Rehan Akbar

Universiti Teknologi PETRONAS, Computer and Information Sciences, Faculty Member

Universiti Teknologi PETRONAS, Computer & Information Sciences (CIS), Faculty Member

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I am working as Associate Professor in Department of Computer and Information Sciences at University Teknologi PETRONAS, Malaysia. Prior to joining UTP, I served Department of Information Systems, Faculty of Information & Communication Technology at Universiti Tunku Abdul Rahman, Malaysia as Associate Professor & Head of Department for about 10 years.
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Graphical authentication based on anti-shoulder surfing mechanism

Proceedings of the 2nd International Conference on Future Networks and Distributed Systems

Authentication is one of the most important mechanisms to ensure system accessibility by legitima... more Authentication is one of the most important mechanisms to ensure system accessibility by legitimate users. Various authentication tools exist based on numerous techniques. Distinguishing factors of such authentication tools are the underlying passwords that they imply. These passwords can be textual based, graphical based, hardware based or biometric based. All such password types have their pros and cons. The principle focus of this research is picture-based graphical passwords, since they are easy to remember and can overcome the limitations of using long textual passwords for stronger security. However, mostly the picture-based passwords suffer from shoulder surfing attacks and are therefore vulnerable. If this vulnerability is overcome then such graphical passwords are highly useful because of their strength and ease of use as compared to long textual passwords. The main objective of this research is to propose and develop a picture-based authentication scheme with anti shoulder surfing capability. The proposed authentication scheme consists of both password creation and usage. Both these stages are supported by specialized technical constructs that overcome the anti shoulder surfing attack even if the attacker is standing next to the legitimate user.

Automatic Sentiment Annotation of Idiomatic Expressions for Sentiment Analysis Task

IEEE Access

Social media users use words and phrases to convey their views or opinions. However, some people ... more Social media users use words and phrases to convey their views or opinions. However, some people use idioms or proverbs that are implicit and indirect to make a stronger impression on the audience or perhaps catch their attention by utilizing funny, sarcastic, or metaphorical phrases. Idioms and proverbs are figurative expressions with a thematically coherent totality that cannot be understood literally. In previous work, the extension of IBM's Sentiment Lexicon of Idiomatic Expressions was proposed to include around 9,000 idioms; a crowdsourcing service manually annotates both lexicons. Therefore, in this research, we provide a knowledge-based expansion approach to avoid human annotation of idioms. For sentiment classification, the proposed method has the advantage that it does not require any fine-tuning for the BERT model. Experimental comparisons show that automated idiom enrichment and annotation are very beneficial for the performance of the sentiment classifier. The expanded annotated lexicon will be made available to the general public.

Rehan Akbar

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