Customer reviews on online platforms have grown to become an important source of insight into a company's performance. Food delivery services (FDS) companies aim to effectively use customers' feedback to identify areas for improvement of customer satisfaction. Although Arabic is becoming one of the most widely used languages on the Internet, only a few studies have focused on Arabic sentiment analysis to date. The present study conducts an extensive emotion mining and sentiment analysis on FDS-related reviews in Arabic, exploiting natural language processing, and machine learning techniques to extract information that reflects customers' subjective viewpoints, recognize their feelings, and determine polarity in the FDS domain. This work begins with collecting the FDS dataset (Talabat), and then extracting and creating a dialects lexicon for Arabic dialects, followed by walking the reader through detailed steps of cleaning and pre-processing a manually annotated dataset. Finally, we examined classification algorithms including Decision Tree (DT), and Support Vector Machine (SVM). We achieved a maximum accuracy of about 82% using the SVM classifier.

The availability of high resolution images allows for using steganography to hide the presence of secret information. An issue of importance is to guarantee that the hidden data neither affects the quality of the images nor is it visually perceived. Another factor to consider is the capacity of embedding in the cover images without detection. In this paper we employ the Discrete Cosine Transform compression with quantization for lossy compression. We use the Salp Swarm Algorithm in conjunction with chaotic maps to find optimal locations in the cover images for data embedding in the LSBs. When chaotic maps are inserted into the SSA algorithm environment, the proposed method has achieved satisfactory results with minimal impact on the PSNR.

Image steganography has been widely adopted to protect confidential data. Researchers have been seeking to improve the steganographic techniques in order to increase the embedding capacity while preserving the stego-image quality. In this paper, we propose a steganography method using particle swarm optimization and chaos theory aiming at finding the best pixel locations in the cover image to hide the secret data while maintaining the quality of the resultant stego-image. To enhance the embedding capacity, the host and secret images are divided into blocks and each block stores an appropriate amount of secret bits. Experimental results show that the proposed scheme outperforms existing methods in terms of the PSNR and SSIM image quality metrics.

Several grouping proof protocols were presented to meet the security requirements of Radio Frequency Identification Systems. Nevertheless, these protocols were shown to be vulnerable to various attacks. In this work, we cryptanalyze one of the newest grouping proof protocols. Through this analysis, we show the weaknesses of the protocol and launch a full-disclosure attack to disclose all secrets in the protocol. We show that the probability of success of the protocol is one and that increasing the length of the strings adds little complexity to the attack. We follow this by proposing an enhanced version of the protocol with better overall security. We show its efficiency by providing a security and performance analysis and comparing it with some of the existing protocols in the literature.

Radio frequency identification is a modern technology for item identification that has widely spread over the recent years. In order to securely identify the items and transfer their ownership from one entity to another, several authentication and ownership management protocols have been proposed. One of the recent protocols is Niu et al.'s EPC Class 1 Generation 2 RFID Standard Authentication and Ownership Management protocol. This lightweight protocol is mainly based on the use of bitwise XOR and permutation operations in addition to the lightweight 16-bit Pseudo Random Number Generator. However, Bagheri et al. launched de-synchronization and secret-disclosure attacks against Niu et al.'s protocol and proved that it does not fulfill the requirements for a secure authentication and ownership management protocol. In this paper, we propose an enhancement for Niu et al.'s protocol such that it can resist the de-synchronization and secret-disclosure attacks. The enhanced protocol is based on using the bitwise conversion and Hamming Weight-based left rotation operations instead of the 16-bit Pseudo Random Number Generator and the permutation operation in order to resist the secret-disclosure attack. Moreover, the proposed protocol employs the old-ids-denial mechanism and adds extra messages to the mutual authentication and ownership delegation phases so that it can defend against the de-synchronization attack.

Providing security in passive RFID systems has gained significant attention due to their widespread use. Research has focused on providing both location and data privacy through mutual authentication between the readers and tags. In such systems, each party is responsible of verifying the identity of the other party with whom it is communicating. For such a task to succeed, the tags and readers are initialized with shared secret information which is updated after a successful authentication session. Ownership management, which includes transfer and delegation, builds upon mutual authentication. Here, the use of security in RFID is extended to encompass the more practical case where a tagged item is shifted from one owner to another. As such, we propose a new authentication and ownership management protocol that is compliant with the EPC Class-1 Generation-2 Version 2 standard. The protocol is formally analyzed and successfully implemented on hardware. The implementation shows that the use of such protocol adds security with little added overhead in terms of communication and computation.

Passive RFID tags and readers are initialized with secret keys which are updated after a successful cycle of authenticatio. Ownership transfer builds upon mutual authentication where a tagged item is shifted from one owner to another. Since the available protocols provide limited security for passive RFID systems and are vulnerable to attackers, we propose a novel ultra-lightweight authentication and ownership management protocol which conforms to the EPC Class-1 Generation-2 Version 2 standard while taking into account the storage and computational resources of the tags. The protocol is successfully implemented on hardware to overcome the weaknesses of the available protocols. The experimental results show that the use of such protocol ensures security with little added communication and computation overhead.