Izzat Alsmadi

• PhD in software engineering
• Professor (Associate) at Texas A&M University – San Antonio

The proliferation of text generation applications in social networks has raised concerns about the authenticity of online content. Large language models like GPTs can now produce increasingly indistinguishable text from human-written content. While learning-based classifiers can be trained to differentiate between human-written and machine-generate...

Objective: Explore deep learning applications in predictive analytics for public health data, identify challenges and trends, and then understand the current landscape. Materials and Methods: A systematic literature review was conducted in June 2023 to search articles on public health data in the context of deep learning, published from the incepti...

The integration of large language models (LLMs) into public transit systems presents a transformative opportunity to enhance urban mobility. This study explores the potential of LLMs to revolutionize public transportation management within the context of San Antonio's transit system. Leveraging the capabilities of LLMs in natural language processin...

Online social networks (OSNs) are inundated with an enormous daily influx of news shared by users worldwide. Information can originate from any OSN user and quickly spread, making the task of fact-checking news both time-consuming and resource-intensive. To address this challenge, researchers are exploring machine learning techniques to automate fa...

The integration of large language models into public transit systems represents a significant advancement in urban transportation management and passenger experience. This study examines the impact of LLMs within San Antonio's public transit system, leveraging their capabilities in natural language processing, data analysis, and real time communica...

Large language models (LLMs) have revolutionized how we interact with machines. However, this technological advancement has been paralleled by the emergence of "Mallas," malicious services operating underground that exploit LLMs for nefarious purposes. Such services create malware, phishing attacks, and deceptive websites, escalating the cyber secu...

Search engines are competing to be seen as universal, consistent and language independent. In principle, users searching for information through the Internet should get consistent information regardless of the language of the words they are searching for and regardless of the language of the matching or the relevant documents. Nevertheless, the lan...

The increasing frequency and sophistication of cyber-attacks pose significant threats to organizational entities and critical national infrastructure, leading to substantial financial and operational consequences. Detecting such attacks early and accurately remains a complex endeavour, compounded by challenges in intrusion detection system (IDS) de...

Cloud Service Providers, exemplified by industry leaders like Google Cloud Platform, Microsoft Azure, and Amazon Web Services, deliver a dynamic array of cloud services in an ever-evolving landscape. This sector is witnessing substantial growth, with enterprises such as Netflix and PayPal heavily relying on cloud infrastructure for various needs su...

Motivated by the rise of new GPT language models and their impact on society, both realized and potential, we evaluated several potential impacts of those models, in particular bias and misinformation issues. Bias in machine learning models refers to their tendencies to make certain decisions more often than expected. Humans exhibit numerous biases...

This book series, “Chronicle of Computing,” aims to facilitate increased opportunities for cross-fertilization across the disciplines and topics in Computing. Book proposals are solicited for consideration in all disciplines of Computing and including, but not limited to, Artificial Intelligence, Computer Science & Engineering, Information Systems...

Air writing is one of the essential fields that the world is turning to, which can benefit from the world of the metaverse, as well as the ease of communication between humans and machines. The research literature on air writing and its applications shows significant work in English and Chinese, while little research is conducted in other languages...

Abstractive summarization is distinguished by using novel phrases that are not found in the source text. However, most previous research ignores this feature in favour of enhancing syntactical similarity with the reference. To improve novelty aspects, we have used multiple warm-started models with varying encoder and decoder checkpoints and vocabul...

Abstractive summarization is distinguished by using novel phrases that are not found in the source text. However, most previous research ignores this feature in favour of enhancing syntactical similarity with the reference. To improve novelty aspects, we have used multiple warm-started models with varying encoder and decoder checkpoints and vocabul...

Deep neural networks have shown remarkable performance on a wide range of classification tasks and applications. However, the large model size and the enormous size of the training dataset make the training process slow and often limited by the computing resources. To overcome this limitation, distributed training can be used to accelerate the proc...

With advanced neural network techniques, language models can generate content that looks genuinely created by humans. Such advanced progress benefits society in numerous ways. However, it may also bring us threats that we have not seen before. A neural text detector is a classification model that separates machine-generated text from human-written...

The process of collecting business, software, or information systems’ requirements in general and security requirements in particular can take different approaches, i.e., structured or unstructured. At the end of the requirements collection process or stage, we may have one or more examples of the following problems that trigger the need for a thor...

In cyber threat analysis, knowledge of internal and external vulnerabilities related to a particular system or organization is analyzed and matched against real-world cyberattacks relevant to that system or organization. Figure 9.1 shows a model that describes threat analysis components:

Model optimization in deep learning (DL) and neural networks is concerned about how and why the model can be successfully trained towards one or more objective functions. The evolutionary learning or training process continuously considers the dynamic parameters of the model. Many researchers propose a deep learning-based solution by randomly selec...

With the continuous increase in cyberattacks over the past few decades, the quest to develop a comprehensive, robust, and effective intrusion detection system (IDS) in the research community has gained traction. Many of the recently proposed solutions lack a holistic IDS approach due to explicitly relying on attack signature repositories, outdated...

Automatic Text Summarization (ATS) models yield outcomes with insufficient coverage of crucial details and poor degrees of novelty. The first issue resulted from the lengthy input, while the second problem resulted from the characteristics of the training dataset itself. This research employs the divide-and-conquer approach to address the first iss...

Neural text detectors aim to decide the characteristics that distinguish neural (machine-generated) from human texts. To challenge such detectors, adversarial attacks can alter the statistical characteristics of the generated text, making the detection task more and more difficult. Inspired by the advances of mutation analysis in software developme...

As the Internet of Things (IoT) continues to grow, cyberattacks are becoming increasingly common. The security of IoT networks relies heavily on intrusion detection systems (IDSs). The development of an IDS that is accurate and efficient is a challenging task. As a result, this challenge is made more challenging by the absence of balanced datasets...

The coronavirus (COVID‐19) started in China in 2019, has spread rapidly in every single country and has spread in millions of cases worldwide. This paper presents a proposed approach that involves identifying the relative impact of COVID‐19 on a specific gender, the mortality rate in specific age, investigating different safety measures adopted by...

Detection of malware and security attacks is a complex process that can vary in its details and analysis activities. As part of the detection process, malware scanners try to categorize a malware once it is detected under one of the known malware categories (e.g. worms, spywares, viruses, etc.). However, many studies and researches indicate problem...

Essentially all forms of online communication involve the use of cryptography to ensure that only the intended recipient of a message can read it. Nearly every protocol includes message encryption as a part of its standard. Whether it is https, sh, or S[MIME, the most common types of connections have encryption enabled by default. Most computers ca...

Deep Learning (DL) models are widely used in machine learning due to their performance and abilityto deal with large datasets while producing high accuracy and performance metrics. The size ofsuch datasets and the complexity of DL models cause such models to be complex, consuming largeamount of resources and time to train. Many recent libraries and...

The Internet, and many of the related things, hence the term Internet of Things, IoT, continue to expand and take more roles in human lives. Indeed, this enables us to be connected with our devices and the environment. The Internet also enabled us to be continuously informed about the status of our cars, homes, health, family, friends, etc. However...

Data analytics projects span all types of domains and applications. Researchers publish results using certain datasets and classification models. They present results with a summary of the performance metrics of their evaluated classifiers. However, readers and evaluators may not be able to compare results from the different papers for several reas...

The majority of the intrusion detection solutions proposed using machine learning and deep learning approaches are based on known attack classes only. Comprehensive threat detection systems should consider both known and unknown attacks. Rapidly changing network environment and the advanced tools and techniques used by adversaries to launch new sop...

For hackers and many actors in the cyber world, crises can make opportunities. With the continuous spread of Covid-19 pandemics, new waves of cyber-attacks are witnessed. Attackers are taking advantage of possibly increasing vulnerabilities due to lack of awareness of best security practices when using online resources by many new users. While the...

Deep Learning (DL) models are widely used in machine learning due to their performance and ability to deal with large datasets while producing high accuracy and performance metrics. The size of such datasets and the complexity of DL models cause such models to be complex, consuming large amount of resources and time to train. Many recent libraries...

Availability is one of the three main goals of information security. This paper contributes to systems’ availability by introducing an optimization model for the adaptation (controlling the capturing, coding, and sending features of the video communication system) of live broadcasting of video to limited and varied network bandwidth and/or limited...

The intelligence extracted through machine learning algorithms (MLAs) plays an important role in most of the smart applications and systems around us. Those MLAs make intelligence decisions on behalf of humans based on knowledge extracted from historical and current data. With such growth of MLA roles in human lives, the rise of adversarial attempt...

Firewalls have been one of the most important networks access control mechanisms for several decades. Their ability to filter traffic flowing through them has been instrumental to the task of keeping malicious activity from occurring on the network. This crucial role to the network means that properly configuring the firewall is of the utmost impor...

Cyber threat behaviors can take different forms, approaches, and goals. For threat detection systems, it is essential to monitor URLs known for previous malicious attempts. It is also vital to study attack behaviors for the ultimate goal of designing autonomous threat detection systems. We collected a large dataset of URL links annotated toward tha...

Machine learning algorithms represent the intelligence that controls many information systems and applications around us. As such, they are targeted by attackers to impact their decisions. Text created by machine learning algorithms has many types of applications, some of which can be considered malicious especially if there is an intention to pres...

Using data analytics in the problem of Intrusion Detection and Prevention Systems (IDS/IPS) is a continuous research problem due to the evolutionary nature of the problem and the changes in major influencing factors. The main challenges in this area are designing rules that can predict malware in unknown territories and dealing with the complexity...

The growing use of media has led to the development of several machine learning (ML) and natural language processing (NLP) tools to process the unprecedented amount of social media content to make actionable decisions. However, these ML and NLP algorithms have been widely shown to be vulnerable to adversarial attacks. These vulnerabilities allow ad...

Today, deep learning approaches are widely used to build Intrusion Detection Systems for securing IoT environments. However, the models’ hidden and complex nature raises various concerns, such as trusting the model output and understanding why the model made certain decisions. Researchers generally publish their proposed model’s settings and perfor...

The significance of an intrusion detection system (IDS) in networks security cannot be overstated in detecting and responding to malicious attacks. Failure to detect large-scale attacks like DDoS not only makes the networks vulnerable, but a failure of critical lifesaving medical and industrial equipment can also put human lives at risk. Lack of av...

Firewalls and network access controls play important roles in security control and protection. Those firewalls may create an incorrect sense or state of protection if they are improperly configured. One of the major configuration problems in firewalls is related to misconfiguration in the access control roles added to the firewall that will control...

Abstract—Phishing attacks have witnessed a rapid increase thanks to the matured social engineering techniques, COVID-19 pandemic, and recently adversarial deep learning techniques. Even though adversarial phishing attacks are recent, attackers are crafting such attacks by considering context, testing different attack paths, then selecting paths...

The growing use of social media has led to the development of several Machine Learning (ML) and Natural Language Processing(NLP) tools to process the unprecedented amount of social media content to make actionable decisions. However, these MLand NLP algorithms have been widely shown to be vulnerable to adversarial attacks. These vulnerabilities all...

The vast majority of digital currency transactions rely on a blockchain framework to ensure quick and accurate execution. As such, understanding how a blockchain works is vital to understanding the dynamics of cryptocurrency operations. One of the key benefits of this type of system is the exhaustive records captured in a given marketplace. The int...

The detection of events from online social networks is a recent, evolving field that attracts researchers from across a spectrum of disciplines and domains. Here we report a time-series analysis for predicting events. In particular, we evaluated the frequency distribution of top n-grams of terms over time, focusing on two indicators: high-frequency...

Validation of software requirements is a primary phase in requirements engineering that ensures requirements match the target system with the intended needs of the acquirer. It aims to detect and correct errors that prevail in the specified requirements. Although there are tremendous requirements validation approaches, some software may fail becaus...

Automatic Text Summarization (ATS) is an important area in Natural Language Processing (NLP) with the goal of shortening a long text into a more compact version by conveying the most important points in a readable form. ATS applications continue to evolve and utilize effective approaches that are being evaluated and implemented by researchers. Stat...

The constant development of interrelated computing devices and the emergence of new network technologies have dramatically increased the Internet of Things (IoT) devices. Intrusion Detection Systems (IDSs) play a significant role in securing IoT networks. Designing an IDS that performs with maximum accuracy with minimum false alarms is a challengin...

The power of information and information exchange defines the current Internet and Online Social Networks (OSNs). With such power and influence, individuals and entities expose those networks to different types of false information. This paper proposes several classification models based on Quora insincere questions; a dataset released by Kaggle. W...

The internet, Online Social Networks (OSNs) and smart phones enable users to create tremendous amount of information. Users who search for general or specific knowledge may not have these days problems of information scarce but misinformation. Misinformation nowadays can refer to a continuous spectrum between what can be seen as "facts" or "truth",...

Nowadays, security is becoming number one priority for governments, organization, companies, and individuals. Security is all about protecting critical and valuable assets. Protecting valuable and critical assets, whether they are tangible or intangible, is a process that can be ranged from being unsophisticated to being very sophisticated. Securit...

With the continuous expansion and evolution of IoT applications, attacks on those IoT applications continue to grow rapidly. In this systematic literature review (SLR) paper, our goal is to provide a research asset to researchers on recent research trends in IoT security. As the main driver of our SLR paper, we proposed six research questions relat...

Classic security methods become less effective against the Internet of Things (IoT) cyber-attacks, such as cryptography. An urgent need for real-time and lightweight detection of cyber-attacks is needed to secure IoT networks. This demand is achieved by a reliable and efficient intrusion detection system (IDS) that can meet IoT environments' high s...

The research field of adversarial machine learning witnessed a significant interest in the last few years. A machine learner or model is secure if it can deliver main objectives with acceptable accuracy, efficiency, etc. while at the same time, it can resist different types and/or attempts of adversarial attacks. This paper focuses on studying aspe...

Technology innovations have led to modern society’s inevitable use of data to execute day-to-day operations. However, by its nature, these technologies are centralized, which makes them targets to malicious hackers and jeopardizes citizens’ privacy. Blockchain increases security and privacy; it limits who can access the data, and it gives citizens...

Recently, different machine learning-based detection systems are proposed to detect DDoS saturation attacks in Software-defined Networking (SDN). Meanwhile, different research studies highlight the vulnerabilities of adapting such systems in SDN. For instance, an adversary can fool the machine learning classifiers of these systems by crafting speci...

Increased usage of bots through the Internet in general, and social networks in particular, has many implications related to influencing public opinion. Mechanisms to distinguish humans from machines span a broad spectrum of applications and hence vary in their nature and complexity. Here we use several public Twitter datasets to build a model that...

The exposure of Internet of Things (IoT) networks led to an exponential increase in traffic size. Thus, the traffic data meet the 5V big data model, which results in the rise of many cyber threats and the appearance of new security challenges. Intrusion Detection Systems (IDS) need to apply dimensionality reduction to handle the enormous data size...

word count: 184 Abstract The new Coronavirus, (A.K.A. COVID-19) created a global crisis that impacted the world not only in health perspectives but in most aspects of life. Many teams across the globe from difference, science, and health domains continue as of the time of writing this paper to find proper treatments for COVID-19. In this scope, our...

Universities compete to improve their ranking in the different ranking systems and expend resources toward this goal. Higher rankings attract elite students, research funds, government and public support, among other benefits. However, perhaps the most influential ranking system in U.S. contexts—the U.S. News & World Report Best Colleges rankings—h...

Background In health and medicine, people heavily use the Internet to search for information about symptoms, diseases, and treatments. As such, the Internet information can simulate expert medical doctors, pharmacists, and other health care providers. Aim This article aims to evaluate a dataset of search terms to determine whether search queries a...

In an era of billions of dollars in outstanding student loan debt, researchers have posited that the U.S. News & World Report rankings continue to be an influential source of information for prospective students, yet these rankings do not include college affordability metrics in their ranking algorithm. As a result, this study performed a series of...

Software management chapter considers security-related activities throughout the lifecycle of software development. Software applications exist in all applications around us. Vulnerabilities in those software applications can cause serious issues. Those vulnerabilities may come from software design, construction, testing, or usage.

Risks in Information systems and technologies come from different dimensions in addition to security such as financial risks, managerial risks, people risks, etc. The cycle of risk and security management include 4 main stages: (1) Risks identifications, (2) Risk assessment and prioritizations, (3) Risk mitigations (e.g., prevention, tolerance, etc...

Information Systems Security (ISS) is a broad term that covers all security aspects in enterprises, including system analysis and design method, manual information systems, managerial issues, and both societal and ethical problems. Information systems security management (ISSM) evolved recently to be a discipline by itself. Some universities offer...

Information Systems exist these days in all business domains. They form core business IT infrastructures. Security and vulnerability issues in information systems can come from the systems themselves, applications developed on those systems, how those systems are configured or administered or users of those systems. In this chapter, we will survey...

Training and certification in cyber security are key elements to provide alternative education to colleges and universities. Many jobs require certain types of certificates. Due to the nature of this field, continuous training and practice are necessary to ensure that employees are gaining knowledge on recent trends and technologies. Cyber awarenes...

Data Envelopment Analysis (DEA) has been applied creatively in various study domains to compare and evaluate different Decision Making Units (DMUs) based on multiple input–output attributes. In this paper, the performance of Jordanian public hospitals is assessed via a methodology combining DEA with data mining methods, specifically, clustering. In...

News claims that travel the Internet and online social networks (OSNs) originate from different, sometimes unknown sources, which raises issues related to the credibility of those claims and the drivers behind them. Fact-checking websites such as Snopes, FactCheck, and Emergent use human evaluators to investigate and label news claims, but the proc...

This textbook covers security controls and management. It is for courses in cyber security education that follow National Initiative for Cybersecurity Education (NICE) work roles and framework that adopt the Competency-Based Education (CBE) method. The book follows the CBE general framework, meaning each chapter contains three sections, knowledge a...

Securing the cyberspace is a challenging task that needs well educated and trained professionals. Developing a workforce that can hold the burden of monitoring and ensure cyberspace security is becoming prominent nowadays. Accordingly, developing effective cybersecurity programs is gaining more focus in academia and industry. This paper examines th...