Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal Jurnal Teknologi Informasi dan Pendidikan Electron: Jurnal Ilmiah Teknik Elektro
Setiawan, Putu Ayu Citra
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering

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

Found 2 Documents
Search

 1 
Tinjauan Literatur: Deteksi Anomali Berbasis Analisis Waktu pada CAN Bus Kendaraan Listrik Setiawan, Putu Ayu Citra; Giriantari, Ida Ayu Dwi; ER, Ngurah Indra
ELECTRON Jurnal Ilmiah Teknik Elektro Vol 6 No 1: Jurnal Electron, Mei 2025
Publisher : Jurusan Teknik Elektro Fakultas Teknik Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33019/electron.v6i1.282

Abstract

The development of modern automotive technology emphasizes the importance of vehicle connectivity and autonomy, with the aim of enhancing safety and comfort. Due to its role in managing critical vehicle functions and its vulnerability to security threats, the automotive industry has developed two primary approaches to address CAN Bus security. Therefore, the automotive industry has developed two main approaches to address this security issue. First, passive defense through security protocols that include encryption, authentication, and message verification, and second, anomaly detection using advanced technologies. Several anomaly detection methods have been introduced, including K-Means clustering, Support Vector Machines, and Deep Learning, each offering advantages in detecting specific attack patterns. However, one increasingly popular approach is time analysis, which leverages message inter-arrival patterns and clock skew on the CAN Bus to identify suspicious behavior and detect anomalies in real-time. Although this method has shown effectiveness in detecting various types of attacks, the main challenge lies in its ability to identify highly concealed attacks that may not be visible to traditional methods. This research provides an understanding of various anomaly detection approaches on electric vehicle CAN Bus networks, with a primary focus on time analysis. By reviewing several approaches, this study offers valuable insights into improving the security of electric vehicles and the overall smart transportation ecosystem. The results show that time-based analysis methods can detect various types of attacks, such as spoofing, replay attacks, and denial-of-service, with high efficiency.
Potensi Metode Regresi Kuat dalam Pengukuran Skew Jam Setiawan, Putu Ayu Citra; Saputra, Komang Oka; Wiharta, Dewa Made
Jurnal Teknologi Informasi dan Pendidikan Vol. 18 No. 1 (2025): Jurnal Teknologi Informasi dan Pendidikan
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jtip.v18i1.962

Abstract

Clock skew, defined as the difference in clock rates between digital devices, serves as a unique and stable fingerprint for device identification and authentication, particularly in distributed network environments. Traditional clock skew estimation techniques, such as linear regression, are effective under stable conditions but often fail in the presence of data disturbances, such as latency, jitter, and asymmetric delays, which introduce outliers. This study explores the application of robust regression methods to enhance the accuracy and stability of clock skew estimation under such conditions. Three robust techniques are comparatively analyzed: Least Median of Squares (LMedS), Random Sample Consensus (RANSAC), and S-Estimators. LMedS offers high resistance to outliers by minimizing the median of squared residuals, though it is computationally demanding for large datasets. RANSAC achieves a practical balance between robustness and efficiency through iterative model fitting and inlier maximization, while S-Estimators provide strong statistical resistance to both outliers and high-leverage points, albeit with increased implementation complexity. The comparative evaluation considers key parameters such as estimation accuracy, computational cost, and robustness to anomalies. Results indicate that RANSAC is generally preferred for clock skew measurement in distributed systems due to its efficient performance and explicit outlier detection capabilities. However, LMedS and S-Estimators remain valuable in scenarios with more complex anomaly structures or higher noise levels. This study contributes to the selection of appropriate robust regression methods for reliable clock skew estimation in dynamic and error-prone network environments.
Co-Authors Dewa Made Wiharta Ida Ayu Dwi Giriantari Ngurah Indra ER Saputra, Komang Oka