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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics
Abbas M. Al-Ghaili
Universiti Tenaga Nasional (UNITEN)
Computer Science & IT Electrical & Electronics Engineering

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A secured data transform-and-transfer algorithm for energy internet-of-things applications Abbas M. Al-Ghaili; Hairoladenan Kasim; Naif Mohammed Al-Hada
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 6: December 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i6.21665

Abstract

Digital transformation (DT) is one of the key technologies with effective impacts on many traditional processes towards a digital world. DT influences the way other digital services behave. Hence, there is a need to consider DT-related processes carefully specifically while designing phase. DT contributes to many services. It can, for example, contribute to implement security tasks applied to digital contents and therefore can be applied to change contents being secured. One of the transformation ways applied in security is to consider the way those digital contents are being stored or transferred. This paper proposes a DT algorithm (DTA) for energy internet-of-things (EIOT) contents. DTA consists of two steps, to convert original contents to another digital form and to transfer that form utilizing IOT. This paper utilizes DT in term of security. EIOT contents are converted to increase security. It is aimed to transfer EIOT contents to destination safely and efficiently. Thus, EIOT contents are transformed first to hide original contents. To make sure that the transferring process is done safely, DTA is evaluated in terms of efficiency, accuracy, and robustness. Results confirm that DTA is efficient, accurate, and robust against loss of bits caused by transferring.
QR code based authentication method for IoT applications using three security layers Abbas M. Al-Ghaili; Hairoladenan Kasim; Marini Othman; Wahidah Hashim
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 4: August 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i4.14748

Abstract

A quick response code-based authentication method (QRAM) is proposed. QRAM is applicable for lots of internet of things (IoT) applications. QRAM aims to verify requests of such an access to IoT applications. Requests are made using a quick response code (QRC). To authenticate contents of QRC, users will scan QRC to access IoT applications. To authenticate contents of QRC, three procedures are applied. QRAM contributes to IoT automatic access systems or smart applications in terms of authentication and safety of access. QRAM is evaluated in term of security factors (e.g., authentication). Computation time of authentication procedures for several IoT applications has become a considerable issue. QRAM aims to reduce computation time consumed to authenticate each QRC. Some authentication techniques still face difficulties when an IoT application requires fast response to users; therefore, QRAM aims to enhance so to meet real-time applications. Thus, QRAM is compared to several competitive methods used to verify QRC in term of computation time. Results confirmed that QRAM is faster than other competitive techniques. Besides, results have shown a high level of complexity in term of decryption time needed to deduce private contents of QRC. QRAM also is robust against unauthorized requests of access.
Data falsification attacks in advanced metering infrastructure Hasventhran Baskaran; Abbas M. Al-Ghaili; Zul- Azri Ibrahim; Fiza Abdul Rahim; Saravanan Muthaiyah; Hairoladenan Kasim
Bulletin of Electrical Engineering and Informatics Vol 10, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i1.2024

Abstract

Smart grids are the cutting-edge electric power systems that make use of the latest digital communication technologies to supply end-user electricity, but with more effective control and can completely fill end user supply and demand. Advanced Metering Infrastructure (AMI), the backbone of smart grids, can be used to provide a range of power applications and services based on AMI data. The increased deployment of smart meters and AMI have attracted attackers to exploit smart grid vulnerabilities and try to take advantage of the AMI and smart meter’s weakness. One of the possible major attacks in the AMI environment is False Data Injection Attack (FDIA). FDIA will try to manipulate the user’s electric consumption by falsified the data supplied by the smart meter value in a smart grid system using additive and deductive attack methods to cause loss to both customers and utility providers. This paper will explore two possible attacks, the additive and deductive data falsification attack and illustrate the taxonomy of attack behaviors that results in additive and deductive attacks. This paper contributes to real smart meter datasets in order to come up with a financial impact to both energy provider and end-user.
Co-Authors Fiza Abdul Rahim Hairoladenan Kasim Hairoladenan Kasim Hasventhran Baskaran Marini Othman Naif Mohammed Al-Hada Saravanan Muthaiyah Wahidah Hashim Zul- Azri Ibrahim