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All Journal International Journal of Electrical and Computer Engineering TELKOMNIKA (Telecommunication Computing Electronics and Control)
Muayad Sadik Croock
University of Technology-Iraq
Computer Science & IT Electrical & Electronics Engineering

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Software engineering based secured E-payment system Muayad Sadik Croock; Rawan Ali Taaban
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4413-4422

Abstract

Nowadays, the E-payment systems have been considered to be the safe way of money transfer in most of modern institutes and companies. Moreover, the security is important side of these systems to ensure that the money transfer is done safely. Software engineering techniques are used for guaranteeing the applying of security and privacy of such systems. In this paper, a secure E-payment system is proposed based on software engineering model and neural network technology. This system uses different proposed algorithms for applying authentication to the devices of users as mobile application. They are used to control the key management in the system. It uses the neural network back-propagation method for ensuring the security of generated keys that have sufficient random levels. The proposed system is tested over numerous cases and the obtained results show an efficient performance in terms of security and money transfer. Moreover, the generated keys are tested according to NIST standards.
Software engineering based self-checking process for cyber security system in VANET Muntadher Naeem Yasir; Muayad Sadik Croock
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1328.568 KB) | DOI: 10.11591/ijece.v10i6.pp5844-5852

Abstract

Newly, the cyber security of Vehicle Ad hoc Network (VANET) includes two practicable: Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I), that have been considered due to importance. It has become possible to keep pace with the development in the world. The people safety is a priority in the development of technology in general and particular in of VANET for police vehicles. In this paper, we propose a software engineering based self-checking process to ensure the high redundancy of the generated keys. These keys are used in underlying cyber security system for VANET. The proposed self-checking process emploies a set of NIST tests including frequency, block and runs as a threshold for accepting the generated keys. The introduced cyber security system includes three levels: Firstly, the registration phase that asks vehicles to register in the system, in which the network excludes the unregistered ones. In this phase, the proposed software engineeringbased self-checking process is adopted. Secondly, the authentication phase that checks of the vehicles after the registration phase. Thirdly, the proposed system that is able to detect the DOS attack. The obtained results show the efficient performance of the proposed system in managing the security of the VANET network. The self-checking process increased the randomness of the generated keys, in which the security factor is increased.
Early detection of breast cancer using mammography images and software engineering process Muayad Sadik Croock; Saja Dhyaa Khuder; Ayad Esho Korial; Sahar Salman Mahmood
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.v18i4.14718

Abstract

The breast cancer has affected a wide region of women as a particular case. Therefore, different researchers have focused on the early detection of this disease to overcome it in efficient way. In this paper, an early breast cancer detection system has been proposed based on mammography images. The proposed system adopts deep-learning technique to increase the accuracy of detection. The convolutional neural network (CNN) model is considered for preparing the datasets of training and test. It is important to note that the software engineering process model has been adopted in constructing the proposed algorithm. This is to increase the reliably, flexibility and extendibility of the system. The user interfaces of the system are designed as a website used at country side general purpose (GP) health centers for early detection to the disease under lacking in specialist medical staff. The obtained results show the efficiency of the proposed system in terms of accuracy up to more than 90% and decrease the efforts of medical staff as well as helping the patients. As a conclusion, the proposed system can help patients by early detecting the breast cancer at far places from hospital and referring them to nearest specialist center.
Software engineering model based smart indoor localization system using deep-learning Zainab Mohammed Resan; Muayad Sadik Croock
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.v18i4.14318

Abstract

During the last few years, the allocation of objects or persons inside a specific building is highly required. It is well known that the global positioning system (GPS) cannot be adopted in indoor environment due to the lack of signals. Therefore, it is important to discover a new way that works inside. The proposed system uses the deep learning techniques to classify places based on capturing images. The proposed system contains two parts: software part and hardware part. The software part is built based on software engineering model to increase the reliability, flexibility, and scalability. In addition, this part, the dataset is collected using the Raspberry Pi III camera as training and validating data set. This dataset is used as an input to the proposed deep learning model. In the hardware part, Raspberry Pi III is used for loading the proposed model and producing prediction results and a camera that is used to collect the images dataset. Two wheels’ car is adopted as an object for introducing indoor localization project. The obtained training accuracy is 99.6% for training dataset and 100% for validating dataset.
A developed GPS trajectories data management system for predicting tourists' POI Rula Amjed Hamid; Muayad Sadik Croock
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 1: February 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i1.13006

Abstract

One of the areas that have challenges in the use of internet of things (IoT) is the field of tourism and travel. The issue here is how to employ this technology to serve the tourism and managing the produced data. This work is focus on the use of tourists' trajectories that are collected from global positioning system (GPS) mobile sensors as a source of information. The aim of work is to predict preferred tourism places for tourists by tracking tourists' behavior to extract the tourism places that have been visited by such tourists. Density based clustering algorithm is mainly used to extract stay points and point of interest (POI). By projecting GPS location (for user and places) on the Google map, the type and name of places favored by the tourists are determined. K nearest neighbor (KNN) algorithm with haversine distance has been adopted to find the nearest places for tourists. The evaluation of the obtained results shows superior and satisfactory performance that can reach the objective behind this work.
Co-Authors Ayad Esho Korial Muntadher Naeem Yasir Rawan Ali Taaban Rula Amjed Hamid Sahar Salman Mahmood Saja Dhyaa Khuder Zainab Mohammed Resan