Azizah Abd Manaf

An effective SVD-based image tampering detection and self-recovery using active watermarking

In this paper, an effective tamper detection and self-recovery algorithm based on singular value decomposition (SVD) is proposed. This method generates two distinct tamper detection keys based on the singular value decomposition of the image blocks. Each generated tamper detection and self-recovery key is distinct for each image block and is encrypted using a secret key. A random block-mapping sequence and three unique optimizations are employed to improve the efficiency of the proposed tamper detection and the robustness against various security attacks, such as collage attack and constant-average attack. To improve the proposed tamper localization, a mixed block-partitioning technique for 4×4 and 2×2 blocks is utilized. The performance of the proposed scheme and its robustness against various tampering attacks is analyzed. The experimental results demonstrate that the proposed tamper detection is superior in terms of tamper detection efficiency with a tamper detection rate higher than 99%, security robustness and self-recovery image quality for tamper ratio up to 55%. HighlightsA novel SVD-based image tamper detection and self-recovery by active watermarking is proposed.A new aspect of singular values for each images block is utilized to improve the detection rate.The combination of 4×4 and 2×2 block sizes improved the recovered images quality.The proposed optimizations improved the schemes security against several malicious attacks.The results showed the superiority of the algorithm in terms of accuracy, security and recovery.

Analysis of ISB watermarking model: block based methods vs embedding repetition methods

Digital watermarking technique based on intermediate significant bit (ISB) has been discussed by this study. This technique can survive against different types of attacks and at the same time keep the quality of the image. In this study, two improvement stages were applied, repeating the embedding and watermark embedding based on the average of pixels values. The results showed that the value of the Normalized Cross Correlation (NCC) was increased by increasing the embedding number of all the attacks. The results of the NCC for all the attacks became very close to 1 after nine repetitions. The results indicate that the method, based on the average of pixels values, is better for all the attacks as compared to based on repetition, except for rotation and scaling which improved extensively using the same method.

Nearest Neighbor For Histogram-based Feature Extraction

Manual grading process of Fresh Fruit Bunch (FFB) leads to misconduct and human error while inspecting the right category of fruits for the purpose of oil palm production at the mill. It is extremely important to identify the degree of ripeness of FFB are at 95% level of confidence as mentioned by Malaysian Palm Oil Board (MPOB). Therefore, wrong evaluation of graded fruits will result wrong report regarding the oil content. However, the most critical part of oil palm grading is the fruit classification. Error in classifying the right category of FFB will cause error in estimating the oil content. Research done by Federal Land Development Authority (FELDA) at mills show the estimated oil content for ripe fruit is 60%, while underripe is 40% and unripe is only 20% minus water and dirt. This indicates the importance of the right classification of FFB during grading process is essential to prevent from mistakenly claim low quality fruits as the good ones. Problem will occur while receiving the grading report claiming the high percentage of Basic Extraction Rate (BER) by the appointed graders while they have been proven to be poor quality fruits during oil production process. Fruit ripeness identification based on color is hard to measure especially when it involves the color intensity. The most suitable color space must be carefully selected to determine the right color especially when the color intensity is involved. HSV color space has proven to be a good choice because it has all the colors in the channel. Besides, it also offers color intensity which can be in variety level of intensity degrees. This paper explores the use of Nearest Neighbor Distance for histogram-based fruit ripeness identification. Promising results are obtained when value elements of HSV gives the highest recognition rate towards both ripe and unripe category.

Perceived Effectiveness of Information Technology Governance Initiatives Among IT Practitioners

Information Technology (IT) governance has risen in importance in recent years, driven by various trends in IT development. With rapid growth in the country and the globalization of the IT sector, there is growing interest in IT governance in Malaysia. This study aims to explore whether IT practitioners with different job functions, education levels, education areas of specialization, certifications and experience levels have different perceptions of IT governance effectiveness in their organization. The results reveal differences in perceived IT governance effectiveness between different job function groups, but not between groups with different education levels, certification or experience levels. The findings for education area of specialization are not conclusive. The findings of this study will help IT managers to identify areas of focus to maximize effectiveness of IT governance initiatives through their IT staff. The implications of the findings are discussed at the end of the paper.

SQL injection vulnerability general patch using header sanitization

SQL injection is one of well-known web application vulnerabilities. SQL injection is a type of attack which attacker attempts to insert malicious SQL query through none sanitized variables into the web application. Consequently web application will concatenate the variable with the legitimate query and will send it to the database for execution. In result of a successful SQL injection attack, the attacker can read from the database or modify entities of the database (Insert, Delete, Update). Currently different types of defense systems are available to defeat this vulnerability. However some of these techniques needs to stop the existence web application and patch the vulnerability, and since this process might be time consuming, it is not very practical for companies to stop their online services. To address this problem we proposed a model which can generally patch the SQL injection vulnerability. The model is not dependent on the language which the web application is written in and the amount of necessary changes in the application is low. The model can be implemented as a library which can be include in the vulnerable web application by calling one line of code.

Efficient Two Level Image Tamper Detection Using Three LSB Watermarking

The integrity and authenticity of digital images have become more important in past few years with the fast improvement of digital technologies. The integrity of digital images can be achieved by using digital watermarking. In this paper we proposed an efficient image tamper detection method using 3 LSB (last significant bit) watermarking technique. In the proposed algorithm a 12-bit watermark created from each block of host image will embed to last three significant bit of each block. Our proposed method improved Chaluvadi and Prasads tamper detection rate by 40 percent. To evaluate the proposed method, we performed different types of tamper attacks and demonstrated the result in this paper. The experimental result clearly proved the efficiency of our proposed method.

Forensic investigation and analysis on digital evidence discovery through physical acquisition on smartphone

Cybercriminals are changing their strategies as users are less concerns on the smartphone and social networks security risks such as spams, that will threaten them as they are more dependent on the smartphone [1]. Thus, theres a need to perform the smartphone forensics analysis to retrieve and analysed the potentially great amounts and extremely valuable information on these devices. This paper investigates a wealth of personal and sensitive data by types of digital information as evidence and conducted forensic analysis on a popular smartphone Samsung Galaxy Note III. The standard approach applied to extract information from smartphone through physical acquisition and analysis using Cellebrite UFED. The results are presented to demonstrate the smartphone as a goldmine for investigators and as sources of digital evidence. Furthermore this research also presents the forensic tool and techniques for acquiring and examining digital evidence on this device. The evidence discovered include files, contacts, events of smartphone and social network data storage and location. The smartphone examined produced abundant user information and in total 98,127 artefacts were recovered. Performing the extraction and analysis of digital evidence over smartphone activities show the possibility of identifying potential suspects that could assist the forensic investigators in crime investigations.

Efficient Image Authentication and Tamper Localization Algorithm Using Active Watermarking

Due to the increasing number of forged images and possibilities of effortless digital manipulations, certain organizations have started to focus on approaches that help preserve their digital data integrity. Image authentication systems try to accurately verify the integrity of digital images, of which digital watermarking is known to be one of the most precise techniques in authenticating the originality of digital images. This chapter has presented a novel image authentication system with accurate tamper localization ability. In the proposed algorithm a 16-bit watermark key has been created from each block of pixels in a host image. The generated 16-bit watermark key will be embedded into the host image by utilizing a fragile watermarking algorithm. The security of the watermarking algorithm will be ensured by using the proposed block cipher algorithm, which encrypts the user key and watermarking algorithm. The proposed tamper detection algorithm conducts two comprehensive comparisons, to ensure the accuracy of the results. The high quality watermarks and powerful tamper detection approaches, along with less computational complexity are the main advantages of the proposed image authentication system, which makes it suitable for real-time application. Several tampering experiments have been conducted to examine the proposed algorithm. The experiment results have clearly proved that, the proposed method is not only efficient, but also very accurate in detecting different types of digital image manipulations, such as, small region tampering, cropping tampering and bit tampering.

A secure blind discrete wavelet transform based watermarking scheme using two-level singular value decomposition

Abstract In this paper, a secure blind image watermarking scheme is proposed to improve efficiency of hybrid Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) based schemes. The main contribution of this research is using two-level singular value decomposition in hybrid DWT + SVD watermarking schemes results to high improvement in both imperceptibility and robustness. Also, security is ensured in this scheme by proposing a two-level authentication system for watermark extraction in which not only the false positive problem is eliminated, when the attacks are very severe, the false negative effect is also detected and prevented. In the proposed scheme, the cover image is initially transformed to DWT and the high frequency sub bands are selected. Subsequently, High (HH) sub band is divided into 8 × 8 non overlapping blocks and the SVD transform is applied to each of them. In SVD transform, the highest energy compaction is in the first row and the first column of the matrix of singular values. These singular values for each block will be collected in a separate matrix and then the second SVD transform will be exerted on the produced matrix. The singular values of the watermark image after exerting one level DWT, is embedded into the singular values of this matrix. Experimental result shows when the scheme is subjected to ten most common types of signal processing and geometric attacks, using the second level of SVD makes it highly robust and imperceptible while it is independent from type of image. So, the proposed scheme is tested and certified for both medical and normal images. This scheme is compared to a range of hybrid schemes using DWT and one level SVD, and experimental results show high improvements in imperceptibility with the average of 46.6950 db and robustness more than 99% and proven efficiency in security.

A Practical Procedure for Collecting More Volatile Information in Live Investigation of Botnet Attack

Nowadays because of the growth of internet usage in all over the world, users of this global service are faced with many different threats. Attackers are trying to improve their methods in order to penetrate the users’ machines to misuse their systems and their information. Most of the cyber-crimes are the result of one attack to a user or a network of many users. One of the important attacks in this area is Botnet which is controlling some compromised computers by an attacker remotely in terms of specific victim. This study tries to propose and implement a procedure in order to extract information and footprints of infected system with Botnet in order to reconstruct the Botnet attack and prepare a digital evidence package which shows the malicious activities and malicious files of this attack to present in a court.