Osama S. Faragallah

Divided two-part adaptive intrusion detection system

The main objective of this paper is to design a more complete intrusion detection system solution. The paper presents an efficient approach for reducing the rate of alerts using divided two-part adaptive intrusion detection system (DTPAIDS). The proposed DTPAIDS has a high degree of autonomy in tracking suspicious activity and detecting positive intrusions. The proposed DTPAIDS is designed with the aim of reducing the rate of detected false positive intrusion through two achievements. The first achievement is done by implementing adaptive self-learning neural network in the proposed DTPAIDS to gives it the ability to be automatic adaptively system based on Radial Basis Functions (RBF) neural network. The second achievement is done through dividing the proposed intrusion detection system IDS into two parts. The first part is IDS1, which is installed in the front of firewall and responsible for checking each entry user’s packet and deciding if the packet considered is an attack or not. The second is IDS2, which is installed behind the firewall and responsible for detecting only the attacks which passed the firewall. This proposed approach for IDS exhibits a lower false alarm rate when detects novel attacks. The simulation tests are conducted using DARPA 1998 dataset. The experimental results show that the proposed DTPAIDS [1] reduce false positive rate, [2] detects intrusion occurrence sensitively and precisely, [3] accurately self–adapts diagnoser model, thus improving its detection accuracy.

A Neural Network-Based Learning Algorithm for Intrusion Detection Systems

Recently, intrusion detection systems (IDS) have been introduced to effectively secure networks. Using neural networks and machine learning in detecting and classifying intrusions are powerful alternative solutions. In this research paper, both of Gradient descent with momentum (GDM)-based back-propagation (BP) and Gradient descent with momentum and adaptive gain (GDM/AG)-based BP algorithms are utilized for training neural networks to operate like IDS. To investigate the efficiency of the two proposed learning schemes, a neural network based IDS is built using the proposed learning algorithms. The efficiency of both algorithms is inspected in terms of convergence speed to achieve system learning, and elapsed learning time using various settings of neural network parameters. The result demonstrated that the GDM/AG-based BP learning algorithm outperforms the GDM-based BP learning algorithm.

Secure Audio Cryptosystem Using Hashed Image LSB watermarking and Encryption

Abstract The paper proposes a secure audio cryptosystem that realize integrity, authentication and confidentiality. The proposed audio cryptosystem achieves integrity by applying a message digest algorithm, authentication by employing LSB watermarking and confidentiality through encryption with Advanced Encryption Standard (AES) or RC6. The main concept of the proposed audio cryptosystem relays on XORing the plain-audio with one selected image from a private image database. Then, the mixed plain-audio blocks are LSB watermarked with the selected image hash value prior to ciphering. The proposed audio cryptosystem is prepared with the potential of increasing immunity against brute force attacks and providing integrity, authentication and confidentiality through the selected image hash value addition using LSB embedding as an extra key. Also, the extra XORing step removes residual intelligibility from the plain-audio blocks, fills the speechless intervals of audio conversation and helps in destroying format and pitch information. The proposed audio cryptosystem is compared with audio encryption using AES, and RC6 through encryption key performance indicators. The comparison outcomes ensured the superiority of the proposed audio cryptosystem. Security investigation of the proposed audio cryptosystem is studied from a precise cryptographic standpoint and tests ensured the superiority of the proposed audio cryptosystem from a cryptographic standpoint.

Robust hybrid watermarking techniques for different color imaging systems

Digital watermarking is an efficient and promising mechanism for protecting the copyright of the transmitted multimedia information. Thus, this paper presents two robust hybrid color image watermarking techniques. The objective of the proposed watermarking techniques is to increase the immunity of the watermarked color images against attacks and to achieve adequate perceptual quality. The first proposed hybrid technique is the homomorphic transform based Singular Value Decomposition (SVD) in Discrete Wavelet Transform (DWT) domain. Firstly, the DWT is employed to divide an image into non-overlapping bands. Then, the reflectance components of the LL sub-bands are extracted using the homomorphic transform of each of the RGB (Red, Green, and Blue) color image components. After that, the watermark is embedded by applying the SVD on these reflectance components. The second proposed hybrid technique is the three-level Discrete Stationary Wavelet Transform (DSWT) in Discrete Cosine Transform (DCT) domain. In this technique, the RGB components of the host color image are separated, and then the DCT is applied on each separated color component. The three-level DSWT is employed to divide the DCT components into four sub-bands. These sub-bands are the A, H, V, and D matrices, which have the same host image size. The watermark image is then embedded into the determined matrix A. The two proposed hybrid watermarking techniques are compared with the current state-of-the-art techniques. This paper also presents a comparative study of the proposed techniques for different color imaging systems to determine their robustness and stability. The comparisons are based on the subjective visual results to detect any degradation in the watermarked image in addition to the objective results of the Peak Signal-to-Noise Ratio (PSNR) of the watermarked image, and the Normalized Correlation (NC) of the extracted watermark to test and evaluate the performance efficiency of the proposed watermarking techniques. Extensive experimental results show that the proposed hybrid watermarking techniques are both robust and have adequate immunity against different types of attacks compared to the traditional watermarking techniques. They achieve not only very good perceptual quality with appreciated PSNR values, but also high correlation coefficient values in the presence of different multimedia attacks.

Efficient HEVC selective stream encryption using chaotic logistic map

At present, the digital video encryption technology has become an interest research topic as a result of very rapid evolution in the application of real-time video over the Internet. So this paper presents a new method for encrypting the selective sensitive data of the latest video coding standard, which called High-Efficiency Video Coding (HEVC). The High-Efficiency Video Coding was founded in 2013 by the Joint Collaborative Team on Video Coding (JCT-VC) from the ISO/IEC Moving Picture Experts Group (MPEG) and ITU-T Video Coding Experts Group (VCEG). The proposed selective encryption HEVC video technique uses the low complexity overhead chaotic logistic map (CLM) to encrypt the sign bits of the Motion Vector Difference (MVD) and the Discrete Cosine Transform (DCT) coefficients in the entropy stage of the process of video encoding. The contribution of the proposed CLM-based HEVC SE is to encrypt the sensitive video bits with the features of low complexity overhead, fast encoding time, keeping the HEVC constant bitrate and format compliant. Also, this paper introduces a comparative study between the proposed CLM-based HEVC SE and the Glenn HEVC SE that uses the Advanced Encryption Standard (AES). Experimental results demonstrate the main feature of the proposed CLM-based HEVC SE, which turned out to save the time of the video encoding with remaining of the near visual distortion of the encrypted video stream by Glenn HEVC SE. This feature is due to the low complexity of the CLM-based encryption employed in the proposed CLM-based HEVC SE scheme instead of using the AES in the Glenn HEVC SE. A course of security investigation experiments is performed for the proposed CLM-based HEVC SE including the main security performance metrics like encryption quality, key space, statistical and sensitivity tests. The achieved test results ensured the superiority of the proposed CLM-based HEVC SE for digital video streams.