Ammar Almomani

• Professor.
• Professor at Higher Colleges of Technology (HCT)

Distributed denial of service (DDoS) attacks have emerged as a critical challenge for cloud computing, impacting service availability and raising concerns among providers. Despite cloud computing's scalable and flexible architecture, its vulnerabilities make it an attractive target for attackers. This paper presents a comprehensive survey of DDoS a...

The rapidly evolving darknet enables a wide range of cybercrimes through anonymous and untraceable communication channels. Effective detection of clandestine darknet traffic is therefore critical yet immensely challenging. This research demonstrates how advanced machine learning and specialized deep learning techniques can significantly enhance dar...

Educational data mining has sparked a lot of attention in latest years. Many machine learning methods have been suggested to discover hidden information from educational data. The extracted knowledge assists institutions in enhancing the effectiveness of teaching tactics and the quality of education. As a result, it improves students' performance a...

This paper presents a modified bonobo optimizer (MBO) that integrates the Gaussian local mutation, restart strategy, and random contraction strategy into the original bonobo optimizer (BO). BO, inspired by the unique reproductive schemes and fission-fusion social behaviors of bonobos, has previously demonstrated promising results in solving a range...

Machine learning has become ubiquitous across industries for its ability to uncover in- sights from data. This research explores the application of machine learning for identifying phishing websites. The efficiency of different algorithms at classifying malicious sites is evaluated and contrasted. By exposing the risks of phishing, the study aims t...

The internet of things (IoT) represents a rapidly expanding sector within computing, facilitating the interconnection of myriad smart devices autonomously. However, the complex interplay of IoT systems and their interdisciplinary nature has presented novel security concerns (e.g. privacy risks, device vulnerabilities, Botnets). In response, there h...

The generation and control of cryptographic keys are the most important things when it comes to the security and integrity of encrypted data. The traditional key generation methods including pseudorandom number generation often fail to generate truly random values and become predictable as well. This chapter explores the potential of generative adv...

This chapter aims to determine the role of cryptography in the provision of secure applications of business intelligence and data analytics. Through this, the legal implications for weak cryptographic systems are illustrated in areas such as safeguarding customer information, trade secrets, and intellectual property in the context of data-driven bu...

The combination of artificial intelligence (AI) methods like machine learning with cryptography is essential for more intelligent and adaptable security measures. This chapter of the book outlines the convergence of AI with cryptography in detail. It summarizes the foundations of cryptography and the major AI techniques such as machine learning, de...

This chapter explores the impact of quantum computing on cybersecurity, comparing classical and quantum techniques. It provides an overview of the current quantum landscape, focusing on the threats posed by quantum algorithms to traditional encryption methods. The study examines defensive strategies, such as quantum key distribution and post-quantu...

Blockchain's decentralized trust models are spurring rapid advances in applied cryptography. This chapter explores the accelerating convergence between cryptographic innovations and next-gen blockchain platforms. The authors provide background on modern cryptography and the distributed ledger tech behind blockchains. They then analyze how blockchai...

This chapter analyzes the most sophisticated cryptography methods which are used to protect blockchain-based cryptocurrency transactions against attacks by botnets. First, a background will explain blockchain, cryptocurrencies, and threat space for bots is going to sing in. Core cryptographic building blocks such as hash functions and digital signa...

Homomorphic encryption enables computations on encrypted data, providing confidentiality for cloud computing applications. This chapter explains the foundations, classifications, and security definitions for homomorphic encryption schemes. Partially and somewhat homomorphic cryptosystems allow limited operations whereas fully homomorphic encryption...

Machine learning models rely on sensitive personal data, creating tension between utility and privacy. Privacy-preserving machine learning aims to enable secure data analysis through cryptographic techniques. This chapter provides an overview of fundamental cryptographic primitives including secure multiparty computation, homomorphic encryption, di...

The proliferation of Internet of Things (IoT) devices has revolutionized many industries and daily life, however these resource-constrained devices also present significant cybersecurity challenges. Traditional cryptographic protocols are often too resource intensive for IoT use cases. This chapter provides a comprehensive review of lightweight cry...

Personal computers and the Internet are used in different areas and are easier to use. Most data is easy to transmit and duplicate in digital format, and being tampered with and stolen easily leads to issues for content owners and service providers. The Paper describes a secure (tampering-resistant) method for watermarking images for protection and...

This paper presents a novel approach to predictive Ischemic brain stroke analysis using game theory and machine learningtechniques. The study investigates the use of the Shapley value in predictive Ischemic brain stroke analysis. Initially, preferencealgorithms identify the most important features in various machine learning models, including logis...

This study presents a novel and innovative approach to automatically translating Arabic Sign Language (ATSL) into spoken Arabic. The proposed solution utilizes a deep learning-based classification approach and the transfer learning technique to retrain 12 image recognition models. The image-based translation method maps sign language gestures to co...

The Internet plays a crucial role in our daily routines. Ensuring cybersecurity to Internet users will provide a safe online environment. Automatic network intrusion detection (NID) using machine learning algorithms has recently received increased attention recently. The NID model is prone to bias towards the classes with more training samples due...

The smart city vision has driven the rapid development and advancement of interconnected technologies using the Internet of Things (IoT) and cyber-physical systems (CPS). In this paper, various aspects of IoT and CPS in recent years (from 2013 to May 2023) are surveyed. It first begins with industry standards which ensure cost-effective solutions a...

The proportion of multimedia traffic in data networks has grown substantially as a result of advancements in IT. As a result, it's become necessary to address the following challenges in protecting multimedia data: prevention of unauthorized disclosure of sensitive data, in addition to tracking down the leak's origin, making sure no alterations may...

The exponential growth of Internet and network usage has necessitated heightened security measures to protect against data and network breaches. Intrusions, executed through network packets, pose a significant challenge for firewalls to detect and prevent due to the similarity between legitimate and intrusion traffic. The vast network traffic volum...

People’s lives have become easier and simpler as technology has proliferated. This is especially true with the Internet of Things (IoT). The biggest problem for blind people is figuring out how to get where they want to go. People with good eyesight need to help these people. Smart shoes are a technique that helps blind people find their way when t...

Social media networks are becoming essential to our daily activities,and many issues are due to this great involvement in our lives. Cyberbullyingis a social media network issue, a global crisis affecting the victims and societyas a whole. It results from a misunderstanding regarding freedom of speech. Inthis work, we proposed a methodology for det...

Lung cancer has been the leading cause of cancer death for many decades. With the advent of artificial intelligence, various machine learning models have been proposed for lung cancer detection (LCD). Typically, challenges in building an accurate LCD model are the small-scale datasets, the poor generalizability to detect unseen data, and the select...

Darknet, a source of cyber intelligence, refers to the internet’s unused address space, which people do not expect to interact with their computers. The establishment of security requires analyses of the threats characterizing the network. New machine learning classifiers known as stacking ensemble learning are proposed in this paper to analyze and...

The darknet refers to an anonymous address space on the Internet where people do not expect to interact with their computers so that it is considered malicious and provides them with a safe place where people can express themselves anonymously. Tools such as “tor" are also used in illegal activities such as disseminating child abuse, selling Drugs...

Email is used in business and education and almost everywhere for communications. Email is categorized into many categories based on its content like primary, social, promotional, and spam. So spams are also a sub-category under all the categories. Spam may be in the form of text messages,web messages, images and others also. In this paper, we are...

Machine learning and deep learning are one of the most sought-after areas in computer science which are finding tremendous applications ranging from elementary education to genetic and space engineering. The applications of machine learning techniques for the development of smart cities have already been started; however, still in their infancy sta...

Scheduling large-scale and resource-intensive workflows in cloud infrastructure is one of the main challenges for cloud service providers (CSPs). Cloud infrastructure is more efficient when virtual machines and other resources work up to their full potential. The main factor that influences the quality of cloud services is the distribution of workf...

Cost estimation for software development is crucial for project planning and management. Several regression models have been developed to predict software development costs, using historical datasets of previous projects. Accurate cost estimation in software development is heavily influenced by the relevance and quality of the cost estimation datas...

The impending exhaustion of internet protocol (IP) version four (IPv4) addresses necessitates a transition to the more expansive IP version six (IPv6) protocol. However, this shift faces challenges due to the widespread legacy of IPv4 infrastructure and resistance among organizations to overhaul networks. Host-based translators offer a critical bri...

A healthy diet and daily physical activity are a cornerstone in preventing serious diseases and conditions such as heart disease, diabetes, high blood pressure, and hypertension. They also play an important role in the healthy growth and cognitive development for young and old people. Thus, this paper presents a new restaurant advisory system (RAS)...

Integrating virtual reality (VR) and augmented reality (AR) technology into online stores enables more immersive and engaging shopping experiences, which is crucial for businesses to succeed in today's competitive e-commerce market. These technologies offer unique, personalized experiences that consider the preferences and requirements of each cust...

Voice classification is important in creating more intelligent systems that help with student exams, identifying criminals, and security systems. The main aim of the research is to develop a system able to predicate and classify gender, age, and accent. So, a new system called Classifying Voice Gender, Age, and Accent (CVGAA) is proposed. Backpropa...

Image segmentation is the method of dividing an image into many segments, comprising groups of pixels. It is a process used to determine objects within the image. Fuzzy c-means (FCM) technique has been popularly employed as grayscale image segmentation method. Meanwhile, the conventional FCM suffers from some drawbacks including easy fall into loca...

Smishing is a combined form of short message service (SMS) and phishing in which a malicious text message or SMS is sent to mobile users. This form of attack has come to be a severe cyber‐security difficulty and has triggered incredible monetary losses to the victims. Many antismishing solutions for mobile devices have been proposed till date but s...

BACKGROUND OF THE INVENTION Internet of Things (IoT) enables sensors embedded physical objects to exchange information with other devices via internet. Users utilize the network services through various interfaces such as smart phones, PCs, laptops, notepads, etc. These interfaces have latent web application vulnerabilities such as Cross-Site S...

Feature selection (FS) is considered to be a hard optimization problem in data mining and some artificial intelligence fields. It is a process where rather than studying all of the features of a whole dataset, some associated features of a problem are selected, the aim of which is to increase classification accuracy and reduce computational time. I...

Virtual Private Networks (VPNs) are one example of encrypted communication services commonly used to bypass censorship and access geographically locked services. This study performed VPN and non-VPN traffic analysis and developed a classification system based on the new techniques of machine learning classifiers known as stacking ensemble learning....

Die vorliegende Erfindung bezieht sich auf das Gebiet der Kommunikation. Insbesondere bezieht sich die vorliegende Erfindung auf ein intelligentes Abwehrsystem gegen verteilte Denial of Service ( DDoS) Angriff in Internet der Dinge ( IoT) Netzwerke.

Cloud computing is a very large storage space, can be accessed via an internet connection, this concept has appeared to facilitate the preservation of personal and corporate data and the easily of sharing, and this data can also be accessed from anywhere in the world as long as it is on the Internet, large gaps have emerged around data theft and vi...

The phishing attack is one of the main cybersecurity threats in web phishing and spear phishing. Phishing websites continue to be a problem. One of the main contributions to our study was working and extracting the URL & Domain Identity feature, Abnormal Features, HTML and JavaScript Features, and Domain Features as semantic features to detect phis...

Educators have been calling for reform for a decade. Recent technical breakthroughs have led to various improvements in the semantic web-based education system. After last year's COVID-19 outbreak, development quickened. Many countries and educational systems now concentrate on providing students with online education, which differs greatly from tr...

Road accidents have become a major concern for safety today. The increase in the number of vehicles has significantly increased the real-time road traffic, leading to many fatal accidents. Over the years, researchers have been trying to find solutions to enhance vehicular security in order to prevent these accidents or at least reduce their impact....

Mobile networks, in particular, are composed of wireless cellular communication nodes (MANET). Communication between these mobile nodes is not under centric systems. MANET is a network of randomly traveling nodes that self-configure and self-organize. Routing is a fundamental topic of MANET, and performance analysis of routing protocols is the focu...

A Fast Flux Service Network (FFSN) domain name system method is a technique used on botnet that bot herders used to support malicious botnet actions to rapidly change the domain name IP addresses and to increase the life of malicious servers. While several methods for the detection of FFSN domains are suggested, they are still suffering from relati...

Fuzzy c-means algorithm (FCM) is among the most commonly used in the medical image segmentation process. Nevertheless, the traditional FCM clustering approach has been several weaknesses such as noise sensitivity and stuck in local optimum, due to FCM hasn't able to consider the information of contextual. To solve FCM problems, this paper presented...

Botnet Detection Used Fast-Flux Technique,Based on Adaptive Dynamic Evolving SpikingNeural Network Algorithm Abstract: A botnet refers to a group of machines. These machines are controlled distantly y a specific attacker. It represents a threat facing the web and data security. Command and Control C&C service is deemed as the pillar of botnet commu...

Information management collects data from several online systems. They analyze the information. They issue reports about information for supporting decision-making management. Utilizing current modern innovations try to controlling many obstacles such as, high cost, high battery power and speed system, safety System without building a full system t...

In today's internet world the internet of things (IoT) is becoming the most significant and developing technology. The primary goal behind the IoT is enabling more secure existence along with the improvement of risks at various life levels. With the arrival of IoT botnets, the perspective towards IoT products has transformed from enhanced living en...

Information management collects data from several online systems. They analyze the information. They issue reports about information for supporting decision-making management. Utilizing current modern innovations try to controlling many obstacles such as, high cost, high battery power and speed system, safety System without building a full system t...

Classification is achieved through the categorisation of objects into predefined categories or classes, where the categories or classes are created based on a similar set of attributes of the object. This is referred to as supervised learning. Numerous methodologies have been formulated by researchers in order to solve classification problems effec...

Globally, the acceptance of Open Source Software (OSS) varies among the users of a company. Despite the substantive software, social, and infrastructure-related implications of OSS acceptance, the research on the acceptance of OSS across organizations inhabitants remains surprisingly limited. To propose a model for the acceptance of OSS; investigat...

ABSTRACT Botnets are considered a serious issue today. They have several negative economic impacts as well. Such impacts are affecting orga- nizations and individuals. Recent botnets–such as Zeus and Citadel’s Conficker–use the Domain Name System (DNS) to avoid detection. These botnets use the DNS server to prevent the network adminis- trator from lo...

Abstract Classification is a crucial step in the data mining field. The probabilistic neural network (PNN) is an efficient method devel- oped for classification problems. The success factor of using PNN for classification problems implies in finding the proper weight during classification process. The main goal of this paper is to improve the perf...

Abstract—Nowadays, the concept of the Internet of Things (IoT) has become more noticeable and realistic where it is being used in all aspects of life, such as smart cities, agriculture, military surveillance, home automation, security, healthcare, etc. The idea behind IoT is making everyday objects, especially those with constrained resources,...

A botnet refers to a set of compromised machines controlled distantly by an attacker. Botnets are considered the basis of numerous security threats around the world. Command and control (C&C) servers are the backbone of botnet communications, in which bots send a report to the botmaster, and the latter sends attack orders to those bots. Botnets are...

Classification is used to categorize data and produce decisions for several domains. To improve the accuracy of classification, researchers have tended to hybridize the neural network with other metaheuristic algorithms in order to better exploit and explore the search space and thereby solve many different classification problems in an effective m...

ABSTRACT Botnets are considered a serious issue today. They have several negative economic impacts as well. Such impacts are affecting orga- nizations and individuals. Recent botnets–such as Zeus and Citadel’s Conficker–use the Domain Name System (DNS) to avoid detection. These botnets use the DNS server to prevent the network adminis- trator from lo...

In cloud–fog environments, the opportunity to avoid using the upstream communication channel from the clients to the cloud server all the time is possible by fluctuating the conventional concurrency control protocols. Through the present paper, the researcher aimed to introduce a new variant of the optimistic concurrency control protocol. Through t...

Distributed Denial of Service (DDoS) attack is considered as one of the major security threats to the cloud computing environment. This attack hampers the adoption and deployment of cloud computing. DDoS Attack is an explicit attempt by an attacker to prevent and deny access to shared services or resources on a server in a cloud environment by legi...

In today's internet world the internet of things (IoT) is becoming the most significant and developing technology. The primary goal behind the IoT is enabling more secure existence along with the improvement of risks at various life levels. With the arrival of IoT botnets, the perspective towards IoT products has transformed from enhanced living en...

Generally, malware has come to be known as one of the biggest threats, so malware is a program which operates malicious actions and steals information, to specifically identify it as software which is designed specifically to through breaking the system of a computer without consent from the owner. This chapter aimed to study feature selection and...

This article describes how as network traffic grows, attacks on traffic become more complicated and harder to detect. Recently, researchers have begun to explore machine learning techniques with cloud computing technologies to classify network threats. So, new and creative ways are needed to enhance intrusion detection system. This article addresse...

The spread of IoT devices is significantly increasing worldwide with a low design security that makes it more easily compromised than desktop computers. This gives rise to the phenomenon of IoT-based botnet attacks such as Mirai botnet, which have recently emerged as a high-profile threat that continues. Accurate and timely detection methods are re...

Classification is a crucial step in the data mining field. The probabilistic neural network (PNN) is an efficient method developed for classification problems. The success factor of using PNN for classification problems implies in finding the proper weight during classification process. The main goal of this paper is to improve the performance of P...

Botnets are considered a serious issue today. They have several negative economic impacts as well. Such impacts are affecting organizations and individuals. Recent botnets–such as Zeus and Citadel’s Conficker–use the Domain Name System (DNS) to avoid detection. These botnets use the DNS server to prevent the network administrator from locating and...

Leader election is an important issue in distributed systems and communication networks. Many protocols and algorithms that are running on distributed systems need a leader to ensure smooth execution; the leader has the responsibility to synchronize and coordinate the system processes. The absence of the leader makes the system inconsistent, and th...

Spiking neural networks (SNN) represents the third generation of neural network models, it differs significantly from the early neural network generation. The time is becoming the most important input. The presence and precise timing of spikes encapsulate have a meaning such as human brain behavior. However, deferent techniques are therefore requir...

Automatic segmentation of medical images is a key step in contouring during radiotherapy planning. Computed topography (CT) and Magnetic resonance (MR) imaging are the most widely used radiographic techniques in diagnosis, clinical studies and treatment planning. This paper proposed an unsupervised and automatic estimation of the required parameter...