Nadeem Alherbawi | National University of Malaysia (original) (raw)
Uploads
Papers by Nadeem Alherbawi
From the digital forensics point of view, image forgery is considered as evidence that could prov... more From the digital forensics point of view, image forgery is considered as evidence that could provide a major breakthrough in the investigation process. Additionally, the development of storage device technologies has increased storage space significantly. Thus a digital investigator can be overwhelmed by the amount of data on storage devices that needs to be analysed. In this paper, we propose a model for classifying bulk JPEG images produced by the data carving process or other means into three different classes to solve the problem of identifying forgery quickly and effectively. The first class is JPEG images that contain errors or corrupted data, the second class is JPEG images that contain forged regions, and the third is JPEG images that have no signs of corruption or forgery. To test the proposed model, some experiments were conducted on our own dataset in addition to CASIA V2 image forgery dataset. The experiments covered different types of forgery technique. The results yielded around 88% accuracy rate in the classification process using five different machine learning methods on CASIA V2 dataset. It can be concluded that the proposed model can help investigators to automatically classify JPEG images, which reduce the time needed in the overall digital investigation process.
Data carving is a very important topic in digital investigation and computer forensic. And for th... more Data carving is a very important topic in digital investigation and computer forensic. And for that reason researches are needed to focus on improving data carving techniques to enable digital investigators to retrieve important data and evidences from damaged or corrupted data resources. This study is the result of a systematic literature review which answer three main questions in data carving filed. The Results fall into four main directions. First it shows the need of realistic data sets for tools testing. Secondly, it points to the need of object validation under fragmented data storage. Thirdly, investigating content based validation and its benefits in digital investigation field. Finally, it points to a new direction in data carving such as in-place data carving, bulk extractor and using semantic validation in data carving. Finally, a set of potential areas of interest are pointed out that needs further research and investigation.
Image authenticity is a real issue in the digital forensic field since the wide spread of images ... more Image authenticity is a real issue in the digital forensic field since the wide spread of images and the spread of low-cost image processing software which make it easy to alter images and change them using hard to detect techniques. This study highlights the importance of image authentication and on which level a JPEG image could be altered. Also, it covers some techniques used in making forged images. Finally, it discusses some current techniques used in detecting and localizing forgeries in JPEG images.
Data carving is a very important topic in digital investigation and computer forensic. Researches... more Data carving is a very important topic in digital investigation and computer forensic. Researches are needed to focus on improving data carving techniques to enable digital investigators to retrieve important data and evidences from damaged or corrupted data resources. This paper is the result of a systematic literature review which answer three main questions in data carving filed. The Results fall into four main directions. First it shows the need of realistic data sets for tools testing. Secondly, it points to the need of object validation under fragmented data storage. Thirdly, investigating content based validation and its benefits in digital investigation field. Finally, it points to a new direction for using semantic validation to reduce false positive rates.
From the digital forensics point of view, image forgery is considered as evidence that could prov... more From the digital forensics point of view, image forgery is considered as evidence that could provide a major breakthrough in the investigation process. Additionally, the development of storage device technologies has increased storage space significantly. Thus a digital investigator can be overwhelmed by the amount of data on storage devices that needs to be analysed. In this paper, we propose a model for classifying bulk JPEG images produced by the data carving process or other means into three different classes to solve the problem of identifying forgery quickly and effectively. The first class is JPEG images that contain errors or corrupted data, the second class is JPEG images that contain forged regions, and the third is JPEG images that have no signs of corruption or forgery. To test the proposed model, some experiments were conducted on our own dataset in addition to CASIA V2 image forgery dataset. The experiments covered different types of forgery technique. The results yielded around 88% accuracy rate in the classification process using five different machine learning methods on CASIA V2 dataset. It can be concluded that the proposed model can help investigators to automatically classify JPEG images, which reduce the time needed in the overall digital investigation process.
Data carving is a very important topic in digital investigation and computer forensic. And for th... more Data carving is a very important topic in digital investigation and computer forensic. And for that reason researches are needed to focus on improving data carving techniques to enable digital investigators to retrieve important data and evidences from damaged or corrupted data resources. This study is the result of a systematic literature review which answer three main questions in data carving filed. The Results fall into four main directions. First it shows the need of realistic data sets for tools testing. Secondly, it points to the need of object validation under fragmented data storage. Thirdly, investigating content based validation and its benefits in digital investigation field. Finally, it points to a new direction in data carving such as in-place data carving, bulk extractor and using semantic validation in data carving. Finally, a set of potential areas of interest are pointed out that needs further research and investigation.
Image authenticity is a real issue in the digital forensic field since the wide spread of images ... more Image authenticity is a real issue in the digital forensic field since the wide spread of images and the spread of low-cost image processing software which make it easy to alter images and change them using hard to detect techniques. This study highlights the importance of image authentication and on which level a JPEG image could be altered. Also, it covers some techniques used in making forged images. Finally, it discusses some current techniques used in detecting and localizing forgeries in JPEG images.
Data carving is a very important topic in digital investigation and computer forensic. Researches... more Data carving is a very important topic in digital investigation and computer forensic. Researches are needed to focus on improving data carving techniques to enable digital investigators to retrieve important data and evidences from damaged or corrupted data resources. This paper is the result of a systematic literature review which answer three main questions in data carving filed. The Results fall into four main directions. First it shows the need of realistic data sets for tools testing. Secondly, it points to the need of object validation under fragmented data storage. Thirdly, investigating content based validation and its benefits in digital investigation field. Finally, it points to a new direction for using semantic validation to reduce false positive rates.