Scopus Index Publications

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This collection consists of all Scopus-indexed publications produced by SLIIT researchers. Scopus is recognized worldwide as a leading and reputable academic indexing database.

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Start date: 2018End date: 2019

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Now showing 1 - 10 of 17
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    DNS Cache Poisoning: A Review on its Technique and Countermeasures
    (IEEE, 2018-10-02) Dissanayake, I. M. M
    IP address is the basis of Internet server communication. Many attackers try to spoof Domain Name System using different techniques to introduce false IP addresses to client servers. Use of cache memory is the most commonly seen type, which is known as DNS cache poisoning. This attack has become a serious threat to information security at individual and organizational levels. The purpose of this article is to study Domain Name System and the mechanism of DNS cache poisoning. Further, this paper will discuss countermeasures used against DNS cache poisoning. Many scholars have presented different methods of cache poisoning and the most recent technique was introduced by Kaminsky in 2008. Many researches have been done throughout the world to invent more secure countermeasures against DNS cache poisoning and the most commonly used countermeasure is Domain Name System Security Extensions. However, there are different countermeasures against DNS cache poisoning; none of the countermeasure could certify the action against DNS cache poisoning. Hence, future researches should be oriented towards to introducing more trustworthy countermeasures against DNS cache poisoning and new identical infrastructure for internet browsing other than DNS.
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    Smart Monitor for Tracking Child's Brain Development
    (researchgate.net, 2019-03) Anparasanesan, T; Mathangi, K; Seyon, S; Kobikanth, S; Gamage, A
    This paper provides a way to track the brain development of children and improving it via gamification. Machine Learning and Gamification are the key technologies used here. As the population rises, the demand for cost-effective methods to reduce the rate of cognitive decline becomes higher. A mobile application is developed to track and develop the brain development of children. In the mobile application, the child initially undergoes an evaluation phase to determine the current level of the cognitive skills of the child. Milestones particular to that age category are also tracked in this evaluation phase. The results of this evaluation phase are analyzed by the machine learning model and suitable brain games are suggested. K-means algorithm is used to develop the model which is an unsupervised learning algorithm. The dataset is prepared by storing the results of each game category in the evaluation phase. Data preprocessing is done to clean up the dataset. During this period, data undergoes a series of steps. The dataset is divided into 80% and 20%. 80% of the dataset is used as the training dataset and the remaining 20% as the test dataset. The accuracy of the model is checked several times against the test data. Model accuracy is improved through model training and finally, the model got an accuracy of 88.49%. For the child, proper training is given to improve his cognitive skills and thus the brain development using Gamification. Games are developed using the UNITY game engine. The system generates a report and notifies parents about their child's statistics periodically. This paper elaborates the procedure of model development, model training, model testing and development of suitable brain games in details. The results of the research work and future works are also discussed in the following sections.
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    PublicationOpen Access
    Review on vibration quality improvement of a passenger seat
    (researchgate.net, 2019-03) Perera, M; Rikaz, M; Abeysinghe, A
    Seats are one of the most significant components of vehicles. Customer’s expectations for the comfort in vehicle seats rise continuously. Designing of automobile seats has always been a challenge for engineers as design parameters for automobile seats are complex. When it comes to the design of automobile seats, three design objectives, namely comfort, safety and health need to be fulfilled simultaneously. Vibration analysis plays a major role in engineering including the area of design for automobile comfort. Human structure, as a mechanical system, is immensely complex and the mechanical properties of human body readily undergo change. In addition, the vibration can initiate the development of pressure ulcer and other long-term diseases. Comfort measurement is challenging because of such factors as user subjectivity, seat geometry, occupant anthropometry and amount of time spent sitting. The purpose of this study is to identify the most significant parameters that make vibration in the vehicle seat which reduce passenger comfort and to identify the design parameters that can impact on appropriate seat design. Suspension systems, seat cushion and sitting postures are some of the vital parameters that have huge impacts on comfort analysis. This review could help in design of seat cushions with appropriate material properties and in analysing the comfort levels of human body to reduce the vibration transmissibility at the critical frequency bands
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    PublicationOpen Access
    Factors Influencing the Private Cost of Higher Education; the Case of Sri Lanka
    (researchgate.net, 2019-03) Gobinath, S; Tharshan, K; Dheerasekara, W. R. H; Gunawardena, M.M.D de S; Jayakody, S. G; Lokeshwara, A. A
    The research aims to identify and analyze the cost elements that impact the private cost of university education in Sri Lanka. It focused on determining the private cost of the Bachelor’s degree programs and also the cost elements affecting the total private cost and their significance. Twenty one cost categories were identified through a pilot study and analyzed in order to assess their impact on the private cost and their variability based on field of study, gender, programme duration, and the socio-economic group of undergraduates. The population comprised of students enrolled in private higher education institutes offering Bachelor’s degree programs in Sri Lanka. The study was conducted during the 2016/2017 academic year and the sample contained 419 respondents drawn utilizing the purposive and stratified random sampling procedures. The data were analyzed using descriptive statistics, while the hypotheses were tested using the Chi-square test for independent sample statistics at 0.05 level of significance. It was found that majority of cost categories (15) had significantly varied between fields of study undertaken while minority of cost categories (10) varied significantly between students’ gender. The study revealed that the identified factors influenced the private cost of university education in the Sri Lankan context.
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    Occupancy Monitoring System for Workplace Washrooms
    (IEEE, 2019-03-28) Godakandage, V. M. P; Kothalawala, K. R. M; Chathumali, E. J. A; Madhubhashana, A. W
    With regard to rapid technological advancements majorly influencing our daily lives, Internet of Things (IoT) has been a topic of broad and current interest in the recent years. The capabilities of IoT can assist in revolutionizing the way people live and work, thereby improving quality of life. With the impact of IoT only continuing to propagate in the future, it can be used as a means of easing our day-to-day struggles. Therefore, with the assistance of IoT along with a few hardware, the proposed system, addresses the displeasing reality of queues and several visits for the washrooms due to them coming forth occupied. Thus, the focus of the intended system is on delivering a pleasant washroom experience for employees in an office environment providing them with an at-desk indication on the occupancy of the washroom cubicles reducing queues and disappointments.
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    On the scaling of virtualized network functions
    (IEEE, 2019-05-20) Rankothge, W; Ramalhinho, H; Lobo, J
    Offering Virtualized Network Functions (VNFs) as a service requires automation of cloud resource management to allocate cloud resources for the VNFs dynamically. Most of the existing solutions focus only on the initial resource allocation. However, the allocation of resources must adapt to dynamic traffic demands and support fast scaling mechanisms. There are three basic scaling models: vertical where re-scaling is achieved by changing the resources assigned to the VNF in the host server, horizontal where VNFs are replicated or removed to do rescaling, and migration where VNFs are moved to servers with more resources. In this paper, we present an Iterated Local Search (ILS) based framework for automation of resource reallocation that supports the three scaling models. We, then, use the framework to run experiments and compare the different scaling approaches, specifically how the optimization is affected by the scaling approach and the optimization objectives.
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    Parade in the Virtual Dressing Room
    (IEEE, 2018-08) Priyadharsun, S; Lakshigan, S; Baheerathan, S. S; Rajasooriyar, S; Rajapaksha, U. U. S. K; Harshanath, S. M. B
    Fashion has always been in the forefront especially with the youngsters. The interest in fashion can vary according to the country, region, culture, age, seasons, climates, places visited, attitude, personal interests etc. Some of them, however, have difficulties finding out about suitable dressing styles for them. Meeting this need is the purpose of this application. On the other hand, social networks are an easy way to interact with the teenagers. In this new age social network site, users create a profile and enter their body measurements to create a virtual model of the particular user. They can also upload their photos to create a complete virtual model which includes face as well. It was necessary to add business value to the application along with the usual entertainment factors. Adding business value to entertainment factors is the main attraction in Fashion Fit to suit a new age of social networking.
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    EyeDriver: Intelligent Driver Assistance System
    (IEEE, 2019-12-18) Gayadeeptha, P; Baddewithana, T. P; Pannegama, K. V; Samarakkody, C. S; Samarasinghe, P; Siriwardana, S
    “EyeDriver” is a driver assistance system that analyzes and provides real-time driver assistant data from four separate components. These main components are drowsiness detection and head pose estimation, over-speed detection, lane departure, and front collision avoidance. It is a compact product that included a Raspberry pi board, a USB camera module, Pi camera, and a TFT LCD. Since the “EyeDriver” is a first affordable aftermarket solution in Sri Lanka, it can be mounted and configured in any vehicle without any professional knowledge in less effort. Drowsiness detection and head pose estimation component will monitor the driver's eyes and keep track of whether the driver's head's position is inconsistent or deviated from the optimal position. In accordance with the road's recommended speed, the vehicle's actual speed is analyzed and if it is more than the permitted, the system makes a notification. It is done by the over-speed detection component. Lane departure component consists of assisting in keeping the vehicle stable on the desired lane on the road. Also, when the driver makes an intended lane change, the system provides a notification. The Front collision avoidance part will detect the frontal obstacle on the road and provide pre-collision/proximity warning notification. The notification makes according to the vehicle speed and distance between the object and the vehicles. The whole system is based on the Raspberry Pi 3 Model B+ board and the implementation of the system has been done by using OpenCV and Python.
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    Tempcache: A Database Optimization Algorithm for Real-Time Data Handling in Indoor Spatial Environments
    (IEEE, 2018-08-08) Jayakody, A; Murray, I; Hermann, J; Lokuliyana, S; Dunuwila, V. R
    The unstable arrangement of modern indoor environments has made navigation within buildings a difficult task. Hence, this paper introduces the AccessBIM framework, which is an efficient real-time indoor navigation system that facilitates in generating a real-time indoor map by crowdsourcing spatial data through the sensors available in mobile devices of navigators. The framework is equipped with a database optimization algorithm known as “Tempcache” which reduces the time and cost of searching data by examining the AccessBIM database for previously navigated paths, thus enabling faster data retrieval through efficient query processing. A simulation of a virtual environment similar to an actual indoor environment was used to test the algorithm. The significance of the algorithm was validated by comparing the total map generation time before and after the algorithm was applied for which the results demonstrated a reduction in map generation time with the use of the algorithm. The framework is also capable of capturing localization information with the support of i-Beacons which is then stored in a cloud server.
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    Location based garbage management system with iot for smart city
    (IEEE, 2018-08-08) Lokuliyana, S; Jayakody, A; Dabarera, G. S. B; Ranaweera, R. K. R; Perera, P. G. D. M; Panangala, P. A. D. V. R
    Smart cities integrate multiple ICT and IOT solutions to build a comfortable human habitation. One of these solutions is to provide an environmentally friendly, efficient and effective garbage management system. The current garbage collection system includes routine garbage trucks doing rounds daily or weekly, which not only doesn't cover every zone of the city but is a completely inefficient use of government resources. This paper proposes a cost-effective IOT based system for the government to utilize available resources to efficiently manage the overwhelming amounts of garbage collected each day, while also providing a better solution for the inconvenience of garbage disposal for the citizens. This is done by a network of smart bins which integrates cloud-based techniques to monitor and analyze data collected to provide predictive routes generated through algorithms for garbage trucks. An android app is developed for the workforce and the citizens, which primarily provides the generated routes for the workforce and finds the nearest available smart bin for citizens.