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An Automated System for Detecting and Preventing Phishing Attempts on Steam Accounts

- Sonne, Kabir, Chindipha, Stones D

  • Authors: Sonne, Kabir , Chindipha, Stones D
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/473729 , vital:77676 , xlink:href="https://ieeexplore.ieee.org/abstract/document/10389578"
  • Description: In recent years Steam has become a giant in the gaming industry. The Valve-owned digital distribution platform held an estimated 75% of market share in 2013, and continues to grow. However, with such a large user base comes the ever-increasing threat of security breaches in both the Steam database and individual Steam user accounts. While Steam does make use of a mobile authentication app, users are still susceptible to malware and/or phishing attempts that can cause users to lose access to their accounts through manipulation or gaining access to recovery email accounts. This project aims to investigate how the authentication process can be improved or if a solution can be created to help prevent the worst-case scenario when users become victims of phishing attacks.
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  • Date Issued: 2023

Count me in: Leopard population density in an area of mixed land‐use, Eastern Cape, South Africa

- Bouderka, Safia, Perry, Travis W, Parker, Daniel M, Beukes, Maya, Mgqatsa, Nokubonga

  • Authors: Bouderka, Safia , Perry, Travis W , Parker, Daniel M , Beukes, Maya , Mgqatsa, Nokubonga
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/462591 , vital:76317 , xlink:href="https://doi.org/10.1111/aje.13078"
  • Description: Although the leopard (Panthera pardus) has the widest range of any felid in the world is designated as a vulnerable species, mainly because of human-induced conflict (Jacobson et al., 2016). Our study focuses on a population of leopards on privately owned, mixed-use farmland (Baviaanskloof Hartland–BH hereafter) which is adjacent to the Baviaanskloof Mega Reserve (BMR) in the Baviaanskloof UNESCO World Heritage Site of the Eastern Cape, South Africa. Given the unique make-up of the region, with sometimes conflicting management objectives, the status of leopards in the broader Baviaanskloof is of particular interest to a range of stakeholders. However, despite the need for management decisions to be based on reliable and regular population monitoring efforts (Elliot et al., 2020), the last formal assessment of the leopard population in the Baviaanskloof was performed in 2011/2012 but published 9 years later (Devens et al., 2018). The only other assessment of the status of leopards in the region was an unpublished Master's project (McManus, 2009). Here, we use photographic captures of leopards and a Spatially Explicit Capture Recapture (SECR) analytical framework in the mixed-use BH region of the Baviaanskloof to generate an up-to-date leopard population density estimate that can inform conservation management of the species in this important World Heritage Site.
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  • Date Issued: 2023

Cryptojacking Detection in Cloud Infrastructure Using Network Traffic

- Kwedza, Philip, Chindipha, Stones D

  • Authors: Kwedza, Philip , Chindipha, Stones D
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/473762 , vital:77679 , xlink:href="https://ieeexplore.ieee.org/abstract/document/10389593"
  • Description: Cryptomining is a way to obtain cryptocurrency, by performing computationally complex puzzles in exchange for a reward. To perform this requires expensive specialised hardware to become profitable but most times, this is not viable. Cryptojacking is a cybercrime in which an attacker uses devices to mine cryptocurrency without permission. This attack can be extended to use the resources of networks and cloud infrastructure. This research aimed to develop a model that could detect cryptojacking automatically in a cloud environment, utilising network traffic. The models in this paper solved this by developing a machine learning model that could analyse cryptojacking in a dataset of network traffic from an attacked cloud server.
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  • Date Issued: 2023

Plant Disease Detection using Vision Transformers on Multispectral Natural Environment Images

- De Silva, Malitha, Brown, Dane L

  • Authors: De Silva, Malitha , Brown, Dane L
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/463456 , vital:76410 , xlink:href="https://ieeexplore.ieee.org/abstract/document/10220517"
  • Description: Enhancing agricultural practices has become essential in mitigating global hunger. Over the years, significant technological advancements have been introduced to improve the quality and quantity of harvests by effectively managing weeds, pests, and diseases. Many studies have focused on identifying plant diseases, as this information aids in making informed decisions about applying fungicides and fertilizers. Advanced systems often employ a combination of image processing and deep learning techniques to identify diseases based on visible symptoms. However, these systems typically rely on pre-existing datasets or images captured in controlled environments. This study showcases the efficacy of utilizing multispectral images captured in visible and Near Infrared (NIR) ranges for identifying plant diseases in real-world environmental conditions. The collected datasets were classified using popular Vision Transformer (ViT) models, including ViT- S16, ViT-BI6, ViT-LI6 and ViT-B32. The results showed impressive training and test accuracies for all the data collected using diverse Kolari vision lenses with 93.71 % and 90.02 %, respectively. This work highlights the potential of utilizing advanced imaging techniques for accurate and reliable plant disease identification in practical field conditions.
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  • Date Issued: 2023

Spatiotemporal Convolutions and Video Vision Transformers for Signer-Independent Sign Language Recognition

- Marais, Marc, Brown, Dane L, Connan, James, Boby, Alden

  • Authors: Marais, Marc , Brown, Dane L , Connan, James , Boby, Alden
  • Date: 2023
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/463478 , vital:76412 , xlink:href="https://ieeexplore.ieee.org/abstract/document/10220534"
  • Description: Sign language is a vital tool of communication for individuals who are deaf or hard of hearing. Sign language recognition (SLR) technology can assist in bridging the communication gap between deaf and hearing individuals. However, existing SLR systems are typically signer-dependent, requiring training data from the specific signer for accurate recognition. This presents a significant challenge for practical use, as collecting data from every possible signer is not feasible. This research focuses on developing a signer-independent isolated SLR system to address this challenge. The system implements two model variants on the signer-independent datasets: an R(2+ I)D spatiotemporal convolutional block and a Video Vision transformer. These models learn to extract features from raw sign language videos from the LSA64 dataset and classify signs without needing handcrafted features, explicit segmentation or pose estimation. Overall, the R(2+1)D model architecture significantly outperformed the ViViT architecture for signer-independent SLR on the LSA64 dataset. The R(2+1)D model achieved a near-perfect accuracy of 99.53% on the unseen test set, with the ViViT model yielding an accuracy of 72.19 %. Proving that spatiotemporal convolutions are effective at signer-independent SLR.
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  • Date Issued: 2023

An evaluation of hand-based algorithms for sign language recognition

- Marais, Marc, Brown, Dane L, Connan, James, Boby, Alden

  • Authors: Marais, Marc , Brown, Dane L , Connan, James , Boby, Alden
  • Date: 2022
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/465124 , vital:76575 , xlink:href="https://ieeexplore.ieee.org/abstract/document/9856310"
  • Description: Sign language recognition is an evolving research field in computer vision, assisting communication between hearing disabled people. Hand gestures contain the majority of the information when signing. Focusing on feature extraction methods to obtain the information stored in hand data in sign language recognition may improve classification accuracy. Pose estimation is a popular method for extracting body and hand landmarks. We implement and compare different feature extraction and segmentation algorithms, focusing on the hands only on the LSA64 dataset. To extract hand landmark coordinates, MediaPipe Holistic is implemented on the sign images. Classification is performed using poplar CNN architectures, namely ResNet and a Pruned VGG network. A separate 1D-CNN is utilised to classify hand landmark coordinates extracted using MediaPipe. The best performance was achieved on the unprocessed raw images using a Pruned VGG network with an accuracy of 95.50%. However, the more computationally efficient model using the hand landmark data and 1D-CNN for classification achieved an accuracy of 94.91%.
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  • Date Issued: 2022

Investigating the Effects of Image Correction Through Affine Transformations on Licence Plate Recognition

- Boby, Alden, Brown, Dane L, Connan, James, Marais, Marc

  • Authors: Boby, Alden , Brown, Dane L , Connan, James , Marais, Marc
  • Date: 2022
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/465190 , vital:76581 , xlink:href="https://ieeexplore.ieee.org/abstract/document/9856380"
  • Description: Licence plate recognition has many real-world applications, which fall under security and surveillance. Deep learning for licence plate recognition has been adopted to improve existing image-based processing techniques in recent years. Object detectors are a popular choice for approaching this task. All object detectors are some form of a convolutional neural network. The You Only Look Once framework and Region-Based Convolutional Neural Networks are popular models within this field. A novel architecture called the Warped Planar Object Detector is a recent development by Zou et al. that takes inspiration from YOLO and Spatial Network Transformers. This paper aims to compare the performance of the Warped Planar Object Detector and YOLO on licence plate recognition by training both models with the same data and then directing their output to an Enhanced Super-Resolution Generative Adversarial Network to upscale the output image, then lastly using an Optical Character Recognition engine to classify characters detected from the images.
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  • Date Issued: 2022

Situating the diversity of Southern African environmental education scholarship within a global conversation at a critical juncture on Earth

- Olvitt, Lausanne L

  • Authors: Olvitt, Lausanne L
  • Date: 2022
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/389869 , vital:68491 , xlink:href="https://www.ajol.info/index.php/sajee/article/view/247386"
  • Description: ¬The collection of papers in Volume 38 in many ways mirrors the diversity of research methodologies and teaching approaches in the contemporary eld of Environmental and Sustainability Education. ¬ e seven papers remind us that, whilst environmental educators and researchers are largely in agreement over the nature and causes of the social-ecological problems that we face in sub-Saharan Africa, there is less certainty around what types of educational approaches and pedagogies are adequate to help resolve them. ¬ e papers in this volume either o er pedagogical innovations that may strengthen teaching and learning for sustainable futures, or they provide insights into the social, cultural and economic contexts in which such teaching and learning occurs.
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  • Date Issued: 2022

Symmetry effect of cobalt phthalocyanines on the aluminium corrosion inhibition in hydrochloric acid

- Nnaji, Nnaemeka, Sen, Pinar, Nyokong, Tebello

  • Authors: Nnaji, Nnaemeka , Sen, Pinar , Nyokong, Tebello
  • Date: 2022
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/231323 , vital:49877 , xlink:href="https://doi.org/10.1016/j.matlet.2021.130892"
  • Description: The aluminium corrosion retardation potentials of phthalocyanine-based dyes, cobalt (II) 2,9,16-tris(4-(tert-butyl)phenoxy)-23-(pyridin-4-yloxy)phthalocyanine (D1) and cobalt (II) 2,9,16,24-tetrakis(4-(tert-butyl)phenoxy)phthalocyanine (D2) in 1 M hydrochloric acid were evaluated. Results from potentiodynamic polarization measurements show that inhibition efficiency increased with inhibitor concentration at 28 °C with values of 91.9 % and 87.0 % values respectively for D1 and D2 at 10 μM.
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  • Date Issued: 2022

Traumatic Imagination in Traditional Stories of Gender-Based Violence

- Ahmad, Ayesha, Ahmad, Lida, Andrabi, Shazana, Ben Salem, Lobna, Hughes, Peter, Mannell, Jenevieve, Paphitis, Sharli A, Senyurek, Gamze

  • Authors: Ahmad, Ayesha , Ahmad, Lida , Andrabi, Shazana , Ben Salem, Lobna , Hughes, Peter , Mannell, Jenevieve , Paphitis, Sharli A , Senyurek, Gamze
  • Date: 2022
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/426548 , vital:72362 , xlink:href="https://journalofethics.ama-assn.org/article/traumatic-imagination-traditional-stories-gender-based-violence/2022-06"
  • Description: Traumatic imagination includes creative processes in which traumatic memories are transformed into narratives of suffering. This article emphasizes the importance of storytelling in victims’ mental health and offers a literary perspective on how some women’s experiences of suffering can be expressed in the telling of traditional stories, which confer some protection from stigma to individual women in Turkish and Afghan societies.
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  • Date Issued: 2022

“It’s just like a waiting room”: The lived experiences of psychology students seeking professional training programme admission in South Africa

- Duiker, Adeline, Booysen, Duane D

  • Authors: Duiker, Adeline , Booysen, Duane D
  • Date: 2022
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/454068 , vital:75307 , xlink:href="https://doi.org/10.1080/14330237.2022.2075620"
  • Description: We aimed to explore the lived experiences of South African psychology students of professional training opportunities and career prospects. Informants were eight psychology Honours students attending a South African public university. Interpretive phenomenological analysis of the data yielded four themes recurrent in most participant’s experiences: (i) personal capacity development; (ii) feeling stuck with nothing; (iii) sense of disillusionment and uncertainty; and (iv) low career prospects. The students considered psychology studies beneficial to their personal growth although they were uncertain about their futures, accessing professional training programs, and employment in the field. The uncertainty to access professional training contributes to a sense of unemployability in the South African mental health field.
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  • Date Issued: 2022

A heavy-atom-free π-extended N-confused porphyrin as a photosensitizer for photodynamic therapy

- Babu, Balaji, Mack, John, Nyokong, Tebello

  • Authors: Babu, Balaji , Mack, John , Nyokong, Tebello
  • Date: 2021
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/185909 , vital:44447 , xlink:href="https://doi.org/10.1039/d1nj00112d"
  • Description: The synthesis and characterization of a novel 1,3-diethyl-2-thiobarbituric-acid-substituted N-confused porphyrin (NCP-TB) is reported, along with a study of its photodynamic activity against MCF-7 cells using 530 (110 mW cm−2) and 660 nm (280 mW cm−2) Thorlabs light-emitting diodes for 30 min. The singlet oxygen quantum yield for NCP-TB is 0.38 compared to 0.23 for the parent unsubstituted N-confused porphyrin (NCP) due to the presence of a sulfur atom. NCP-TB exhibits enhanced PDT activity compared to NCP at both wavelengths. A significantly lower IC50 value of 5.2 μM was obtained at 530 nm (14.7 μM at 660 nm) despite a smaller light dose, due to a large red shift of the intense B band into the green region of the spectrum. 2′,7′-Dichlorofluorescein diacetate (DCFDA) assays demonstrate that there is intracellular generation of reactive oxygen species upon exposure to light.
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  • Date Issued: 2021

Adaptive machine learning based network intrusion detection

- Chindove, Hatitye E, Brown, Dane L

  • Authors: Chindove, Hatitye E , Brown, Dane L
  • Date: 2021
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/464052 , vital:76471 , xlink:href="https://doi.org/10.1145/3487923.3487938"
  • Description: Network intrusion detection system (NIDS) adoption is essential for mitigating computer network attacks in various scenarios. However, the increasing complexity of computer networks and attacks make it challenging to classify network traffic. Machine learning (ML) techniques in a NIDS can be affected by different scenarios, and thus the recency, size and applicability of datasets are vital factors to consider when selecting and tuning a machine learning classifier. The proposed approach evaluates relatively new datasets constructed such that they depict real-world scenarios. It includes analyses of dataset balancing and sampling, feature engineering and systematic ML-based NIDS model tuning focused on the adaptive improvement of intrusion detection. A comparison between machine learning classifiers forms part of the evaluation process. Results on the proposed approach model effectiveness for NIDS are discussed. Recurrent neural networks and random forests models consistently achieved high f1-score results with macro f1-scores of 0.73 and 0.87 for the CICIDS 2017 dataset; and 0.73 and 0.72 against the CICIDS 2018 dataset, respectively.
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  • Date Issued: 2021

Early dehydration detection using infrared imaging

- Poole, Louise C, Brown, Dane L, Connan, James

  • Authors: Poole, Louise C , Brown, Dane L , Connan, James
  • Date: 2021
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/465656 , vital:76629 , xlink:href="https://www.researchgate.net/profile/Louise-Poole-3/publication/357578445_Early_Dehydration_Detection_Using_Infrared_Imaging/links/61d5664eb8305f7c4b231d50/Early-Dehydration-Detection-Using-Infrared-Imaging.pdf"
  • Description: Crop loss and failure have devastating impacts on a country’s economy and food security. Developing effective and inexpensive systems to minimize crop loss has become essential. Recently, multispectral imaging—in particular visible and infrared imaging—have become popular for analyzing plants and show potential for early identification of plant stress. We created a directly comparable visible and infrared image dataset for dehydration in spinach leaves. We created and compared various models trained on both datasets and concluded that the models trained on the infrared dataset outperformed all of those trained on the visible dataset. In particular, the models trained to identify early signs of dehydration yielded 45% difference in accuracy, with the infrared model obtaining 70% accuracy and the visible model obtaining 25% accuracy. Infrared imaging thus shows promising potential for application in early plant stress and disease identification.
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  • Date Issued: 2021

Exploring the Integration of Blockchain Technology and IoT in a Smart University Application Architecture

- Mjoli, Siphamandla, Dlodlo, Nomusa

  • Authors: Mjoli, Siphamandla , Dlodlo, Nomusa
  • Date: 2021
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/474342 , vital:77703 , xlink:href="https://dl.acm.org/doi/pdf/10.1145/3459104.3459153"
  • Description: The ecosystem inherent within currently deployed Internet of Things (IoT) systems is that of low-powered devices equipped with sensors that consume data. The data these devices collect is then stored in use-case specific applications, which are connected through application layer gateways that allow these devices to connect to third party cloud storage platforms for further processing. This stratified architecture has created data silos that introduce complexities such as limited user control and lack of solicitation regarding the usage of user data. The constant proliferation of IoT devices deployed in smart cities which include smart university campus (SUC) has resulted in the need for the development of IoT architecture models which are data-centric. In this paper a blockchain- based architecture model, and specifically, the distributed ledger inherent within the Ethereum blockchain, combined with the Proof Of Authority (POA) consensus mechanism, are proposed as a potential solution to developing a proof of concept architecture model that is data-centric. The proposed architecture model will be tested against with application specific use-cases in a simulated environment within the context of a SUC which is subsumed by a smart city.
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  • Date Issued: 2021

Mobile attendance based on face detection and recognition using OpenVINO

- Brown, Dane L

  • Authors: Brown, Dane L
  • Date: 2021
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/465201 , vital:76582 , xlink:href="https://ieeexplore.ieee.org/abstract/document/9395836"
  • Description: The OpenVINO toolkit enables versatile computer vision with an Intel® Movidius ™ Neural Compute Stick 2 connected to a Raspberry Pi. This small portable platform provides new opportunities for innovative solutions in computer vision applications and beyond. This paper investigates its feasibility for mobile attendance systems for settings such as classrooms or other scenarios that require headcount or roll call. Related studies of face-based systems are explored, while the advantages of the proposed system are highlighted. Although there are some positioning constraints, the proof-of-concept system processes an approximate average of five faces per second. That means it can take attendance in a lecture room of 90 students in about 18 seconds. A recognition accuracy of 98.1% with an f-score of 96.9% was yielded on a private classroom dataset captured with a modest RPi camera. These promising results were achieved using a tiny ResNet-18 architecture, producing significantly better results than MobileNet. Furthermore, it outperformed the recognition accuracy of other ‘lightweight’ methods used in the literature that do not run off embedded devices on publicly available datasets.
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  • Date Issued: 2021

Naked Eye and Colorimetric Detection of Cyanide with a 1, 3‐Diethyl‐2‐thiobarbituric Acid Substituted Ferrocene Chemosensor

- Babu, Balaji, Mack, John, Nyokong, Tebello

  • Authors: Babu, Balaji , Mack, John , Nyokong, Tebello
  • Date: 2021
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/190567 , vital:45006 , xlink:href="https://doi.org/10.1002/slct.202100163"
  • Description: A 1,3-diethyl-2-thiobarbituric-acid-substituted ferrocene (FET) has been evaluated for its cyanide sensing ability by UV-visible absorption spectroscopy and other characterization methods. FET provides a ratiometric colorimetric chemosensor for the CN− anion detection in 1 : 1 DMSO/H2O (v/v) solution. The addition of CN− results in an immediate color change from dark blue to pale orange that is visible to the naked eye. Mechanism studies and molecular modelling with TD-DFT calculations demonstrate that nucleophilic addition of CN− to an electrophilic sp2-hybridized carbon atom blocks charge transfer from the ferrocene ring complex to the thiobarbituric acid moiety. The FET sensor exhibits excellent selectivity for CN− and a limit of detection of 0.2 μM.
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  • Date Issued: 2021

Fucoidan from Ecklonia maxima is a powerful inhibitor of the diabetes-related enzyme, Éø-glucosidase

- Daub, Chantal D, Mabate, Blessing, Malgas, Samkelo, Pletschke, Brett I

  • Authors: Daub, Chantal D , Mabate, Blessing , Malgas, Samkelo , Pletschke, Brett I
  • Date: 2020
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/425982 , vital:72304 , xlink:href="https://doi.org/10.1016/j.ijbiomac.2020.02.161"
  • Description: Ecklonia maxima, an endemic South African seaweed, is a potential source of beneficial bioactive compounds. Among these compounds, fucoidan, a sulphated polysaccharide has a wide range of bioactivities including anti-diabetic activity. In this study, fucoidan was extracted from E. maxima by the hot water extraction method and then characterised by colorimetric assays for sugar composition. The extraction from E. maxima yielded 6.89% fucoidan which was found to contain 4.45 ± 0.25% L-fucose and 6.01 ± 0.53% sulphate. The water extracted E. maxima fucoidan had a low molecular weight of approximately 10 kDa. Structural studies (FT-IR, NMR and XRD) confirmed the structure and integrity of the fucoidan to be similar to previously studied fucoidans in literature. Finally, the activities of starch digestive enzymes; α-amylase and α-glucosidase, were investigated in the presence of the E. maxima fucoidan extract. Fucoidan from E. maxima was observed to be a potent mixed-type inhibitor of α-glucosidase with an IC50 range of 0.27–0.31 mg.ml-1, which was significantly lower than the commercial anti-diabetic standard, acarbose. Our present study demonstrated that fucoidan from E. maxima is a more powerful inhibitor compared to some standard anti-diabetic compounds and thus shows great potential for managing type 2 diabetes.
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  • Date Issued: 2020

Genetics of schizophrenia in the South African Xhosa

- Gulsuner, S, Stein, D J, Susser, E S, Sibeko, G, Pretorius, A, Walsh, T, Majara, L, Mndini, M M, Mqulwana, S G, Ntola, O A, Casadei, S, Zingela, Zukiswa, Nagdee, M, Ramesar, R S, King, M-C, McClellan, J M, Ngqengelele, L L, Korchina, V, van der Merwe, C, Malan, M, Fader, K M, Feng, M, Willoughby, E, Munzi, D, Andrews, H F, Gur, R C, Gibbs, R A

An Evaluation of Text Mining Techniques in Sampling of Network Ports from IBR Traffic

- Chindipha, Stones D, Irwin, Barry V W, Herbert, Alan

  • Authors: Chindipha, Stones D , Irwin, Barry V W , Herbert, Alan
  • Date: 2019
  • Subjects: To be catalogued
  • Language: English
  • Type: text , article
  • Identifier: http://hdl.handle.net/10962/473740 , vital:77677 , xlink:href="https://www.researchgate.net/profile/Stones-Chindi-pha/publication/335910179_An_Evaluation_of_Text_Mining_Techniques_in_Sampling_of_Network_Ports_from_IBR_Traffic/links/5d833084458515cbd1985a38/An-Evaluation-of-Text-Mining-Techniques-in-Sampling-of-Network-Ports-from-IBR-Traffic.pdf"
  • Description: Information retrieval (IR) has had techniques that have been used to gauge the extent to which certain keywords can be retrieved from a document. These techniques have been used to measure similarities in duplicated images, native language identification, optimize algorithms, among others. With this notion, this study proposes the use of four of the Information Retrieval Techniques (IRT/IR) to gauge the implications of sampling a/24 IPv4 ports into smaller subnet equivalents. Using IR, this paper shows how the ports found in a/24 IPv4 net-block relate to those found in the smaller subnet equivalents. Using Internet Background Radiation (IBR) data that was collected from Rhodes University, the study found compelling evidence of the viability of using such techniques in sampling datasets. Essentially, being able to identify the variation that comes with sampling the baseline dataset. It shows how the various samples are similar to the baseline dataset. The correlation observed in the scores proves how viable these techniques are to quantifying variations in the sampling of IBR data. In this way, one can identify which subnet equivalent best represents the unique ports found in the baseline dataset (IPv4 net-block dataset).
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  • Date Issued: 2019
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