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All Journal Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Leith Hamid Abed
Middle Technical University
Electrical & Electronics Engineering

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COVID-19 detection based on combined domain features Omar Munthir Al Okashi; Ismail Taha Ahmed; Leith Hamid Abed
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp965-973

Abstract

The computed tomography (CT) scan delivers more detailed information and higher judgment accuracy than a chest X-ray, which has a wide range of uses in diagnosing and decision-making to aid medical professionals. This paper proposed a method to detect COVID-19 from CT scan images using the combination of spatial domain and transform domain features. Using the lung segmentation step, the CT image is first processed and segmented, and then various domain features are extracted. From these domain features, the highest combined domain features (CDF) are obtained. Finally, the detection task is completed using random forest (RF) and Naive Bayesian (NB) classifiers. The proposed method is tested using a dataset of CT scan images, and the results are compared to several current techniques. The results showed that our method based on CDF outperforms previous methods, with an overall accuracy of nearly 98%. As can be shown, CDF is the best domain feature to apply for detecting COVID-19.
Financial information security using hybrid encryption technique on multi-cloud architecture Mustafa Noori Rashid; Leith Hamid Abed; Waleed Kareem Awad
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.3967

Abstract

One of the most severe issues in the cloud is security. In comparison to financial data, so it is extremely sensitive and must be safeguarded against unwanted access. We have developed a proposed system based on three different keys. We divided the data into insensitive, sensitive, and highly sensitive data. The data will be saved on a separate cloud server. The proposed system used different keys for encryption and decryption purposes. The elliptic curve cryptography (ECC) based distributed cloud-based secure data storage (DDSPE) approach was proposed to provide secure large data based data protection across the different clouds. With DDSPE technology, the ECC scheme has been used for encryption and decryption purposes. The cloud is used for simulation. The results of the tests reveal that the suggested DDSPE system is safe and saves time regarding data retention and retrieval. To analyze performance, we compared the DDSPE method with advance encryption standard (AES), blowfish, rivest shamir adleman (RSA), security-aware efficient distributed storage (SA-EDS), and attribute based encryption (ABE) based secure distributed storage (ASDSS). In terms of information retention and recovery, our methodology is quite effective because it requires less amount of time as compared to other strategies.
Co-Authors Ismail Taha Ahmed Mustafa Noori Rashid Omar Munthir Al Okashi Waleed Kareem Awad