Conference Papers


Dynamical Behavior of a Delayed Predator Prey Model with Hunting Cooperation on Predator

Hebatallah J. Alsakaji (Department of Mathematical Sciences UAE University, Al Ain, UAE); Fathalla A. Rihan (Department of Mathematical Sciences UAE University, Al Ain, UAE)


The dynamical relationship between prey and predator has long been and will continue to be one of the effective themes in ecology because of its universal existence and importance. In this paper, we propose a delay differential model for predator-prey system with hunting cooperation on predator (cooperative hunting increases as predator density increases). We consider that the rate of change of density of population depends on growth, death and intra-specific competition for the predators, with logistic growth rate for preys. We incorporate time-delay in the growth component for prey and predator to represent the gestation period for preys. We study the existence of positive equilibrium points and their asymptotic stabilities. Hopf bifurcation is obtained in terms of critical values of time-delays. The system may have a stable periodic orbit, depending on parameter values. The presence of time-delays in the model improves the stability of the solutions and enriches the dynamics of the model. Numerical simulations are provided to validate the derived theoretical results.

Collaborative Caching For D2D Content Sharing In 5G

Ansam Abdelsalam (American University of Sharjah, Sharjah, UAE); Rana Ahmed (American University of Sharjah, Sharjah, UAE)


Due to the huge number of mobile devices expected to be connected to 5G wireless networks and their expected demand in high data-rate, the core network and the backhaul links are expected to be congested with the large amount of data traffic. Caching the most popular files at the network edge and in user?s devices will provide a close proximity to the end user which will help to offload traffic in the core network, minimize the overall system latency, and to increase the cache hit probability. Device to Device (D2D) communication can be utilized to exchange the cached files between any pair of devices upon request. However, there are many challenges that are needed to be addressed including popularity index, interference management, mode selection, device discovery, and content placement. This work attempts to solve most of the abovementioned problems via collaborative content caching and sharing using D2D communication in 5G networks. The proposed system model will exploit the social-networking concept, assuming the cell structure in a condensed populated area. It will be validated and simulated, and the results will be compared to the base-line system performance reported in literature.

A Comparative Legal Analysis of Cyberbullying and Cyberstalking in the UAE, US, UK, and Canada

Haifa Al Hosani (College of Technological Innovation Zayed University, UAE); Maryam Yousef (College of Technological Innovation Zayed University, UAE); Shaima Al Shouq (College of Technological Innovation Zayed University, UAE); Farkhund Iqbal (College of Technological Innovation Zayed University, UAE)


Bullying and stalking through cyberspace have become serious phenomena in the Internet era, impacting mainly young users and teenagers. Many tragic incidents have occurred, especially in the West, including self-harm and suicide due to these problems. To protect the victims, many countries such as the United Arab Emirates (UAE), the United States (US), England and Canada have codified laws dealing with cyber-crimes, including cyber-harassment. To determine the adequacy of the laws in addressing these issues, we present in this paper a legal analysis of the existing anti-bullying and stalking laws in the UAE, the US, England, and Canada. The purpose is to gain perspective on the characteristics of the laws and their ability to protect the society from various forms of crimes associated with cyberbullying and stalking. The paper also presents recommendations and steps to help combat cyberbullying and cyberstalking and protect our youth from these issues.

SQL Injection and Rootkit Forensics in Relational Databases: A Case Study of Two Insider Attacks

Abdulla Kazim (College of Technological Innovation Zayed University, UAE); Fadya AlMaeeni(College of Technological Innovation Zayed University, UAE); Hakim Hacid (College of Technological Innovation Zayed University, UAE)


Databases are very crucial for the implementation of any kind of system, and integrity and confidentiality of stored data is what makes it valuable. Attacks on databases may differ in nature from those on normal operating systems, nonetheless it requires a forensic approach that might be specific for databases. In this paper, we discuss SQL injection for malicious SQL statements execution from an insider and how digital forensics might help in discovering it. We also discuss how the concept of rootkit can be planted by an insider into a relational database system to conceal a user account from the view of a database administrator and thus can use this account as a backdoor to access the database for malicious purposes.

Forensics Investigation of Humanoid Robot: A Case Study on Zenbo Robot

Abdulla Kazim (College of Technological Innovation Zayed University, UAE); Musaab Mohamad (Ajman University, Ajman, UAE); Farkhund Iqbal(College of Technological Innovation Zayed University, UAE)


In contrast to traditional devices, Internet of Things (IoT) devices work on the basis of connectivity and data sharing, which necessarily allows for data to reside on multiple platforms or locations. From a digital investigation perspective, reconstructing the full trail of activity involving an IoT device may therefore require composing digital evidence from a variety of devices and locations and this may pose a signicant forensic challenge. Humanoid robots adopt the concept of IoT to perform their functions, and they depend on supervised learning to customize their capabilities to people and environments. Since they are designed to interact with humans in a more social and personal context than other digital devices, a fully functioning humanoid robot can be a rich source of sensitive data about individuals and environments that may assist in any digital investigation. In this paper, we consider the humanoid robot, Zenbo, as a use case to present a comprehensive forensic examination that acts as a guide for forensic examiners by simulating real case scenarios. Furthermore, a deeper examination is conducted on this robot to locate all the useful pieces of evidence and artifacts from multiple locations including root level directories through the use of logical acquisition.

Wavelet-Based Multistep Methods for Initial-Value Problems

Mohamed A. Hajji (Department of Mathematical Sciences UAE University, Al Ain, UAE); Athar Bsharat(Department of Mathematical Sciences UAE University, Al Ain, UAE)


Wavelets have been a popular tool since the 1980s in many areas of engineering, quantum physics, and mathematical analysis. A major contribution of wavelets is their adaption in the JPEG$2000$ picture format. Since then wide applications of wavelets in different areas have emerged. Popular wavelets are those constructed by I. Daubechies which have compact support. In this work, we use Daubechies? wavelets in developing multistep algorithms for the solution of initial value problems (IVPs). Though, such wavelet basis has good approximation property, they do not have explicit formula. This is a challenge in finding inner products. This work tackles this point and uses the properties of wavelet basis to approximate such inner products leading to implicit multistep methods with comparable stability regions with other methods.

Evaluating Malware Detection Effectiveness of Operating Systems Defenses

Abdulla Kazim (Zayed University, UAE); Mathew Nicho(Zayed University, UAE); Fadya Almaeeni(Zayed University, UAE)


Operating Systems (OS) is a favorite target of attacks by hackers to gain unauthorized access using malware that can be created by commonly available malware creation tools. While multiple cyber techniques have been used to gain unauthorized access to computers, ?malware? is commonly used as a threat agent to gain entry into operating systems. Even though operating systems updates, and patches ensure adequate defensive mechanisms to prevent/detect these malwares, it has been found that it is not a foolproof system. To test the capability of the OS we chose three commonly used malware tools to create malware targeted at three versions of Windows OS namely 7, 8.1 and 10. Our penetration test revealed that only version 10 was able to detect and prevent the malware while the rest could not. With millions of Windows 7 and 8.1 still being used by individual computer users and organizations worldwide this is viewed as a potent threat. Furthermore, as malware creation tools gets regularly updated, we feel that eventually Windows 10 may fall victim to these malware attacks.

Data Integrity 2.0: Towards an End-User Layer for Data Integrity

Lu;ay Ahmad Abu Rayyan (College of Technological Innovation Zayed University, UAE); Hakim Hacid (College of Technological Innovation Zayed University, UAE)


Data Integrity (DI) is the ability to ensure that a data retrieved from a database is the same as that stored and processed. The loss of Data Integrity is generated by having data being tampered with by authorized or unauthorized users. The purpose of this article is to characterize and quantify Data Integrity in a structured approach by computing its degree (rate) of loss based on defined criteria, relying on DDL and DML operations together with the security configuration of the DBMS. The driving idea is to provide a simple, yet strong, way to inform the end-user (mainly non-experts although it can be used by experts for investigation matters) with a simple manner of appreciating the DI and potential related issues to support the decision making. We discuss different scenarios to measure the data integrity loss.

Mobile Database Forensics: A Case Study of SQLite

Abdulla Kazim (College of Technological Innovation Zayed University, UAE); Fadya AlMaeeni(College of Technological Innovation Zayed University, UAE); Hakim Hacid (College of Technological Innovation Zayed University, UAE)


Databases can be seen as the backbone of any developed application that provides the feature of managing data. The storage capability of databases can be utilized in digital forensic investigations to retrieve various data about the suspect and the carried activities. While encryption can be used to protect some or all the data stored in the database, a weakness in setting up the encryption may assist the forensics investigator in decrypting some of the stored encrypted data. In this paper, we discuss how a security setup weakness in SQLite can be of great assistance for an investigator and how it can be used in a forensics investigation.


M. Sami Zitouni (Khalifa University, Abu Dhabi, UAE)


Crowd analysis is currently the prime focus of many research works in computer vision. In this report, a deep learning method for detection of three categories in crowded scenes, i.e. individuals, small and large groups, is proposed. In the method, the training data for these categories are automatically annotated using alternative appearance and motion models. Then, three detectors are trained to identify individuals, small groups, and large groups, using Faster R-CNN (regions with convolutional neural networks) architecture. Additional training data are periodically collected and annotated (using the same computer vision models) to fine-tune/retrain the detectors, and to enhance their performances, especially when the test scenes and environments are changing. The proposed method is tested on different scenarios, and results are provided to demonstrate performances.

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