TeleWeaver: an innovative telecommunication platform for marginalized communities in Africa
- Authors: Dalvit, Lorenzo , Gumbo, Sibukelo , Ntshinga, Lindikaya , Terzoli, Alfredo , Hansen, Susan
- Date: 2013
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/431317 , vital:72763 , https://www.academic-bookshop.com/ourshop/prod_2659103-ECEG-2013-13th-European-Conference-on-eGovernment-Como-Italy-PRINT-version.html
- Description: Information and Communication Technologies for Development (ICT4D) is becoming an increasingly important and multi‐faceted area of research and software development. Particularly through provision via mobile devices, e‐services can potentially reach and improve the lives of millions of people living in marginalised areas. The efforts of many governments in sub‐Saharan Africa are frustrated by poor tele-communication infrastructure, lack of skills and unsustainable models of intervention. In this paper we describe the holistic solution offered by the TeleWeaver platform. The novel approach to the development of the software, the strong sense of social responsibility of the developers and the collaborative spirit that shaped the ecosystem of which Tele-Weaver is part, warrants the adoption of an innovative approach to its marketing and implementation. On the one hand, the project needs to provide returns on investment and generate profit for the key stake-holders (ie government at the local and national level, academia, indus-try and socio‐-entrepreneurs in the target community). On the other, it must benefit all members of the marginalised communities it is intended to serve as well as the global community of software developers. Tele-Weaver was developed in close collaboration with the community of Dwesa, a rural area on the Wild Cost of the Transkei regions in eastern South Africa.
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- Date Issued: 2013
An Analysis and Implementation of Methods for High Speed Lexical Classification of Malicious URLs
- Authors: Egan, Shaun P , Irwin, Barry V W
- Date: 2012
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/429757 , vital:72637 , https://digifors.cs.up.ac.za/issa/2012/Proceedings/Research/58_ResearchInProgress.pdf
- Description: Several authors have put forward methods of using Artificial Neural Networks (ANN) to classify URLs as malicious or benign by using lexical features of those URLs. These methods have been compared to other methods of classification, such as blacklisting and spam filtering, and have been found to be as accurate. Early attempts proved to be as highly accurate. Fully featured classifications use lexical features as well as lookups to classify URLs and include (but are not limited to) blacklists, spam filters and reputation services. These classifiers are based on the Online Perceptron Model, using a single neuron as a linear combiner and used lexical features that rely on the presence (or lack thereof) of words belonging to a bag-of-words. Several obfuscation resistant features are also used to increase the positive classification rate of these perceptrons. Examples of these include URL length, number of directory traversals and length of arguments passed to the file within the URL. In this paper we describe how we implement the online perceptron model and methods that we used to try to increase the accuracy of this model through the use of hidden layers and training cost validation. We discuss our results in relation to those of other papers, as well as other analysis performed on the training data and the neural networks themselves to best understand why they are so effective. Also described will be the proposed model for developing these Neural Networks, how to implement them in the real world through the use of browser extensions, proxy plugins and spam filters for mail servers, and our current implementation. Finally, work that is still in progress will be described. This work includes other methods of increasing accuracy through the use of modern training techniques and testing in a real world environment.
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- Date Issued: 2012
Building a Graphical Fuzzing Framework
- Authors: Zeisberger, Sascha , Irwin, Barry V W
- Date: 2012
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/429772 , vital:72638 , https://digifors.cs.up.ac.za/issa/2012/Proceedings/Research/59_ResearchInProgress.pdf
- Description: Fuzz testing is a robustness testing technique that sends malformed data to an application’s input. This is to test an application’s behaviour when presented with input beyond its specification. The main difference between traditional testing techniques and fuzz testing is that in most traditional techniques an application is tested according to a specification and rated on how well the application conforms to that specification. Fuzz testing tests beyond the scope of a specification by intelligently generating values that may be interpreted by an application in an unintended manner. The use of fuzz testing has been more prevalent in academic and security communities despite showing success in production environments. To measure the effectiveness of fuzz testing, an experiment was conducted where several publicly available applications were fuzzed. In some instances, fuzz testing was able to force an application into an invalid state and it was concluded that fuzz testing is a relevant testing technique that could assist in developing more robust applications. This success prompted a further investigation into fuzz testing in order to compile a list of requirements that makes an effective fuzzer. The aforementioned investigation assisted in the design of a fuzz testing framework, the goal of which is to make the process more accessible to users outside of an academic and security environment. Design methodologies and justifications of said framework are discussed, focusing on the graphical user interface components as this aspect of the framework is used to increase the usability of the framework.
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- Date Issued: 2012