Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Zaheera Zainal Abidin
Universiti Teknikal Malaysia Melaka
Electrical & Electronics Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
New insider threat detection method based on recurrent neural networks Mohammed Nasser Al-mhiqani; Rabiah Ahmad; Zaheera Zainal Abidin; Warusia Yassin; Aslinda Hassan; Ameera Natasha Mohammad
Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 3: March 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v17.i3.pp1474-1479

Abstract

Insider threat is a significant challenge in cybersecurity. In comparison with outside attackers, inside attackers have more privileges and legitimate access to information and facilities that can cause considerable damage to an organization. Most organizations that implement traditional cybersecurity techniques, such as intrusion detection systems, fail to detect insider threats given the lack of extensive knowledge on insider behavior patterns. However, a sophisticated method is necessary for an in-depth understanding of insider activities that the insider performs in the organization. In this study, we propose a new conceptual method for insider threat detection on the basis of the behaviors of an insider. In addition, gated recurrent unit neural network will be explored further to enhance the insider threat detector. This method will identify the optimal behavioral pattern of insider actions.
An efficient method for estimating energy losses in distribution's feeder Nur Diana Izzani Masdzarif; Khairul Anwar Ibrahim; Chin Kim Gan; Mau Teng Au; Kyairul Azmi Baharin; Nurul A. Emran; Zaheera Zainal Abidin
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.5261

Abstract

This paper explains a simple and efficient methodology for calculating monthly energy losses (EL) using the load loss factor technique and a representative composite load profile. One of the important benefits of the proposed work is a simpler, more efficient and less rigorous method to estimate the system-wide energy loss of an extensive distribution network with reasonable accuracy. The sum of all EL provided by each feeder section is used to calculate the total feeder EL. A base case feeder with a typical cable type and power factor is used to generate regression equations, a peak power loss function to estimate the EL. A case study is then used to show the models and techniques that have been established. The result indicates a high level of agreement with the time-series load flow simulations (smaller than 10% deviations). With this model, an approach to estimate the EL of all radial feeders of various configurations and characteristics could be extended and implemented. The spreadsheet approach is ideal for completing a quick energy audit of existing distribution feeder EL and determining the sensitivity of distribution network efficiency to changes in feeder sections and load characteristics.
Co-Authors Ameera Natasha Mohammad Aslinda Hassan Chin Kim Gan Khairul Anwar Ibrahim Kyairul Azmi Baharin Mau Teng Au Mohammed Nasser Al-mhiqani Nur Diana Izzani Masdzarif Nurul A. Emran Rabiah Ahmad Warusia Yassin