Browsing by Author "Ndlovu, Siqabukile"

Now showing 1 - 3 of 3
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    Beacon Frame Manipulation to Mitigate Rogue Access Points: Case of Android Smartphone Rogue Access Points
    (Compusoft, 2014-02) Nyathi, Thambo; Ndlovu, Siqabukile
    The use of wireless devices to access corporate network resources is now part of the norm within corporate environments. When wireless users need to connect to a network they hardly question the source of their connectivity. Mobile phones, particularly smartphones allow users to access network resources. These harmless looking wireless devices can be a source of major threats if configured to be so. The Internet is awash with mobile apps capable of performing packet sniffing. These applications, coupled with the capability of the smartphone to be configured as an access point, can present a Smartphone Rogue Access Point. Access Points advertise their availability using what is called a beacon frame. This research paper proposes a solution which restructures this beacon frame to include an Authentic Access Point Value which can be used to defend against Rogue Access Points.
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    Optimisation of the Linear Probability Model for Credit Risk Management
    (2014-11) Nyathi, K.T.; Ndlovu, Siqabukile; Moyo, S.; Nyathi, Thambo
    One of the aims of the banking business is to provide loans to applicants. Credit risk management plays an important role in banks, as loans generally account for half to three quarters of the total value of bank assets. Credit scoring is a systematic method for evaluating credit risk and assists decision makers determine whether or not to provide loans to applicants. Scoring models are systematic means of evaluating the creditworthiness of a loan applicant. However, existing scoring models cause some loan applications to be rejected unnecessarily as their credit rates are lowered to rejection levels due to lack of information such as previous loan payment data. This might be refusal of good credit, which potentially can cause the loss of future profit margins. This study aims at optimising one such credit scoring model to ensure that it uses only the critical scoring criteria to determine a credit score. The optimised model will not only reduce the proportion of unsafe borrowers, but also identify profitable borrowers.
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    Using Fuzzy ARTMAP for Symmetric Key Generation
    (American Institute of Science., 2015) Mulopa, John; Ndlovu, Siqabukile; Mzelikahle, Kernan; Nyathi, Thambo
    Neural cryptography deals with the problem of key exchange between two communicating neural networks using the mutual learning concept. It is the first algorithm for key generation over public channels which are not based on the number theory. The two networks exchange their outputs and the key between the two communicating parties is eventually presented in the final learned weights, when the two networks are synchronised. The security of neural synchronisation is put at risk if an attacker is capable of synchronising with any of the two parties during the training processes. However, the security of a cryptosystem is robust if the algorithm is strong and the keys are long, unpredictable, and random This research proposes use of two distant remote Adaptive Resonance Theory MAP (ARTMAP) architectures that are trained to learn from a unique data set and finally synchronise to same weights.