Browsing by Author "Maskeliunas,R."

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Citation - Scopus: 3
Conflict resolution via emerging technologies?
(Institute of Physics Publishing, 2019) Yinka-Banjo,C.; Ugot,O.-A.; Misra,S.; Adewumi,A.; Damasevicius,R.; Maskeliunas,R.; Computer Engineering; 06. School Of Engineering; 01. Atılım University
This paper presents a review of the current techniques and approaches adopted in conflict resolution in Multi-Agent Systems (MAS). The review highlights the strength and weaknesses, and thus, their success in fostering cooperation and collaboration in multi-agent systems. We survey alternative approaches to conflict resolution that rely on emerging technologies such as deep learning. From the survey, we discuss the benefits of using these emerging technologies in the conflict resolution process. © 2019 Published under licence by IOP Publishing Ltd.
Citation - Scopus: 12
Design and Implementation of a Mobile Webcast Application With Google Analytics and Cloud Messaging Functionality
(Institute of Physics Publishing, 2019) Jonathan,O.; Misra,S.; Ibanga,E.; Maskeliunas,R.; Damasevicius,R.; Ahuja,R.; Computer Engineering; 06. School Of Engineering; 01. Atılım University
Church cast is an application developed to bring the messages of ministries closer to their members by harnessing the Internet and mobile devices. Due to the very busy schedules of people and religious restrictions in some countries, people are not usually able to be physically present at their locations of worship to listen to or watch their ministers. Existing applications developed in the past like DOMI radio and Redemption TV Media were limited to only audio, poor and unintuitive user interfaces and not providing the administrator any interactions with the users of the application. In this work, we develop an Android-based application that makes it possible for users to watch live streams and on-demand videos from their ministries using their mobile devices. The application also incorporates sharing and analytics functionalities to enable users to share videos messages with loved ones and help the administrator monitor users' activities on the application respectively. The cloud messaging functionality enables the administrator to send messages such as announcements to user devices as push notifications. This would eventually increase user knowledge and interaction with the activities going on in their respective places of worship. © 2019 Published under licence by IOP Publishing Ltd.
Citation - Scopus: 48
Identifying Phishing Attacks in Communication Networks Using Url Consistency Features
(Inderscience Publishers, 2020) Azeez,N.A.; Salaudeen,B.B.; Misra,S.; Damasevicius,R.; Maskeliunas,R.; Computer Engineering; 06. School Of Engineering; 01. Atılım University
Phishing is a fraudulent attempt by cybercriminals, where the target audience is addressed by a text message, phone call or e-mail, requesting classified and sensitive information after presenting himself/herself as a legitimate agent. Successful phishing attack may result into financial loss and identity theft. Identifying forensic characteristics of phishing attack can help to detect the attack and its perpetuators and as well as to enable defence against it. To shield internet users from phishing assaults, numerous anti-phishing models have been proposed. Currently employed techniques to handle these challenges are not sufficient and capable enough. We aim at identifying phishing sites in order to guard internet users from being vulnerable to any form of phishing attacks by verifying the conceptual and literal consistency between the uniform resource locator (URL) and the web content. The implementation of the proposed PhishDetect method achieves an accuracy of 99.1%; indicating that it is effective in detecting various forms of phishing attacks. © 2020 Inderscience Enterprises Ltd.. All rights reserved.
Identifying Phishing Attacks in Communication Networks Using Url Consistency Features
(Inderscience Publishers, 2020) Azeez,N.A.; Salaudeen,B.B.; Misra,S.; Damasevicius,R.; Maskeliunas,R.; Computer Engineering; 06. School Of Engineering; 01. Atılım University
Phishing is a fraudulent attempt by cybercriminals, where the target audience is addressed by a text message, phone call or e-mail, requesting classified and sensitive information after presenting himself/herself as a legitimate agent. Successful phishing attack may result into financial loss and identity theft. Identifying forensic characteristics of phishing attack can help to detect the attack and its perpetuators and as well as to enable defence against it. To shield internet users from phishing assaults, numerous anti-phishing models have been proposed. Currently employed techniques to handle these challenges are not sufficient and capable enough. We aim at identifying phishing sites in order to guard internet users from being vulnerable to any form of phishing attacks by verifying the conceptual and literal consistency between the uniform resource locator (URL) and the web content. The implementation of the proposed PhishDetect method achieves an accuracy of 99.1%; indicating that it is effective in detecting various forms of phishing attacks. © 2020 Inderscience Enterprises Ltd.. All rights reserved.
Citation - Scopus: 4
An Improved Feature Selection Method for Short Text Classification
(Institute of Physics Publishing, 2019) Abayomi-Alli,O.; Misra,S.; Matthews,V.O.; Odusami,M.; Abayomi-Alli,A.; Ahuja,R.; Maskeliunas,R.; Computer Engineering; 06. School Of Engineering; 01. Atılım University
Text has become one of the widest means of communication on mobile devices due to cheap rate and convenience for instance short text, web document, emails, instant messages. The exponential growth of text documents shared among users globally has increased the threat of misclassification associated with mobile devices such as Spam, Phishing, License to kill, Malware and privacy issues. Existing studies have shown that the major problem associated with text message classification is the poor representation of feature thus reducing accuracy and increasing f-measure rate. Thus, a modified Genetic Algorithm (GA) for improve feature selection and Artificial Immune System (AIS) algorithm was proposed for effective text classification in mobile short messages. The system will be deployed on an Android OS. © 2019 Published under licence by IOP Publishing Ltd.