International Conference on Advancements in Computing [ICAC]
Permanent URI for this communityhttps://rda.sliit.lk/handle/123456789/312
The International Conference on Advancements in Computing (ICAC) is organized by the Faculty of Computing of the Sri Lanka Institute of Information Technology (SLIIT) as an open forum for academics along with industry professionals to present the latest findings and research output and practical deployments in computing.
The primary objective of ICAC is to promote innovative research that addresses real-world challenges and contributes to the social well-being of communities. The conference provides a dynamic platform for researchers from around the world to present groundbreaking findings, exchange ideas, and establish meaningful collaborations.
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Publication Embargo Anomaly Detection in Microservice Systems Using Autoencoders(IEEE, 2022-12-09) de Silva, M; Daniel, S; Kumarapeli, M; Mahadura, S; Rupasinghe, L; Liyanapathirana, CThe adaptation of microservice architecture has increased massively during the last few years with the emergence of the cloud. Containers have become a common choice for microservices architecture instead of VMs (Virtual Machines) due to their portability and optimized resource usage characteristics. Along with the containers, container-orchestration platforms are also becoming an integral part of microservice-based systems, considering the flexibility and scalability offered by the container-orchestration media. With the virtualized implementation and the dynamic attribute of modern microservice architecture, it has been a cumbersome task to implement a proper observability mechanism to detect abnormal behaviour using conventional monitoring tools, which are most suitable for static infrastructures. We present a system that will collect required data with the understanding of the dynamic attribute of the system and identify anomalies with efficient data analysis methods.Publication Embargo Smart Advertising Based on Customer Preferences and Manage the Supermarket(IEEE, 2022-12-09) Wickramasinghe, A.Y.S. W; Eishan Dinuka, W.H.A.; Weerasinghe, W.S. H; Karunaratne, K.P. G; Liyanapathirana, C; Rupasinghe, LAs a developing country, Sri Lanka needs to go along with cutting-edge technologies. In the beginning phase of this digital advertising, multiple advertisements were displayed on the users’ feeds, including advertisements despite their preferences. This was a terrible user experience for the users. However, smart advertising based on customer preferences can manage the flow of advertisements on the feed as per the users’ preferences. This same technique can be used in handling advertisements while shopping at supermarkets. These advertisements can be directed based on demographic characteristics like face and gender and previous customer transactions. Additionally, providing the nearest supermarket they can reach based on their current location. Queue management is the next most crucial facility that needs to be provided to a supermarket. However, the manual system of queue management is not effective. But with a modernized queue management system, overcrowded supermarkets can be managed effectively. This proposed system also considers providing a chatbot service to manage customer inquiries in a reliable strategy. In this system, we mainly used the Keras model called VGGFace for face detection, the Conventional Neural Network and Keras-based model for gender detection, the TensorFlow model called Single Shot MultiBox Detection MobileNet for queue and crowd detection, the Apriori algorithm base model for predicting the buying pattern, a Keras-based model for Artificial Intelligence chatbot and finally, google map Application Programming Interface for the nearest supermarket finding are models and technology. This system was developed to manage a supermarket properly.Publication Embargo FIMAA: Four-way Integrated Mobile Authentication API(IEEE, 2019-12-05) Kariyawasam, L; Moonamaldeniya, M; Samarawickrama, V; Premalal, S. H; Rupasinghe, L; Abeywardena, K. YIn this era of the digital world, mobile device users have been increased to a significant number. This proposed system presents a hybrid authentication approach which can be considered as a combination of silent authentication and input based authentication to enhance mobile security in android mobile applications. A four-way integrated mobile API introduces the gait patterns and location traces as well as the image context and face ID-based emotions of the user. This application silently authenticates the exposed location trace and gait patterns of the user while other ear and emotion inputs will be prompted to end-user accordingly with input authentication.Publication Embargo Comprehensive Forensic Data Extraction and Representation System for Windows Registry(IEEE, 2019-12-05) W. De Alwis, C; Rupasinghe, LComputer forensics is the process of methodically examining computer media (hard disks, diskettes, tapes, etc.) for evidence. When considering computer forensics, registry forensics plays a vital role because it helps identifying system configurations, application details, user configurations and helps in finding registry malware. Therefore, it is significant to extract this registry information to simplify the investigations for forensic professionals. At present, tools are limited to few commonly used registry information and there is a much border area to cover. Investigators have to manually search for the registries for required artifacts. But the nature and complexity of the registry file structure limits most of the investigators using these registries. Limiting this registry analysis only to the physical registry files and not considering the ability of extraction of registry information from Volatile Memory is another significant issue in registry forensics. Because these tools are only rely on the physical registry files and cannot extract registry artifacts from Volatile Memory. In order to cater to this problem, this research provide a comprehensive solution to registry analysis. This system is capable of extracting registry information from both physical registry files and Volatile Memory.Publication Embargo Intelligent Flood Management System(IEEE, 2019-12-05) Fernando, M. J. D; Pathirana, D. A. K. K; Jayasooriya, W. J. K. T. D; Rathnaweera, S. A. H; Rupasinghe, LFlooding is one of the major disasters in Sri Lanka. In Sri Lanka, there are no effective pre preparedness procedures follow in a flooding situation. The setting of pre and post-disaster activities like mitigation, preparedness, response, and recovery have very important roles in reducing future hazard risk in disaster-prone areas. Lack of communication and coordination during a disaster situation has led inefficiencies in mitigating adverse, in that situation, messages requesting for any assistance are sent to a central cloud system where the system generates response automatically and communicate and coordinate with the relevant parties. The genetic programming methods have used to plan relief supply distribution and safety location allocation for the flood-affected people in Sri Lanka. The research provides a guide for the administration of flood management for decision making on flood disaster management, preparedness and mitigation damages and deaths, recovery, and development in post-disaster situations in Sri Lanka.Publication Embargo Online Music Platform to Create Interaction between Music Artists and Fans(IEEE, 2019-12-05) Rupasinghe, L; Fernando, W. J. C; Perera, A. G. M. M; Weerasooriya, D. G. T. V; Perera, K. A. D. W. H. DIn music industry, purchasing of digital music has been popular lately. This online music platforms make music artists to upload their piece of work and their fans will purchase the songs. When purchasing songs, some people may face problems like not secured way or non-transparency of currency and data transaction. The transparency of currency and data files are not there in most of the platforms, it will make doubt the users about the transactions. Also, People frequently change their music listening behaviors. Which scales by the genres, artist, or specific tracks. When someone wants to find a song which was heard for the first time, he/she would not be able to remember the song at once. If the song is in other language it is difficult to find that because less knowledge of that language. If that language of the song can be translated to English language. But what if they remember nothing of the song or singer but know how to sing or hum a part of that song. And also when a person is singing or humming there are some situations lead to errors such as not in the right pitch, background noise.Publication Embargo FIMAA: Four-way Integrated Mobile Authentication API(IEEE, 2019-12-05) Kariyawasam, L; Moonamaldeniya, M; Samarawickrama, V; Premalal, S. H; Rupasinghe, L; Abeywardena, K. YIn this era of the digital world, mobile device users have been increased to a significant number. This proposed system presents a hybrid authentication approach which can be considered as a combination of silent authentication and input based authentication to enhance mobile security in android mobile applications. A four-way integrated mobile API introduces the gait patterns and location traces as well as the image context and face ID-based emotions of the user. This application silently authenticates the exposed location trace and gait patterns of the user while other ear and emotion inputs will be prompted to end-user accordingly with input authentication.Publication Embargo An Automated Tool for Memory Forensics(IEEE, 2019-12-05) Murthaja, M; Sahayanathan, B; Munasinghe, A. N. T. S; Uthayakumar, D; Rupasinghe, L; Senarathne, AIn the present, memory forensics has captured the world's attention. Currently, the volatility framework is used to extract artifacts from the memory dump, and the extracted artifacts are then used to investigate and to identify the malicious processes in the memory dump. The investigation process must be conducted manually, since the volatility framework provides only the artifacts that exist in the memory dump. In this paper, we investigate the four predominant domains of registry, DLL, API calls and network connections in memory forensics to implement the system `Malfore,' which helps automate the entire process of memory forensics. We use the cuckoo sandbox to analyze malware samples and to obtain memory dumps and volatility frameworks to extract artifacts from the memory dump. The finalized dataset was evaluated using several machine learning algorithms, including RNN. The highest accuracy achieved was 98%, and it was reached using a recurrent neural network model, fitted to the data extracted from the DLL artifacts, and 92% accuracy was reached using a recurrent neural network model, fitted to data extracted from the network connection artifacts.Publication Embargo Emergency Patient Identification System(IEEE, 2019-12-05) Sandamal, T; Fernando, N; Jayasinghe, I; Xavier, J; Kuruwitaarachchi, N; Rupasinghe, LEmergency patient identification system (EPIS) will enable the more powerful quality system in the health industry. This research study was conducted to develop an EPI system, which is a complete patient-based medical information recording system. This system will help to identify the patients uniquely. Doctors can get patients' latest situation and can make quick decisions to do the treatments in emergencies. To achieve this approach, authors use the patient's fingerprint, face recognition technology, and eye recognition to identify the person. The patient can view his medical records; system reminds the notifications. The system helps the patients in storing and tracking the diet weight, medications, allergies, health history, fitness, lab results, x-rays, blood pressure, ongoing surgeries, drug reminders, doctor visits, doctor's appointments, images and more. The system helps the user in receiving and sending necessary health-related information to the doctors and hospitals. This system has many unique features; an emergency will help to find nearest hospitals. This can add patient's family member's history so it can help to remind his present medical situation. The main system is working on web interface; another part is offered as a mobile application.Publication Embargo Mobile-based Malware Detection and Classification using Ensemble Artificial Intelligence(IEEE, 2019-12-05) Somasundaram, S; Kasthurirathna, D; Rupasinghe, LThe Android operating system is one of the most used operating systems in the world and has become a target to malware authors. Traditional malware detection methods such as signatures find it impossible to deal with detecting complex and intelligent malware which are capable of obfuscating and repackaging to avoid being detected. There is therefore an increase in the need to have more efficient and intelligent forms of malware detection. Artificial intelligence has now been brought to the field of malware detection and classification. Due to its accuracy and intelligence it has become an ideal solution to bridge the gap between traditional classifiers and the intelligent malware. Currently, research is mainly being conducted using either machine learning or deep learning techniques to target all or a given malware family. This paper proposes a methodology which brings an ensemble solution between the Support Vector Machine algorithm and the Convolutional Neural Network to create a solution that provides a higher accuracy than available techniques.