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Efficient hardware prototype of ECDSA modules for blockchain applications

10.12928/telkomnika.v19i5.19416
Devika; Amrita Vishwa Vidyapeetham K N , Ramesh; Amrita Vishwa Vidyapeetham Bhakthavatchalu
This paper concentrates on the hardware implementation of efficient and re- configurable elliptic curve digital signature algorithm (ECDSA) that is suitable for verifying transactions in Blockchain related applications. Despite ECDSA architecture being computationally expensive, the usage of a dedicated stand-alone circuit enables speedy execution of arithmetic operations. The prototype put forth supports N-bit elliptic curve cryptography (ECC) group operations, signature generation and verification over a prime field for any elliptic curve. The research proposes new hardware framework for modular multiplication and modular multiplicative inverse which is adopted for group operations involved in ECDSA. Every hardware design offered are simulated using modelsim register transfer logic (RTL) simulator. Field programmable gate array (FPGA) implementation of var- ious modules within ECDSA circuit is compared with equivalent existing techniques that is both hardware and software based to highlight the superiority of the suggested work. The results showcased prove that the designs implemented are both area and speed efficient with faster execution and less resource utilization while maintaining the same level of security. The suggested ECDSA structure could replace the software equivalent of digital signatures in hardware blockchain to thwart software attacks and to provide better data protection.
Volume: 19
Issue: 5
Page: 1636-1647
Publish at: 2021-10-01

Analysis of IPv6 jumbogram packages transmission using jumbo frame in mikrotik-based tunneling

10.11591/ijeecs.v24.i1.pp329-337
Yahya Hidayatullah , Arief Marwanto , Imam Much Ibnu Subroto
The validation and accuracy of internet protocol version 6 (IPv6) performance using jumbo frames is still not perfect, due to peer-to-peer connections testing within the same operating system and between operating systems. Therefore, inaccurate data test results. To mitigated, testing with a wider platform is recommended, a medium-scale network connection is proposed such as metropolitan area networks. In this works, a connection between computer devices connected by three proxy routers are made, with different IPv6 segments on each port. Then each computer device sends traffic data to each other using a traffic-generator application. The first test through three routers without tunnel connection is carried out as the first scenario to compare performance with tunnel-based testing. Three parameters have been used in this test, such as maximum transfer unit (MTU) 1500 bytes, MTU 400 bytes and MTU 9000 bytes. The results of the tests conducted show that the use of jumbo frames using a proxy is less effective, even though it produces a larger throughput when using the MTU 4000, but there is fragmentation in the packet passing through the proxy because the packet passing through the proxy is split into 1500 byte sizes.
Volume: 24
Issue: 1
Page: 329-337
Publish at: 2021-10-01

State regulation of the IoT in the Russian Federation: Fundamentals and challenges

10.11591/ijece.v11i5.pp4542-4549
Zharova Anna , Elin Vladimir
The purpose of this section is to study the problems with implementing technical and legal regulations for the development of public administration functions in the Russian Federation when using the internet of things (IoT). The introduction is based on an analysis of regulatory legal acts and presents the main strategic directions for the development of public administration functions in the Russian federation when using IoT. State reports, scientific literature, a system of technical and legal regulation are analyzed, and the main problems of implementing the IoT that impede the achievement of effective public administration are studied. The Russian practice of using IoT in various economic areas is investigated. Based on an analysis of the mechanisms for ensuring data safety of information technology users in the Russian federation, problems were investigated, such as the collecting data through IoT, including publicly available personal data in order to profile human activities, and creating of a digital twin of a person. The social constraints for introducing distributed registry technologies are users' distrust in the field of data privacy protection and mathematical algorithms that are used to establish trust in a digital environment instead of trusted centralized intermediaries; these problems were also analyzed. The Russian approach was analyzed in comparison to European experience in this field. To ensure information security and the possibility of its distribution, the IoT is revealed.
Volume: 11
Issue: 5
Page: 4542-4549
Publish at: 2021-10-01

Performance evaluation of a new 3D printed dry-contact electrode for EEG signals measurement

10.11591/ijeecs.v24.i1.pp287-294
Aaisha Diaa-Aldeen Abdullah , Auns Q. Al-Neami
Traditional wet silver/silver chloride electrodes are used to record electroencephalography (EEG) signals mainly because of their potential repeatability, excellent signal to noise ratio and biocompatibility. This type of electrode is only suitable for conductive glue, which can irritate the skin and cause injury. In addition, as time goes the conductive gel will be dehydrated so the quality of the EEG signal will decrease. To overcome these problems, 3D printed dry-contact electrodes with multi-pins are designed in this work to measure brain signals without prior preparation or gel application. 3D printed electrodes are made from polylactic acids polymer and coated with suitable materials to enhance the conductivity. Electrode-scalp impedance on human was also measured. To evaluate the dry-contact electrode, EEG measurement are performed in subjects and compared with EEG signals acquired by wet electrode by using linear correlation coefficient. Experimentally results showed that the average electrode-skin impedance change of dry electrode in frontal site (9.42-7.25KΩ) and in occipital site (9.56-8.66KΩ). The correlation coefficient between dry and wet electrodes in frontal site (91.4%) and in occipital site (80%). To conclude, the 3D printed dry-contact electrode can be will promising applied on hairy site and provide a promising solutions for long-term monitoring EEG.
Volume: 24
Issue: 1
Page: 287-294
Publish at: 2021-10-01

Improvement security in e-business systems using hybrid algorithm

10.12928/telkomnika.v19i5.20403
L.; Universitas Musamus Sumaryanti , Dedy Hidayat; Politeknik Negeri Bayuwangi Kusuma , Rosmala; Universitas Musamus Widijastuti , Muhammad Najibulloh; Universitas Nusantara PGRI Kediri Muzaki
E-business security becomes an important issue in the development of technology, to ensure the safety and comfort of transactions in the exchange of information is privacy. This study aims to improve security in e-business systems using a hybrid algorithm that combines two types of keys, namely symmetric and asymmetric keys. Encryption and decryption of messages or information carried by a symmetric key using the simple symmetric key algorithm and asymmetric keys using the Rivest Shamir Adleman (RSA) algorithm. The proposed hybrid algorithm requires a high running time in the decryption process compared to the application of a single algorithm. The level of security is stronger because it implements the process of message encryption techniques with two types of keys simultaneously.
Volume: 19
Issue: 5
Page: 1535-1543
Publish at: 2021-10-01

Artificial neural network technique for improving prediction of credit card default: A stacked sparse autoencoder approach

10.11591/ijece.v11i5.pp4392-4402
Sarah A. Ebiaredoh-Mienye , E. Esenogho , Theo G. Swart
Presently, the use of a credit card has become an integral part of contemporary banking and financial system. Predicting potential credit card defaulters or debtors is a crucial business opportunity for financial institutions. For now, some machine learning methods have been applied to achieve this task. However, with the dynamic and imbalanced nature of credit card default data, it is challenging for classical machine learning algorithms to proffer robust models with optimal performance. Research has shown that the performance of machine learning algorithms can be significantly improved when provided with optimal features. In this paper, we propose an unsupervised feature learning method to improve the performance of various classifiers using a stacked sparse autoencoder (SSAE). The SSAE was optimized to achieve improved performance. The proposed SSAE learned excellent feature representations that were used to train the classifiers. The performance of the proposed approach is compared with an instance where the classifiers were trained using the raw data. Also, a comparison is made with previous scholarly works, and the proposed approach showed superior performance over other methods.
Volume: 11
Issue: 5
Page: 4392-4402
Publish at: 2021-10-01

A maximum entropy classification scheme for phishing detection using parsimonious features

10.12928/telkomnika.v19i5.15981
Emmanuel O.; Landmark University Asani , Adebayo; Hasso Plattner Institute Omotosho , Paul A.; Council for Scientific and Industrial Research-Institute for Scientific and Technological Information (CSIR-INSTI) Danquah , Joyce A.; Landmark University Ayoola , Peace O.; Landmark University Ayegba , Olumide B.; Academic City University College Longe
Over the years, electronic mail (e-mail) has been the target of several malicious attacks. Phishing is one of the most recognizable forms of manipulation aimed at e-mail users and usually, employs social engineering to trick innocent users into supplying sensitive information into an imposter website. Attacks from phishing emails can result in the exposure of confidential information, financial loss, data misuse, and others. This paper presents the implementation of a maximum entropy (ME) classification method for an efficient approach to the identification of phishing emails. Our result showed that maximum entropy with parsimonious feature space gives a better classification precision than both the Naïve Bayes and support vector machine (SVM).
Volume: 19
Issue: 5
Page: 1707-1714
Publish at: 2021-10-01

Hardware implementation of series DC arc fault protection using fast Fourier transform

10.12928/telkomnika.v19i5.20521
Dirhamsyah; Politeknik Pelayaran Surabaya Dirhamsyah , Diana; Politeknik Pelayaran Surabaya Alia , Dimas Okky; Politeknik Elektronika Negeri Surabaya Anggriawan
This paper proposes method of series DC arc fault protection using low cost microcontroller. Series DC arc fault occurs when gap between conductor or wire flows a current. Series DC arc fault can cause fire hazard if do not detected and protected. However, Series DC arc fault is difficult to detected using conventional protection. To detect series DC arc fault accurately using fast Fourier transform (FFT). FFT is used to transform signal in time domain to frequency domain. Series DC arc fault has different characteristic compared by normal current in frequency domain. Therefore, the proposed algorithm for protection of series DC arc fault based on magnitudes of the current in frequency domain. Hardware system is implemented by 100 V DC power supply and DC arc fault generator. Test result is conducted experimentally under varying of load current such as 2 A, 2.5 A, 3 A, 3.5 A, 4 A and 5 A. Experimental testing results show that Series DC arc fault protection has time for trip of 0.48 s, 0.26 s, 1.04 s, 0.68 s, 0.44 s and 0.48, respectively. The fastest time for trip is 0.26 s with current of 2.5 A. Therefore, the proposed algorithm for series DC arc fault protection can operate to trip accurately and have the good performance.
Volume: 19
Issue: 5
Page: 1679-1687
Publish at: 2021-10-01

Robust interference cancellation for differential quadrature phase-shift keying modulation with band limiting and adaptive filter

10.12928/telkomnika.v19i5.19178
Rahmad; Sekolah Tinggi Teknologi Mandala Hidayat , Ahmad; Sekolah Tinggi Teknologi Mandala Sujana , Andrew Ghea; Sekolah Tinggi Teknologi Mandala Mahardika , Herawati; Universitas Kristen Maranatha Herawati , Givy Devira; Sekolah Tinggi Teknologi Mandala Ramady , Ninik Sri; Sekolah Tinggi Teknologi Mandala Lestari
Differential quadrature phase-shift keying (DQPSK) modulation techniques and their variants are widely applied in digital communication, such as for high-speed optical fiber, bluetooth, or satellite communication. In its implementation, DQPSK cannot be separated from the potential harmful interference. In this research, a system model has been made for observation and analysis of the interference cancellation process. Discrete finite-duration impulse response (FIR) filters for band limiting and adaptive filter are the key components of the supporting block for this system model. Robust Simulink results have shown a significant increase in system performance in the existence of these key components. The indication has been shown by the best bit error rate (BER) of 3.3e-05. Constellation and eye pattern diagrams have supported the BER.
Volume: 19
Issue: 5
Page: 1475-1483
Publish at: 2021-10-01

An internet of things ecosystem for planting of coriander (Coriandrum sativum L.)

10.11591/ijece.v11i5.pp4568-4576
Panana Tangwannawit , Kanita Saengkrajang
The internet of things (IoT) is a network of physical devices and is becoming a major area of innovation for computer-based systems. Agriculture is one of the areas which could be improved by utilizing this technology ranging from farming techniques to production efficiency. The objective of this research is to design an IoT to monitor local vegetable (Coriander; Coriandrum sativum L.) growth via sensors (light, humidity, temperature, water level) and combine with an automated watering system. This would provide planters with the ability to monitor field conditions from anywhere at any time. In this research, a group of local vegetables including coriander, cilantro, and dill weed were experimented. The prototype system consists of several smart sensors to accurately monitor the mentioned vegetable growth from seedling stage to a fully grown plant which will ensure the highest production levels from any field environment. Three different types coriander were measured under these parameters: height, trunk width, and leaf width. The result showed that IoT ecosystem for planting different types of coriander could produce effective and efficient plant growth and ready for harvest with a shorter time than conventional method.
Volume: 11
Issue: 5
Page: 4568-4576
Publish at: 2021-10-01

Machine learning for decoding linear block codes: case of multi-class logistic regression model

10.11591/ijeecs.v24.i1.pp538-547
Chemseddine Idrissi Imrane , Nouh Said , Bellfkih El Mehdi , El Kasmi Alaoui Seddiq , Marzak Abdelaziz
Facing the challenge of enormous data sets variety, several machine learning-based algorithms for prediction (e.g, Support vector machine, multi layer perceptron and logistic regression) have been highly proposed and used over the last years in many fields. Error correcting codes (ECCs) are extensively used in practice to protect data against damaged data storage systems and against random errors due to noise effects. In this paper, we will use machine learning methods, especially multi-class logistic regression combined with the famous syndrome decoding algorithm. The main idea behind our decoding method which we call logistic regression decoder (LRDec) is to use the efficient multi-class logistic regression models to find errors from syndromes in linear codes such as bose, ray-chaudhuri and hocquenghem (BCH), and the quadratic residue (QR). Obtained results of the proposed decoder have a significant benefit in terms of bit error rate (BER) for random binary codes. The comparison of our decoder with many competitors proves its power. The proposed decoder has reached a success percentage of 100% for correctable errors in the studied codes.
Volume: 24
Issue: 1
Page: 538-547
Publish at: 2021-10-01

Classification of EEG signals for facial expression and motor execution with deep learning

10.12928/telkomnika.v19i5.19850
Areej Hameed; Al-Nahrain University Al-Anbary , Salih Mahdi; Al-Husain University College Al-Qaraawi
Recently, algorithms of machine learning are widely used with the field of electroencephalography (EEG) brain-computer interfaces (BCI). The preprocessing stage for the EEG signals is performed by applying the principle component analysis (PCA) algorithm to extract the important features and reducing the data redundancy. A model for classifying EEG, time series, signals for facial expression and some motor execution processes had been designed. A neural network of three hidden layers with deep learning classifier had been used in this work. Data of four different subjects were collected by using a 14 channels Emotiv EPOC+ device. EEG dataset samples including ten action classes for the facial expression and some motor execution movements are recorded. A classification results with accuracy range (91.25-95.75%) for the collected samples were obtained with respect to: number of samples for each class, total number of EEG dataset samples and type of activation function within the hidden and the output layer neurons. A time series EEG signal was taken as signal values not as image or histogram, analysed and classified with deep learning to obtain the satisfied results of accuracy.
Volume: 19
Issue: 5
Page: 1588-1593
Publish at: 2021-10-01

Active tremor control in human-like hand tremor using fuzzy logic

10.11591/ijeecs.v24.i1.pp108-115
Hafiz Bin Jamaludin , Azizan As'arry , R. Musab , Khairil Anas Md Rezali , Raja Mohd Kamil Bin Raja Ahmad , Mohd Zarhamdy Bin Md. Zain
Tremoris the vibration in sinusoidal orientation that is experienced regularly by a person with Parkinson’s disease (PD), which disturbs their daily activities. One solution that may be used to counter this tremor effect is by developing an active tremor control system in LabVIEW for linear voice coil actuator (LVCA), where the system uses proportional (P) controller and various types of fuzzy logic controller (FLC) as a hybrid controller to reduce tremor vibration. From this research, it can be concluded that the best controller for tremor reduction is the P+FLC 1st set of rules, compared to P+FLC 2nd set of rules, and P controller only, with the highest percentage of 88.39% of tremor reduction with the actual tremor vibration of PD patients as the reference result. The P+FLC 2nd set of rules has the highest percentage of tremor reduction with a value of 86.81%, whereas P controller only has the highest tremor reduction percentage of 67.10%. This percentage of tremor reduction is based on the power spectral density (PSD) values, in which it represents the intensity of the tremor vibration. This experimental study can be used as an initial step for researchers and engineers to design and develop an anti-tremor device in the future.
Volume: 24
Issue: 1
Page: 108-115
Publish at: 2021-10-01

Detailed modelling and simulation of single-phase transformers for research and educational purposes

10.11591/ijeecs.v24.i1.pp37-49
Saif Sabah Sami , Mazin T. Muhssin , Zeyad Assi Obaid , Ali N. Hussain
COVID-19 pandemic, despite its devastating impact, accelerated the shift to e-learning in higher education. Particularly in the electrical machines courses, that often include laboratory experiments. However, no detailed models of transformers, developed in Simulink/MATLAB®, were reported in the literature. Hence, in this paper, a virtual laboratory consists of models of single-phase transformers was built for the first time. The proposed models are easy to use and modify, and allow all machines’ parameters to be altered for students to replicate easily to support and enhance the learning process of electrical machines courses. Consequently, the developed models are effective tools for educational and research purposes. Dynamic models of single-phase, two-winding, transformers and step-up and step-down auto-transformers were developed using Simulink/MATLAB®. Two different approaches for modelling were proposed, the block diagram representation and Simscape based models. The two modelling methods were validated against the built-in transformer model. The developed models have been successfully integrated into electrical engineering courses at Middle Technical University, Baghdad, Iraq. Therefore, all developed models are freely available online at a dedicated repository.
Volume: 24
Issue: 1
Page: 37-49
Publish at: 2021-10-01

Enabling seamless communication over several IoT messaging protocols in OpenFlow network

10.12928/telkomnika.v19i5.20412
Fauzi Dwi Setiawan; Universitas Muhammadiyah Malang Sumadi , Agus Eko; Universitas Muhammadiyah Malang Minarno , Lailis; Universitas Muhammadiyah Malang Syafa’ah , Muhammad; Universitas Muhammadiyah Malang Irfan
The most prominent protocols for data transfer in internet of things (IoT) are message queuing telemetry transport (MQTT) and constrained application protocol (CoAP). The existing clients from both sides are unable to communicate directly because of the packet’s header structure difference in application and transport layer. In response, this paper aims to develop a bidirectional conversion server used to translate the specified messaging protocol interchangeably in the OpenFlow network and transmit the converted packet from both sides. The conversion server integrated the MQTT subscriber and CoAP POST object for converting the MQTT message into CoAP data. Similarly, the CoAP-MQTT translation was processed by CoAP GET and MQTT publisher object. The research was evaluated by analysing the round trip time (RTT) value, conversion delay, and power consumption. The RTT value for MQTT-CoAP required 0.5 s while the CoAP-MQTT was accumulated in 0.1 s for single-packet transmission. In addition, the SDN controller and the conversion server only consumed less than 1% central processing unit (CPU) usage during the experiment. The result indicated that the proposed conversion server could handle the translation even though there was an overwhelming request from the clients.
Volume: 19
Issue: 5
Page: 1544-1552
Publish at: 2021-10-01
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