:00:00Z

Title: Certificateless signcryption for Wireless Sensor Networks Authors: Kasyoka, Philemon Abstract: Wireless sensor networks (WSNs) have become popular in the field of information and communications technology, they are increasingly being used in applications such as surveillance systems, patient monitoring, object tracking, forest fire detection and habitat monitoring among others. By its very nature, a WSN provides a resource constrained environment where devices used are limited in resource usage. Due to these limitations, security challenges have emerged in their applications. Hence, the need for computationally efficient but still secure cryptosystems. Traditional cryptographic primitives cannot be directly applied on WSNs due to their resource constrained nature, this has led to the challenge of achieving cryptographic security goals which are important for effective communication of information on WSNs. Recent studies have shown that it is possible to apply public key cryptography such as ECC to resource constrained devices by using the right selection of algorithms and associated parameters, optimization and low power concepts. To address security challenges on WSNs, this thesis proposed an efficient digital signature scheme, a variant of ECDSA that can be applied on WSNs to provide authentication. Further, the variant of ECDSA was used in the design of a signcryption schemes. The signcryption schemes are intended to be efficient enough for use on WSNs and for that reason the research work focused on certificateless cryptography (CLC) for the design of the signcryption scheme with a property of ciphertext authenticity. The research methodology employed was experimental. Major contributions of this research were an efficient variant of ECDSA more efficient in the signing and verification process that does not suffer from the security challenges inherent in the original ECDSA. Out of the proposed digital signature scheme a certificateless pairing free authentication scheme for wireless body area network in healthcare management system and a multi-user broadcast authentication scheme for WSNs were constructed. Three certificateless signcryption schemes were designed, two signcryption schemes were designed from the proposed ECDSA variant and one signcryption was a modification of a scheme by Wei and Ma (2019). A formal security proof for indistinguishability against adaptive chosen ciphertext attack and existential unforgeability against adaptive chosen message attack was provided for the three signcryption schemes in the random oracle model. The signcryption schemes were more efficient with respect to computational cost, communication overhead and energy consumption comparison with other existing related schemes. Description: Doctor of Philosophy in Computer Science, 2022

2022-01-01T00:00:00Z Waswa, Gabriel A. https://repository.seku.ac.ke/handle/123456789/6793 2023-11-30T09:56:55Z 2022-06-02T00:00:00Z

Title: Characterization and application of nanozeolitic materials as smart delivery systems for urea fertilizer and lambda cyhalothrin pesticide Authors: Waswa, Gabriel A. Abstract: Natural zeolites could be applied as smart delivery system for controlled release of agricultural inputs resulting in enhanced productivity and reduced environmental pollution caused by excessive use of fertilizer and pesticides. This is because zeolites have nano porous voids and channels that can be loaded with quest molecules like urea fertilizer and pesticides. The formulated zeolite composites can then be applied as carrier agent for target and slow delivery of the fertilizer or pesticide to the intended part of the plants, thus improving the efficiency and effectiveness of the agricultural inputs. Besides, these zeolites being natural are meant to be more cost effective and pose less harm to the environment. This research work aimed at sampling natural zeolites from different parts in Kenya and characterizing them in comparison with the commercial zeolites applied as the standard. Kinetics studies were then conducted to determine their fertilizer and pesticide loading properties. After which formulation, modelling, and agronomic simulation studies were done using urea and lambda cyhalothrin pesticide on tomatoes and spinach. Sample collection was done, guided by Kenya’s geological and mineralogical mapping in five selected places named as Eburru volcanic crater, Lake Magadi, Lake Baringo, Ebulbul-Ngong, and Kitum caves-Mt. Elgon. The collected samples transported to the laboratory were mechanically grinded and sieved to obtain homogeneous fine particles... Description: Doctor of Philosophy Degree in Chemistry, 2020

2022-06-02T00:00:00Z Mutwiri, Robert M. https://repository.seku.ac.ke/handle/123456789/6354 2023-11-30T09:48:28Z 2021-10-07T00:00:00Z

Title: Statistical distributions and modelling of GPS-Telemetry elephant movement data including the effect of covariates Authors: Mutwiri, Robert M. Abstract: In this thesis, I investigate the application of various statistical methods towards analysing GPS tracking data collected using GPS collars placed on large mammals in Kruger National Park, South Africa. Animal movement tracking is a rapidly advancing area of ecological research and large amount of data is being collected, with short sampling intervals between successive locations. A statistical challenge is to determine appropriate methods that capture most properties of the data is lacking despite the obvious importance of such information to understanding animal movement. The aim of this study was to investigate appropriate alternative models and compare them with the existing approaches in the literature for analysing GPS tracking data and establish appropriate statistical approaches for interpreting large scale mega-herbivore movements patterns. The focus was on which methods are the most appropriate for the linear metrics (step length and movement speed) and circular metrics (turn angles) for these animals and the comparison of the movement patterns across herds with covariate. A four parameter family of stable distributions was found to better describe the animal movement linear metrics as it captured both skewness and heavy tail properties of the data. The stable model performed favourably better than normal, Student’s t and skewed Student’s t models in an ARMA-GARCH modelling set-up. The flexibility of the stable distribution was further demonstrated in a regression model and compared with the heavy tailed t regression model. We also explore the application circular linear regression model in analysing animal turn angle data with covariate. A regression model assuming Von Mises distributed turn angles was shown to fit the data well and further areas of model development highlighted. A couple of methods for testing the uniformity hypothesis of turn angles are presented. Finally, we model the linear metrics assuming the error terms are stable distributed and the turn angles assuming the error terms are von Mises distributed are recommended for analysing animal movement data with covariate. Description: Doctor of Philosophy in Statistics

2021-10-07T00:00:00Z Mbala, Simon https://repository.seku.ac.ke/handle/123456789/6269 2023-11-30T09:55:45Z 2021-06-18T00:00:00Z

Title: Symmetric variant truth detection model in sample surveys - a randomized response approach Authors: Mbala, Simon Abstract: In every survey truthfulness is required so as to come up with validdata for decision making. Most surveys use direct questioning to col-ect data. This method does not yield reliable information when the opic under investigation is sensitive in nature. In such surveys, directquestions are not useful as the respondents will either refuse to answerthe survey questions or, even if they do, may give false answers for fearof being known to have the sensitive characteristics. The less privacy a design offers, the more likely respondents cheat by disobeying the instructions thus giving very unreliable information which can lead to wrong decision making. In this study we have formulated a technique which we have called symmetric variant truth detection model. We have also formulated symmetric stratified truth detection model for analyzing stratified data. In this technique, we have used two ran-domization devices which do not require the respondents to disclosetheir identity thus increasing their privacy leading to more honest re-sponses. After developing the models, they were validated by the useof data simulation as well as real life application. It was establishedthat the symmetric truth detection models were more efficient com-pared to the asymmetric truth detection models. This study thereforerecommended that researchers on sensitive information to use symmet-ric truth detection models as opposed to asymmetric truth detection models. Description: Doctor of Philosophy in Mathematical Statistics, 2020

2021-06-18T00:00:00Z