Content-Based Feature Extraction and Extreme Learning Machine for Optimizing File Cluster Types Identification

Ali, Rabei Raad; Al-Dayyeni, Wisam Subhi; Gunasekaran, Saraswathy Shamini; Mostafa, Salama A.; Abdulkader, Ayad Hussain; Rachmawanto, Eko Hari

doi:10.1007/978-3-030-98015-3_21

Cited by 7 publications

(4 citation statements)

References 18 publications

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“…Current studies in Digital Forensic investigation concentrate on developing file recovery methods with missing fragments or file system information. Mainly, these studies focus on the JPEG image format that is widely used due to its sophisticated characteristics [2][3][4][5][6][7]. Subsequently, various JPEG image recovery methods are proposed in the literature.…”

Section: Related Workmentioning

confidence: 99%

“…Joint Photographic Experts Group (JPEG) is a standard image file format having less structured contents that make its retrieval "recovery" possible when the file system is missing [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16]. Since many JPEG images on laptops, tablets, and smartphones are valuable, these images are exposed accidentally to deformation or deletion for many reasons, including storage damage and deliberate destruction.…”

Section: Introductionmentioning

confidence: 99%

“…A fragmented JPEG image is an image that has been split into more than one part where all parts are stored in non-sequential locations on a disk drive [4]. Although the fragmented JPEG image percentage is relatively small, these are typical JPEG images necessary for Digital Forensic investigation [5]. JPEG file recovery generally has three main procedures: identification, verification, and reassembly [6].…”

Section: Introductionmentioning

confidence: 99%

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A Meta-Heuristic Method for Reassemble Bifragmented Intertwined JPEG Image Files in Digital Forensic Investigation

Ali,

Mohamad,

Mostafa

et al. 2023

IEEE Access

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Traditional image recovery from corrupted file systems plays a significant role in Digital Forensics investigation. The images are mainly considered objective court evidence. Since the JPEG image format is less structured than other image formats (e.g., BMP, PNG, GIF, and TIFF), its recovery is more challenging. The paper's main objective is to apply a metaheuristic optimization algorithm with similarity metric to recover Bifragmented intertwined JPEG images. We propose a new method known as Meta-Heuristic Reassemble Images (MHRI) for forensic recovery of Bifragmented intertwined JPEG images in the scan area, where all the fragments are in a linear order. The contribution of this paper lies in the following key components composing the MHRI method: (i) a Restart marker to remove some strange blocks from the scan area; (ii) a Coherence of Euclidean Distance metric (CoED m ) to detect the fragmentation point of intertwined JPEG image; and (iii) a Genetic Algorithm with cost function to predict if every two blocks are sequenced in the same image that searches for the best reassembly solution among the existing solutions. The MHRI method is implemented using MATLAB and tested using a combined dataset of 31 JPEG images. The MHRI process can fully recover all the Bifragmented intertwined JPEG images and 48.4% of all the JPEG images, which comparably performs better than similar methods. INDEX TERMSDigital forensic; JPEG image; image recovery, meta-heuristic, genetic algorithm; reassemble images; coherence of Euclidean distance; restart marker; DFRWS datasets.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Meta-Heuristic Method for Reassemble Bifragmented Intertwined JPEG Image Files in Digital Forensic Investigation

Ali,

Mohamad,

Mostafa

et al. 2023

IEEE Access

Self Cite

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“…In this routing strategy, among multiple cars, one node in the cluster area is designated as a cluster (CH); the other nodes, referred to as cluster members, are handled by the other nodes. A border node is located between the communication ranges of two or more clusters [25].…”

Section: Clustering-based Routingmentioning

confidence: 99%

A Comparative Performance Evaluation of GRP and MDORA Protocols for VANET

Mohammed¹,

Mansor²,

Hock³

2023

IJETAE

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The vehicular ad hoc network (VANET) is a kind of mobile ad hoc network (MANET). VANET is a wireless communication network that offers vehicle-to-vehicle (V2V) or vehicle-to-infrastructure (V2I) dialogue. They have a dynamic topology and are often ad hoc networks, meaning they lack communication management and control infrastructure. Vehicle communication must be used for comfort and safety. The effectiveness of a communication link is determined by how successfully routing protocols are implemented in the network. This work aims to compare the performance of the geographical routing protocol (GRP) with that of the maximum distance on-demand routing algorithm (MDORA). Packet delivery ratio, communication overhead, and end-to-end delay are the performance parameters evaluated in this study.

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An Application of Multilayer Perceptron for the Prediction of River Water Quality

Ghazali,

Fuzi,

Mostafa

et al. 2023

Lecture Notes in Networks and Systems

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Content-Based Feature Extraction and Extreme Learning Machine for Optimizing File Cluster Types Identification

Cited by 7 publications

References 18 publications

A Meta-Heuristic Method for Reassemble Bifragmented Intertwined JPEG Image Files in Digital Forensic Investigation

A Meta-Heuristic Method for Reassemble Bifragmented Intertwined JPEG Image Files in Digital Forensic Investigation

A Comparative Performance Evaluation of GRP and MDORA Protocols for VANET

An Application of Multilayer Perceptron for the Prediction of River Water Quality

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