Browsing by Author "Jayakody, A."

Now showing 1 - 6 of 6

Embargo
Agro-Mate: A Virtual Assister to Maximize Crop Yield in Agriculture Sector
(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Dayalini, S.; Sathana, M.; Navodya, P. R. N.; Weerakkodi, R.W. A. I. M. N.; Jayakody, A.; Gamage, N.
Information Technology plays a vital role in the agriculture industry. The main goal of the project is to develop a mobile application to support farmers to take accurate decisions and help them with activities such as soil quality determination, best crop selection, rice disease prediction, and disaster prediction for the wet zone of Sri Lanka. To achieve the main goal the project has incorporated advanced technologies such as Deep Learning, Image Processing (IP), Internet of Things (IoT), and Machine Learning that can support farmers or investors in a way to maximize yield. ‘Agro-Mate’ application is developed in a way to facilitate the agriculture industry. ‘Agro-Mate’ consists of four components such as soil quality determination and fertilizer recommendation, best crop selection, rice disease prediction and recommendation, and natural disaster prediction and providing the recommendation. Also, the application suggests fertilizer when soil is lacking quality and provides recommendations whenever rice diseases or natural disasters are identified. The usage of android mobile devices in agriculture is one of the key components of the sector's growth, which facilitates the farmer's inaccurate decision-making to gain more quality and quantity of crops. Agro-mate’ is more likely to increase the productivity of crops and indirectly increase the GDP of Sri Lanka.
Embargo
AI Based Cyber Threats and Vulnerability Detection,Prevention and Prediction System
(2019 1st International Conference on Advancements in Computing (ICAC), SLIIT, 2019-12-05) Amarasinghe, A.M.S.N.; Wijesinghe, W.A.C.H.; Nirmana, D.L.A.; Jayakody, A.; Priyankara, A.M.S.
Security of the computer systems is the most important factor for single users and businesses, because an attack on a system can cause data loss and considerable harm to the businesses. Due to the increment of the range of the cyber-attacks, anti-virus scanners cannot fulfil the need for protection. Hence, the increment of the skill level that required for the development of cyber threats and the availability of the attacking tools on the internet, the need for Artificial Intelligence-based systems, is a must to the users. The proposed approach is an automated system that consists of a mechanism to deploy vulnerabilities and a rich database with known vulnerabilities. The Convolutional Neural Networks detects the vulnerabilities and the artificial intelligence-based generative models do the prevention process and improves reliability. The prediction procedure implemented using the algorithm called “Time Series” and the model called “SARIMA”. These implementations give an output with considerable accuracy.
Embargo
Compromising AODV for better performance
(Faculty of Graduate Studies and Research, 2017-01-26) Jayakody, A.; Paranavithana, P.
MANETs became a principal research area as a promising routing protocol for a large scale of applications, due to its' behavior of self-configuring ability according to the infrastructure. Energy efficient in MANETs is a significant area in MANETs related researchers. Nodes in a MANET networks are basically battery operated, and thus have access to a limited amount of energy. The lack of energy can lead to a link failure during an active communication session, which affects the throughput and energy wastage due to a re-run of the algorithm. These papers presents a modified AODV algorithm, where a node calculates its residual energy and select the best path based on the existing matrices and total energy of the path. During the RREQ packet exchange, each node adds its residual energy to the packet and forwards it until it reaches the destination. At the destination, the total energy value is copied to the RREP packet from RREQ packet and sent to the source node through the reverse path. During the process of route selection, the path with the highest energy value gets the priority.
Open Access
Modified expanding ring search in common node scenario for AODV
(Faculty of Graduate Studies and Research, 2017-01-26) Jawadul, A. S.; Jayakody, A.
Mobile ad-hoc networks (MANET) are a collection of nodes without any static infrastructure. Ad-hoc networks establish connections between nodes without the help of centralized nodes but with the help of its neighbour nodes. The nodes are movable and can change its position frequently, so it maintains a dynamic interconnection between nodes in the network and adapts to dynamic topologies. MANETs are characterized by dynamic mobile nodes, with limited battery sourced power. These mobile nodes also act as routers taking its roles such as finding new routes, acting as an intermediate node, deciding best routes and keep a connection with mobile nodes. Any mobile node in the network can make the connection directly to any node within its transmission range, but due to its limited power, its transmission range also limited. Reactive routing protocols are effective than proactive routing protocols on MANETs since it can reduce extra overheads. However, reactive routing protocol suffers from excessive flooding in route discovery process. Authors focus on an existing solution called Expanding Ring Search (ERS) which decreases the flooding by manipulating Time to live (TTL) in AODV. ERS is also is inefficient in some scenarios. When the source is far from the destination ERS is worse than flooding [4]. Authors proposing a modification in ERS to avoid this problem which will make ERS efficient when the MANET consists a node (common node) that frequently accessed by most of the nodes.
Embargo
A New Approach for Consumer Protection with Business Intelligence and Data Visualization
(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Kariyawasam, K.S.T.U.S.; Liyanaarachchi, L.A.A.S.; Chathurabhani, H.M.N.N.; Jayakody, A.; Attanayaka, B.
According to the current market usage in Sri Lanka, there is no proper system to manage the buying and selling process of consumer goods and services. This paper presents a possibility of developing a systematic and essential food items management system using a mobile application with public and private interventions benefiting both the trade and the consumer is being explored. The authors discussed a methodology for managing essential food items through business intelligence and data visualization. It connects the trade and consumer sectors and the public and responsible private sectors related to this sector through a mobile application and presents data related to this sector through business intelligence forecasting and visualization methods. This research will also help reduce consumer problems by building transparency in the essential foodstuff sector. It will also systematically update the future of the essential food and beverage industry. The findings contribute to the body of knowledge on the New Approach for Consumer Protection with Business Intelligence and Data Visualization.
Embargo
Platform Independent Browser Forensic Tool for Advanced Analysis of Artifacts and Case Management
(2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Dissanayake, D.; Rajakaruna, S.; Ranasinghe, D.; Wijesooriya, A.; Jayakody, A.; Rajapaksha, S.
Abstract—A web browser is a major attack vector which cybercriminals utilize to land in an environment. The evidence related to the malicious browsing activities can be found in the host which gives valuable information related to the case. These digital footprints involve history, cookies, bookmarks, saved credentials and downloads etc. This paper presents a sophisticated tool aiding the conventional manual investigation process from evidence collection to the final v e rdict b y a u tomating h u man dependent functions, resulting a fast and unbiased analysis of browser forensic artifacts. This tool states its unique value over the existing tools by working operating systems independently, collecting all browsing evidence including deleted artifacts and encrypted saved credentials, automatically analysing the reputation of the extracted evidence, integrating evidence collected from different web browsers into a single timeline, and correlating the adjacent distrustful events inside and outside the host. Eventually, this tool calculates a browsing reputation scorecard and creates a profile for the host, condensing the findings g a thered t h roughout the investigation. The paper presents another important methodology to predict the future browsing reputation score based on the past browsing patterns. Furthermore, multiple cases management feature and dashboard provide a concise overview of overall findings to the forensic investigator.