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29,939 Article Results

Development of a new system to detect denial of service attack using machine learning classification

10.11591/ijeecs.v23.i2.pp1068-1072
Mohammad M. Rasheed , Alaa K. Faieq , Ahmed A. Hashim
Denial of service (DoS) attack is among the most significant types of attacks in cyber security. The objective of this research is to introduce a new algorithm to distinguish normal service requests from the denial of service attacks. Our proposed approach can detect the denial of service attacks by the analysis of the packets sent from the client to the server, which depend on machine learning. Our algorithm collects different datasets of benign network traffic and different types of denial of service attacks, such as DDoS, DoS Hulk, DoS GoldenEye, DoS Slowhttptest and DoS Slowloris, that were used for training. Moreover, our algorithm monitors the network every specific time to find denial of service attack. Our results show that the algorithm can detect the benign cases and distinguish the types of denial of service attack. Furthermore, the results could achieve 99 percentage of correct classification of all selected cases.
Volume: 23
Issue: 2
Page: 1068-1072
Publish at: 2021-08-01

Application of big data for distribution and consumption of power

10.12928/telkomnika.v19i4.16285
Olagunju; Federal University Mukaila , Adeniyi Abidemi; Landmark University Emmanuel , Ogundokun Roseline; Landmark University Oluwaseun , Ojo Olufemi; Landmark University Samuel , Kolawole Paul; University of Ilorin Oluwatoba
The exponentially growing and tremendous collection of data stored in the power sector, combined with the need for data analysis, has produced an urgent need for powerful tools to extract hidden data as to effectively distribute the power for proper consumption for the household. This research work was embarked on to show the business value of big data analytics in Energy and utilities with a focus on how analytics can help solve problems of inefficiency and wastages in electricity generation, production and distribution and how raw energy datasets can be converted into insights that can be used by energy policy makers to make major business decisions. To explicitly show how raw data can be turned into insights, the study deploys the use of the Hadoop on Hortonworks’ open-source apache-Hive licensed data warehousing framework run on a windows operating system to turn raw datasets (in excel formats converted to .csv format) gotten from the prepaid meters of 196,000 consumers (households and businesses) in 11 business units of Ikeja Electricity Distribution Company (IKEDC, Nigeria) to analyze the distribution and consumption of power.
Volume: 19
Issue: 4
Page: 1090-1099
Publish at: 2021-08-01

Two-step artificial neural network to estimate the solar radiation at Java Island

10.11591/ijece.v11i4.pp3559-3566
Adi Kurniawan , Eiji Shintaku
The availability of information about solar radiation characteristics, particularly solar radiation predictions, is important for efficiently designing solar energy systems. Solar radiation information is not available in Indonesia because official measurements have not been conducted by the Indonesian Meteorological, Climatology, and Geophysical Agency (BMKG). In this study, a new two-step artificial neural network (ANN) is proposed to estimate both the daily average and hourly solar radiation at Java Island, Indonesia. The input parameters for the daily average solar radiation estimation are the location and time required, along with five selected monthly meteorological parameters that BMKG predicts for the subsequent month. The selected meteorological parameters are temperatures, relative humidity, and precipitation. The estimated daily average solar radiation is then used as the input parameter of the hourly solar radiation estimation along with the local time and location. The ANN training was conducted using two years of data, 2018 and 2019, from Surabaya and Jakarta, while the validation was performed in the same cities for January through July 2020. The accuracy of the proposed method is comparable to previous studies with an average R2 of 98.70% for the daily average solar radiation estimate and 97.44% for the hourly solar radiation estimate.
Volume: 11
Issue: 4
Page: 3559-3566
Publish at: 2021-08-01

A review of intelligent methods for condition monitoring and fault diagnosis of stator and rotor faults of induction machines

10.11591/ijece.v11i4.pp2820-2829
Omar Alshorman , Ahmad Alshorman
Nowadays, induction motor (IM) is extensively used in industry, including mechanical and electrical applications. However, three main types of IM faults have been discussed in the literature, bearing, stator, and rotor. Importantly, stator and rotor faults represent approximately 50%. Traditional condition monitoring (CM) and fault diagnosis (FD) methods require a high processing cost and much experience knowledge. To tackle this challenge, artificial intelligent (AI) based CM and FD techniques are extensively developed. However, there have been many review research papers for intelligent CM and FD machine learning methods of rolling elements bearings of IM in the literature. Whereas there is a lack in the literature, and there are not many review papers for both stator and rotor intelligent CM and FD. Thus, the proposed study's main contribution is in reviewing the CM and FD of IM, especially for the stator and the rotor, based on AI methods. The paper also provides discussions on the main challenges and possible future works.
Volume: 11
Issue: 4
Page: 2820-2829
Publish at: 2021-08-01

An optimized power allocation algorithm for cognitive radio NOMA communication

10.12928/telkomnika.v19i4.20366
Madan H.; REVA University T. , P. I.; REVA University Basarkod
The primary objective of cognitive radio network is to effectively utilize the unused spectrum bands. In cognitive radio networks, spectrum sharing between primary and secondary users is accomplished using either underlay or interweave cognitive radio approach. Non orthogonal multiple access (NOMA) is the proven technology in the present wireless developments, which allows the coexistence of multiple users in the same orthogonal block. The new paradigm cognitive radio NOMA (CR-NOMA) is one of the potential solutions to fulfill the demands of future wireless communication. This paper emphasizes on practical implementation of NOMA in cognitive radio networks to enhance the spectral efficiency. The goal is to increase the throughput of the secondary users satisfying the quality of service (QOS) requirements of primary users. To achieve this, we have presented the optimized power allocation strategy for underlay downlink scenario to support the simultaneous transmission of primary and secondary users. Furthermore, we have proposed QOS based power allocation scheme for CR-NOMA interweave model to support the coexistence of multiple secondary networks. Also, the changes adopted in implementing superposition coding (SC) and successive interference cancellation (SIC) for CR-NOMA are highlighted. Finally, simulation results validate the mathematical expressions that are derived for power allocation coefficient and outage probability.
Volume: 19
Issue: 4
Page: 1066-1077
Publish at: 2021-08-01

Implementing optimization of PID controller for DC motor speed control

10.11591/ijeecs.v23.i2.pp657-664
Yasir G. Rashid , Ahmed Mohammed Abdul Hussain
The point of this paper presents an optimization technique which is flexible and quick tuning by using a genetic algorithm (GA) to obtain the optimum proportional-integral-derivative (PID) parameters for speed control of aseparately excited DC motor as a benchmark for performance analysis. The optimization method is used for searching for the proper value of PID parameters. The speed controller of DC motor using PID tuning method sincludes three types: MATALB PID tunner app., modified Ziegler-Nicholsmethod and genetic algorithm (GA). PID controller parameters (Kp, Ki and Kd) will be obtained by GA to produce optimal performance for the DC motor control system. Simulation results indicate that the tuning method of PID by using a genetic algorithm is shown to create the finest result in system performance such as settling time, rise time, percentage of overshoot and steady state error. The MATLAB/Simulink software is used to model and simulate the proposed DC motor controller system.
Volume: 23
Issue: 2
Page: 657-664
Publish at: 2021-08-01

Performance analysis of encryption and decryption algorithm

10.11591/ijeecs.v23.i2.pp1030-1038
Pronika Pronika , S. S. Tyagi
In this tumultuous 21st century, we are surrounding by lots of applications such as social media websites all over the internet or this era can also define as digital era in which everything is accessible over the internet. There are billions of internet users all over the world and they share their information over the same and because of this lots of people intentionally trying to steal the confidential data of other people, so it is always advisable to share and store data in encrypted form. In this paper, we discuss different encryption and decryption algorithms and compare them with respect to time take by these algorithms for encrypting and decrypting different sizes of files.
Volume: 23
Issue: 2
Page: 1030-1038
Publish at: 2021-08-01

Towards developing a pocket therapist: an intelligent adaptive psychological support chatbot against mental health disorders in a pandemic situation

10.11591/ijeecs.v23.i2.pp1200-1211
Intissar Salhi , Kamal El Guemmat , Mohammed Qbadou , Khalifa Mansouri
Nowadays with COVID-19 ongoing epidemic outbreak, containment for weeks was one of the most effective measures adopted to deal with the spread of the virus until a vaccine could be efficient. Over that period, increased anxiety, depression, suicide attempts and post-traumatic stress disorder are accumulated. Several studies referred to the need of using chatbots, which recognizes human emotions in such pandemic contexts. More recently, numerous research papers improved the ability of artificial intelligence methods to recognize human emotion. However, they are still limited. The aim of this paper is the development of a chatbot against the disturbing psychic consequences of the pandemic, taking human emotion recognition into account. The object is to help people; especially students; suffering from mental disorders, by progressively understanding the reasonsbehind them. This innovative chatbot was developed by using the natural language processing model of deep learning. An advanced model of deep learning has been elaborated the intention for people and that to help them to regulate their mood and to reduce distortion of negative thoughts, that why a collection of a new database was done. The sequence-to-sequence model encoder and decoder consist of Long short-term memory cells and it is defined with the bi-directional dynamic recurrent neural network packets.
Volume: 23
Issue: 2
Page: 1200-1211
Publish at: 2021-08-01

Proposed different relay selection schemes for improving the performance of cooperative wireless networks

10.12928/telkomnika.v19i4.18327
Dheyaa Jasim; University of Baghdad Kadhim , Saba Qasim; University of Baghdad Jabbar
Relay selection is a new method currently used to develop and improve cooperative wireless networks. One of the main advantages of this new technology is that it can achieve cooperative diversity gain without installing multiple antennas in the transmitter or receiver. Relay selection algorithms can be used to select one node to become a relay node from a set of N candidate relays with optimization criteria as the outage probability or frame error rate. The selection process is preferable to operate in a distributed fashion and offers only reasonable costs in terms of manufacturing complexity and flexible handling over wireless cooperative networks. In this work, different relay selection schemes are proposed to enhance the cooperative wireless networks in terms of different approaches including: 1) Relay selection-based destination feedback scheme, 2) Relay selection based a ready-to-send/clear-to-send (RTS/CTS) messages scheme, 3) Relay selection-based identification messages (IDM) table scheme, and 4) Relay selection-based relay power consuming scheme. The experimental results via suggested case study show that the performance of overall cooperative network is enhanced in terms of increasing throughput, energy saving (efficiency maximization), blocking reduction and outage reduction (PER minimization).
Volume: 19
Issue: 4
Page: 1107-1117
Publish at: 2021-08-01

IoT-based weather station with air quality measurement using ESP32 for environmental aerial condition study

10.12928/telkomnika.v19i4.18990
Prisma; Universitas Airlangga Megantoro , Shofa Aulia; Universitas Airlangga Aldhama , Gunawan Setia; Universitas Airlangga Prihandana , P.; SRM Institute of Science & Technology Vigneshwaran
This article discusses the design of a weather station device that also functions to measure the concentration of gases in the air. This real-time telemetry device based on the internet of things (IoT) uses the ESP32 board to process measurement data. Some of the weather parameters measured are wind speed, wind direction, humidity, ambient air temperature, air pressure, rainfall, and ultraviolet (UV) index. Meanwhile, the gas concentration parameters in the air are ozone, hydrogen, methane, ammonia, carbon monoxide, and carbon dioxide. The readings from all sensors are processed by the ESP32 board and uploaded to the server. Then a client device will receive the data set and then processed, displayed on the monitor, and stored in the form of a text file. Furthermore, the monitor and the data are used for the analysis of the surrounding air quality and weather conditions.
Volume: 19
Issue: 4
Page: 1316-1325
Publish at: 2021-08-01

Text classification model for methamphetamine-related tweets in Southeast Asia using dual data preprocessing techniques

10.11591/ijece.v11i4.pp3617-3628
Narongsak Chayangkoon , Anongnart Srivihok
Methamphetamine addiction is a prominent problem in Southeast Asia. Drug addicts often discuss illegal activities on popular social networking services. These individuals spread messages on social media as a means of both buying and selling drugs online. This paper proposes a model, the “text classification model of methamphetamine tweets in Southeast Asia” (TMTA), to identify whether a tweet from Southeast Asia is related to methamphetamine abuse. The research addresses the weakness of bag of words (BoW) by introducing BoW and Word2Vec feature selection (BWF) techniques. A domain-based feature selection method was performed using the BoW dataset and Word2Vec. The BWF dataset provided a smaller number of features than the BoW and TF–IDF dataset. We experimented with three candidate classifiers: Support vector machine (SVM), decision tree (J48) and naive bayes (NB). We found that the J48 classifier with the BWF dataset provided the best performance for the TMTA in terms of accuracy (0.815), F-measure (0.818), Kappa (0.528), Matthews correlation coefficient (0.529) and high area under the ROC Curve (0.763). Moreover, TMTA provided the lowest runtime (3.480 seconds) using the J48 with the BWF dataset.
Volume: 11
Issue: 4
Page: 3617-3628
Publish at: 2021-08-01

Comparison of levels and fusion approaches for multimodal biometrics

10.11591/ijeecs.v23.i2.pp791-801
S. Sujana , V. S. K. Reddy
The biometric-based authentication system occupies maximal space in the field of security administration. Biometric applications are swiftly accelerating in day-to-day life such as computer login, smart homes, online banking, hospitals, border areas, industries, forensics, e-voting attendance system and investigation of crime. A reliable and accurate recognition body can be achieved with multimodal biometric methodologies. In this paper, we discuss starting with an introduction to biometric systems followed by their classification, and advantages as well as disadvantages. In today’s world, most of the systems are unimodal biometrics having a lot of limitations to overcome those multimodal biometrics comes in to picture. In this paper we have discussed comprehensive representation on the system of multimodal biometric, various modes of undertakings, the significance of information fusion, a different section is allotted on the various possible levels of fusion involving sensor-level, feature-level, score-level, and decision -level as well as different rules of fusion.
Volume: 23
Issue: 2
Page: 791-801
Publish at: 2021-08-01

IoT-based air quality monitoring systems for smart cities: A systematic mapping study

10.11591/ijece.v11i4.pp3470-3482
Danny Munera , Diana P. Tobon V. , Johnny Aguirre , Natalia Gaviria Gomez
The increased level of air pollution in big cities has become a major concern for several organizations and authorities because of the risk it represents to human health. In this context, the technology has become a very useful tool in the contamination monitoring and the possible mitigation of its impact. Particularly, there are different proposals using the internet of things (IoT) paradigm that use interconnected sensors in order to measure different pollutants. In this paper, we develop a systematic mapping study defined by a five-step methodology to identify and analyze the research status in terms of IoT-based air pollution monitoring systems for smart cities. The study includes 55 proposals, some of which have been implemented in a real environment. We analyze and compare these proposals in terms of different parameters defined in the mapping and highlight some challenges for air quality monitoring systems implementation into the smart city context.
Volume: 11
Issue: 4
Page: 3470-3482
Publish at: 2021-08-01

Design and implementation of a secured SDN system based on hybrid encrypted algorithms

10.12928/telkomnika.v19i4.18721
Samir; Mustansiriyah University Ghaly , Mahmood Zaki; Mustansiriyah University Abdullah
Software defined network suggests centralizing network knowledge in one network portion by separating the routing (control plane) mechanism from the transmission network packet operation (data plane). The control plane is composed of one, two or more controllers which are considered as software-defined networking (SDN) network brain where the real intelligence is incorporated. The process of separating the control unit from the data unit led to a problem related to poor security of data sent in the network, so solutions to these problems had to be found. In this paper, address this problem by implementing robust algorithms to encrypt information, based on advanced encryption standard (AES), Rivest–Shamir–Adleman (RSA), and hybrid encryption algorithms to guarantee data protection and authenticity. The results showed that the hybrid coding method is better in terms of security and improved time (faster than RSA alone) by applying several scenarios in the SDN network to a set of encrypted files.
Volume: 19
Issue: 4
Page: 1118-1125
Publish at: 2021-08-01

High performance binary LDPC-coded OFDM systems over indoor PLC channels

10.12928/telkomnika.v19i4.20401
Nejwa El; Moulay Ismail University Maammar , Seddik; Moulay Ismail University Bri , Jaouad; Moulay Ismail University Foshi , Mohammed Amine; Moulay Ismail University Ihedrane , El Fadl; Mohamed 5 University Rabat Adiba
Power line communication (PLC) technology is actually among the most renowned technologies for home environments due to their low-cost installation opportunities. In this study, the bit error rate (BER) performances of binary low-density parity check (LDPC) coded orthogonal frequency-division multiplexing (OFDM) systems have been considered over indoor PLC channels. Performances comparison of diverse soft and hard decision LDPC decoder schemes such as Min-Sum (MS), weighted bit flipping (WBF), gradient descent bit-flip (GDBF), noisy gradient descent bit-flip (NGDBF) and its few variants including the single-bit NGDBF (S-NGDBF), multi-bit NGDBF (M-NGDBF) and smoothed-multi-bit NGDBF (SM-NGDBF) decoders were examined in the modeled network. To evaluate the BER performance analyses three different PLC channel scenarios were generated by using new and more realistic PLC channel model proposal were also employed. All of the simulations performed in Canete’s PLC channel model showed that remarkable performance improvement can be achieved by using short-length LDPC codes. Especially, the improvements are striking when the MS or SM-NGDBF decoding algorithms are employed on the receiver side.
Volume: 19
Issue: 4
Page: 1388-1395
Publish at: 2021-08-01
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