Novia Admodisastro

Current state of research on cross-site scripting (XSS) – A systematic literature review

Context: Cross-site scripting (XSS) is a security vulnerability that affects web applications. It occurs due to improper or lack of sanitization of user inputs. The security vulnerability caused many problems for users and server applications. Objective: To conduct a systematic literature review on the studies done on XSS vulnerabilities and attacks. Method: We followed the standard guidelines for systematic literature review as documented by Barbara Kitchenham and reviewed a total of 115 studies related to cross-site scripting from various journals and conference proceedings. Results: Research on XSS is still very active with publications across many conference proceedings and journals. Attack prevention and vulnerability detection are the areas focused on by most of the studies. Dynamic analysis techniques form the majority among the solutions proposed by the various studies. The type of XSS addressed the most is reflected XSS. Conclusion: XSS still remains a big problem for web applications, despite the bulk of solutions provided so far. There is no single solution that can effectively mitigate XSS attacks. More research is needed in the area of vulnerability removal from the source code of the applications before deployment.

Computer-based learning model to improve learning of the malay language amongst dyslexic primary school students

Computer-based learning model acts as an important supplement to traditional teaching method that commonly using pen, paper or any material, which apply multi-senses application for students with dyslexia. The need to improve learning style for students with dyslexia raised by many researchers, teachers and also parents. Students with dyslexia have poor fluency in reading, writing, spelling, short-term memory and also other related disorders. Additionally, they often suffer emotions like frustration and low self-esteem due to lack of achievement, which in the end develop behaviour difficulties. In this research, we proposed a computer-based learning model to address dyslexia language-based processing difficulties that considers both students cognitive and emotion. The proposed model intended for students with dyslexia in primary school to learn the Malay language using the machine learning (ML) approach to provide an adaptive learning environment. This allows students with dyslexia to learn in ways that are tailored to suit a specific individual with minimal teacher intervention.

Prevention of attack on Islamic websites by fixing SQL injection vulnerabilities using co-evolutionary search approach

In recent times, there is an alarming increase in web application attacks, with significant cases, specifically, targeting Islamic websites. Since 2004, SQL Injection Vulnerabilities (SQLIVs) remains the most serious software security loopholes via which web applications are exploited. Fixing SQLIVs prior to deployment would provide very effective means of protection against such exploits. Ideally, SQLIVs fixing includes four main phases: SQLIVs detection, fix generation, fix application, and fix effectiveness verification. Most existing research works address different phases separately. There is no single research that addresses the four phases in a seamless integrated automation. This paper presents instances of attack on Islamic websites, and then propose framework for seamless integrated and automated SQLIVs fixing for web application, as part of an ongoing research work. The framework employs Evolutionary Programming to establish competitive co-evolution of web applications and test sets, in which fitness of evolved web applications is evaluated based on their ability to defend test attacks and pass legitimate input tests.

Towards Designing Tangible Interaction for Children with Dyslexia in Learning the Malay Language

In this paper, we provide a study of tangible interaction (TI) based on theories and related works for dyslexic children. The study is an attempt to investigate TI for dyslexic children in learning Malay language in Malaysia primary schools. TI has tremendous contribution in supporting dyslexic children to enhance their way of learning process. However, TI that were developed currently have different capabilities and purposes. For example, current works currently only developed for other languages like English, Mandarin and Dutch. The TI model for English or other languages may not be suitable to be adopted directly for the Malay language due to differences of letter sound, morphology and etc. There were nine related works reviewed in this study. Based on these previous related works and learning theories we designed a conceptual TI model for dyslexic children in learning the Malay language.

Dyslexia Adaptive Learning Model: Student Engagement Prediction Using Machine Learning Approach

Education barriers are synonym with people with dyslexia life experience. People with dyslexia encounter barriers such as in academic related areas, mistreated with negative reaction on their behaviour and limitation to acquire a suitable support to overcome the barriers. Therefore, this work focus on giving the support to help students with dyslexia deal with their difficulty through adaptively sense their behaviour for engagement perspective. For that reason, we apply machine learning approach that utilises Bag of Features (BOF) image classification to predict student engagement towards the learning content. The engagement prediction was relatively using frontal face of the 30 students. We used Speeded-Up Robust Feature (SURF) key point descriptor and clustered using k-Means method for the codebook in this BOF model. Then, we classify the model using 3 types of classifier which are Support Vector Machine (SVM), Naive Bayes and K-Nearest Neighbour (k-NN) to find the best classification result. Through these methods, we managed to get high accuracy with 97–97.8%.

Engagement Prediction in the Adaptive Learning Model for Students with Dyslexia

Student engagement is one of the most important elements in a likelihood of school failure or dropout. Therefore, it is vital to measure the student engagement as quickly as possible and as often as possible to prevent it occurred in a prolonged situation. There a few ways to assess the engagement that includes self-reporting, teachers rating, interviews and observation. However, these methods are not only takings time but also need a lot of hard work, cost and difficult to conduct for a very short time. Therefore, we a proposing an alternative to predict student engagement through frontal face detection. We apply machine learning approach that utilizes Speed-Up Robust Features (SURF) descriptor to detect key interest point of the images and cluster using different codebook sizes. For classification model, we used Support Vector Machine (SVM) with two different kernels and Naïve Bayes. We managed to get more than 88% of the accuracy results. The model is an important part of our proposed adaptive learning model for dyslexic students.

Designing an Interactive Learning to Enrich Children’s Experience in Museum Visit

It has long been known that museum education has the ability to motivate and excite visitors whilst providing them with new insights and experiences. Nevertheless, activities that learning goal, for example, visiting a museum is found to disinterest, not appealing and give insignificant impact to children as compared to visiting the amusement park, playground, or even zoo. Thus, museums are increasingly being equipped with digital and mobile technologies. The main goal of using technologies is to improve the museum-going experience for visitors. In this research, we present a study of a museum interactive quest based on the proposed interaction design model. The study involves children in the age of 9 to 11 to visit a museum located in Malaysia. The findings from the study have highlighted the potential of the proposed interaction model that has affected the children enjoyment and engagement during the museum visit.

Informing Design of an Adaptive Learning Model for student with Dyslexia: A Preliminary Study

Students with dyslexia are known to have difficulties in phonology, spelling, reading, and writing. Therefore, specific intervention needs to be introduced to the students in order to help overcome their difficulties. The existence of Dyslexia Association of Malaysia (DAM) that provides dyslexic intensive education program becomes a primary place for parents to seek for help in intervention. Based on DAM experience in handling students with dyslexia, we conducted a preliminary study comprises semi-structured interview and observation result to uncover their teaching approaches and materials. The result from this preliminary study will be used to develop the adaptive learning model in order to make an effective learning experience that tailored to individual difficulties

Class Diagram Critic: A Design Critic Tool for UML Class Diagram

Unified Modeling Language (UML) diagrams are widely used in Computer Science courses. The UML Class Diagram is part of the most important and widely used diagrams in teaching UML. The learning of UML Class Diagram demands a sufficient guidance from the lecturers. Thus, a critic-based and collaborative approach was proposed in the design of the Class Diagram Critic (CDC) tool. The CDC is an educational tool that offers quick and meaningful feedback to students about UML class diagrams they design. Critics in CDC tool are mainly to critique errors in UML class diagrams, offer suggestions, and provide semi-automated design improvements to students. The CDC tool employed the collaborative approach as to support the collaborative learning between students and lecturers.

Inconsistency Detection of Model and Code via Critic-Based Approach

Model Driven Software Engineering (MDSE) has become the state of the art in software abstraction and increasingly popular in industry and academia. MDSE concerns the use of models as first-class artifacts of software development process. The MDSE has been seen as a way to manage the increasing of software complexity. However, one of the challenges in MDSE is to generate a consistent model-implementation mapping between design model and source code. Source code is also an important software development artifact as it represents the executable system. Detecting inconsistencies between design models and source code is hard because both artifacts normally will have some changes or modifications. Several researchers have introduced various methods in managing the inconsistency of model-code. In this paper, we propose a critic-based approach to detect the inconsistencies between design model and source code. The critic-based approach will provide instant feedback that point out the inconsistencies between model and code.