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Journal of ICT Research and Applications
Published by Institut Teknologi Bandung
ISSN : 23375787     EISSN : 23385499     DOI : https://doi.org/10.5614/itbj.ict.res.appl.
Core Subject : Science,
Computer Science & IT
Journal of ICT Research and Applications welcomes full research articles in the area of Information and Communication Technology from the following subject areas: Information Theory, Signal Processing, Electronics, Computer Network, Telecommunication, Wireless & Mobile Computing, Internet Technology, Multimedia, Software Engineering, Computer Science, Information System and Knowledge Management.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 302 Documents
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Automatically Detect Software Security Vulnerabilities Based on Natural Language Processing Techniques and Machine Learning Algorithms Do Xuan Cho; Vu Ngoc Son; Duong Duc
Journal of ICT Research and Applications Vol. 16 No. 1 (2022)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2022.16.1.5

Abstract

Nowadays, software vulnerabilities pose a serious problem, because cyber-attackers often find ways to attack a system by exploiting software vulnerabilities. Detecting software vulnerabilities can be done using two main methods: i) signature-based detection, i.e. methods based on a list of known security vulnerabilities as a basis for contrasting and comparing; ii) behavior analysis-based detection using classification algorithms, i.e., methods based on analyzing the software code. In order to improve the ability to accurately detect software security vulnerabilities, this study proposes a new approach based on a technique of analyzing and standardizing software code and the random forest (RF) classification algorithm. The novelty and advantages of our proposed method are that to determine abnormal behavior of functions in the software, instead of trying to define behaviors of functions, this study uses the Word2vec natural language processing model to normalize and extract features of functions. Finally, to detect security vulnerabilities in the functions, this study proposes to use a popular and effective supervised machine learning algorithm.
Cover JICTRA Vol. 13 No. 1, 2019 Journal of ICT Research and Applications
Journal of ICT Research and Applications Vol. 13 No. 1 (2019)
Publisher : LPPM ITB

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Abstract

Cover JICTRA Vol. 13 No. 2, 2019 Journal of ICT Research and Applications
Journal of ICT Research and Applications Vol. 13 No. 2 (2019)
Publisher : LPPM ITB

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Abstract

Cover JICTRA Vol. 13 No. 3, 2019 Journal of ICT Research and Applications
Journal of ICT Research and Applications Vol. 13 No. 3 (2019)
Publisher : LPPM ITB

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Cover JICTRA Vol. 14 No. 1, 2020 Journal of ICT Research and Applications
Journal of ICT Research and Applications Vol. 14 No. 1 (2020)
Publisher : LPPM ITB

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Cover JICTRA Vol. 14 No. 2, 2020 Journal of ICT Research and Applications
Journal of ICT Research and Applications Vol. 14 No. 2 (2020)
Publisher : LPPM ITB

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Cover JICTRA Vol. 14 No. 3, 2021 Journal of ICT Research and Applications
Journal of ICT Research and Applications Vol. 14 No. 3 (2021)
Publisher : LPPM ITB

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Abstract

A Classifier to Detect Profit and Non Profit Websites Upon Textual Metrics for Security Purposes Yahya Tashtoush; Dirar Darweesh; Omar Darwish; Belal Alsinglawi; Rasha Obeidat
Journal of ICT Research and Applications Vol. 16 No. 1 (2022)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2022.16.1.6

Abstract

Currently, most organizations have a defense system to protect their digital communication network against cyberattacks. However, these defense systems deal with all network traffic regardless if it is from profit or non-profit websites. This leads to enforcing more security policies, which negatively affects network speed. Since most dangerous cyberattacks are aimed at commercial websites, because they contain more critical data such as credit card numbers, it is better to set up the defense system priorities towards actual attacks that come from profit websites. This study evaluated the effect of textual website metrics in determining the type of website as profit or nonprofit for security purposes. Classifiers were built to predict the type of website as profit or non-profit by applying machine learning techniques on a dataset. The corpus used for this research included profit and non-profit websites. Both traditional and deep machine learning techniques were applied. The results showed that J48 performed best in terms of accuracy according to its outcomes in all cases. The newly built models can be a significant tool for defense systems of organizations, as they will help them to implement the necessary security policies associated with attacks that come from both profit and non-profit websites. This will have a positive impact on the security and efficiency of the network.
Towards Enhancing Keyframe Extraction Strategy for Summarizing Surveillance Video: An Implementation Study Bashir Olaniyi Sadiq; Habeeb Bello-Salau; Latifat Abduraheem-Olaniyi; Bilyaminu Muhammed; Sikiru Olayinka Zakariyya
Journal of ICT Research and Applications Vol. 16 No. 2 (2022)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2022.16.2.5

Abstract

The large amounts of surveillance video data are recorded, containing many redundant video frames, which makes video browsing and retrieval difficult, thus increasing bandwidth utilization, storage capacity, and time consumed. To ensure the reduction in bandwidth utilization and storage capacity to the barest minimum, keyframe extraction strategies have been developed. These strategies are implemented to extract unique keyframes whilst removing redundancies. Despite the achieved improvement in keyframe extraction processes, there still exist a significant number of redundant frames in summarized videos. With a view to addressing this issue, the current paper proposes an enhanced keyframe extraction strategy using k-means clustering and a statistical approach. Surveillance footage, movie clips, advertisements, and sports videos from a benchmark database as well as Compeng IP surveillance videos were used to evaluate the performance of the proposed method. In terms of compression ratio, the results showed that the proposed scheme outperformed existing schemes by 2.82%. This implies that the proposed scheme further removed redundant frames whiles retaining video quality. In terms of video playtime, there was an average reduction of 27.32%, thus making video content retrieval less cumbersome when compared with existing schemes. Implementation was done using MATLAB R2020b.
Strengthening INORMALS Using Context-based Natural Language Generation Soni Yora; Ari Moesriami Barmawi
Journal of ICT Research and Applications Vol. 16 No. 2 (2022)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2022.16.2.1

Abstract

The noiseless steganography method that has been proposed by Wibowo can embed up to six characters in the provided cover text, but more than 59% of Indonesian words have a length of more than six characters, so there is room to improve Wibowo’s method. This paper proposes an improvement of Wibowo’s method by modifying the shifting codes and using context-based language generation. Based on 300 test messages, 99% of messages with more than six characters could be embedded by the proposed method, while using Wibowo’s method this was only 34%. Wibowo’s method can embed more than six characters only if the number of shifting codes is less than three, while the proposed method can embed more than six characters even if there are more than three shifting codes. Furthermore, the security for representing the number of code digits is increased by introducing a private key with the probability of guessing less than 1, while in Wibowo’s method this is 1. The naturalness of the cover sentences generated by the proposed method was maintained, which was about 99% when using the proposed method, while it was 98.61% when using Wibowo’s method.

Page 25 of 31 | Total Record : 302

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