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Spam image email filtering using K-NN and SVM Yasmine Khalid Zamil; Suhad A. Ali; Mohammed Abdullah Naser
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 1: February 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1124.041 KB) | DOI: 10.11591/ijece.v9i1.pp245-254

Abstract

The developing utilization of web has advanced a simple and quick method for e-correspondence. The outstanding case for this is e-mail. Presently days sending and accepting email as a method for correspondence is prominently utilized. Be that as it may, at that point there stand up an issue in particular, Spam mails. Spam sends are the messages send by some obscure sender just to hamper the improvement of Internet e.g. Advertisement and many more.  Spammers introduced the new technique of embedding the spam mails in the attached image in the mail. In this paper, we proposed a method based on combination of SVM and KNN. SVM tend to set aside a long opportunity to prepare with an expansive information set. On the off chance that "excess" examples are recognized and erased in pre-handling, the preparation time could be diminished fundamentally. We propose a k-nearest neighbor (k-NN) based example determination strategy. The strategy tries to select the examples that are close to the choice limit and that are effectively named. The fundamental thought is to discover close neighbors to a question test and prepare a nearby SVM that jelly the separation work on the gathering of neighbors. Our experimental studies based on a public available dataset (Dredze) show that results are improved to approximately 98%.
Enhancing of coverless image steganography capacity based on image block features Hadeel Talib Mangi; Suhad A. Ali; Majid Jabbar Jawad
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 6: December 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i6.24816

Abstract

The idea of coverless information hiding has seen a great deal of development since it was initially introduced due to its effectiveness in defeating steganalysis tools. However, the capacity for general coverless information hiding methods to conceal information is limited, as well as no previous methods worked at the other requirements such as robustness. In this paper, a coverless image steganography (CIS) method for increasing capacity is proposed while retaining the robustness. The proposed method consists of several steps. Firstly, the secret data is segmented into segments of the  length. Secondly, a suitable image that has features similar to the secret message is selected and divided into non-overlapping blocks. Thirdly, these blocks are transformed into the frequency domain by applying discreet wavelet transform (DWT). Fourthly, building a hash sequence table using a suggested hashing algorithm. Fifthly, to reduce search time an indexing table is built based on the generated hash sequence. Sixthly, match each segment with the generated hash sequences and save the auxiliary information for each matched segment in the image in a file. Lastly, send the stego image and the auxiliary information file to the receiver. The experimental results show that the CIS method produces high capacity compared with previous CIS methods.
A coverless image steganography based on robust image wavelet hashing Nadia A. Karim; Suhad A. Ali; Majid Jabbar Jawad
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 6: December 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i6.23596

Abstract

Since the concept of coverless information hiding was proposed, it has been greatly developed due to its effectiveness of resisting the steganographic tools. In this paper, a new coverless steganography is presented to hide the secret data in a more secure way and to enhance the robustness against attacks. This method depends on frequency domain. The embedding process consists of several steps. Firstly, the secret data is divided into no overlapping segments. Secondly, a set of images is collected to find appropriate images to be stego images. Thirdly, to build a hash sequence for an image, a powerful hashing algorithm is used. Fourthly, for each image hash sequence, the inverted index structure is created. Fifthly, choose the image which its hash equivalent to the secret data segment. Several tests are done to measure the robustness of the proposed method. The results of the experiments reveal that the proposed strategy is resistant to a variety of image processing attacks such as joint photographic experts group (JPEG) compression, noise, low pass filtering, scaling, rotation and median and mean filter, brightness, and sharpening.
Enhance iris segmentation method for person recognition based on image processing techniques Israa A. Hassan; Suhad A. Ali; Hadab Khalid Obayes
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 21, No 2: April 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v21i2.23567

Abstract

The limitation of traditional iris recognition systems to process iris images captured in unconstraint environments is a breakthrough. Automatic iris recognition has to face unpredictable variations of iris images in real-world applications. For example, the most challenging problems are related to the severe noise effects that are inherent to these unconstrained iris recognition systems, varying illumination, obstruction of the upper or lower eyelids, the eyelash overlap with the iris region, specular highlights on pupils which come from a spot of light during captured the image, and decentralization of iris image which caused by the person’s gaze. Iris segmentation is one of the most important processes in iris recognition. Due to the different types of noise in the eye image, the segmentation result may be erroneous. To solve this problem, this paper develops an efficient iris segmentation algorithm using image processing techniques. Firstly, the outer boundary segmentation of the iris problem is solved. Then the pupil boundary is detected. Testes are done on the Chinese Academy of Sciences’ Institute of Automation (CASIA) database. Experimental results indicate that the proposed algorithm is efficient and effective in terms of iris segmentation and reduction of time processing. The accuracy results for both datasets (CASIA-V1 and V4) are 100% and 99.16 respectively.