Erhan Akbal

Work place: Digital Forensics Engineering, Technology Faculty, Firat University, Elazig, Turkey



Research Interests: Computer systems and computational processes, Computer Architecture and Organization, Application Security, Hardware Security, Information Security, Intrusion Detection System, Network Security, Information-Theoretic Security


Erhan AKBAL is currently working as an assistant professor at Digital Forensics Engineering Department of Firat University, He received his Ph.D. degree in electrical and electronics engineering in 2012, the M.S. degree in computer engineering in 2007, from Firat University, Turkey. His research interests include computer network security, wireless sensor network, intrusion detection and digital forensics.

Author Articles
Discrete Complex Fuzzy Transform based Face Image Recognition Method

By Turker Tuncer Sengul Dogan Erhan Akbal

DOI:, Pub. Date: 8 Apr. 2019

In this paper, a novel discrete complex fuzzy transform (DCFT) and the proposed DCFT based facial image recognition method is presented. The presented DCFT consists of histogram extraction, peak points of histogram calculation and images construction. 3 real and 3 complex images are constructed using DCFT. Also, 3 angular images and 3 vector image are calculated using the real and complex images. To create real and complex images, polynomial and smith fuzzy sets are used in this paper. Briefly, 12 image are constructed using DCFT. In order to demonstrate effect of the proposed DCFT, face images data sets and local binary pattern (LBP) are used to create facial image recognition method. In this method, LBP is applied on the each DCFT image and 12 x 256 size of feature are extracted. Also, maximum pooling is applied on this feature set to obtain 256 size of feature. In the classification phase, support vector machine (SVM) and k nearest neighborhood (KNN) classifiers are used. The comparisons clearly demonstrate that the proposed DCFT is increased facial image recognition capability.

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Forensics Image Acquisition Process of Digital Evidence

By Erhan Akbal Sengul Dogan

DOI:, Pub. Date: 8 May 2018

For solving the crimes committed on digital materials, they have to be copied. An evidence must be copied properly in valid methods that provide legal availability. Otherwise, the material cannot be used as an evidence. Image acquisition of the materials from the crime scene by using the proper hardware and software tools makes the obtained data legal evidence. Choosing the proper format and verification function when image acquisition affects the steps in the research process. For this purpose, investigators use hardware and software tools. Hardware tools assure the integrity and trueness of the image through write-protected method. As for software tools, they provide usage of certain write-protect hardware tools or acquisition of the disks that are directly linked to a computer. Image acquisition through write-protect hardware tools assures them the feature of forensic copy. Image acquisition only through software tools do not ensure the forensic copy feature. During the image acquisition process, different formats like E01, AFF, DD can be chosen. In order to provide the integrity and trueness of the copy, hash values have to be calculated using verification functions like SHA and MD series. In this study, image acquisition process through hardware-software are shown. Hardware acquisition of a 200 GB capacity hard disk is made through Tableau TD3 and CRU Ditto. The images of the same storage are taken through Tableau, CRU and RTX USB bridge and through FTK imager and Forensic Imager; then comparative performance assessment results are presented.

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