In this paper, we propose a deep learning framework for malware classification. There has been huge increase in the volume of recent years which poses serious security threat to financial institutions, businesses and individuals. order combat proliferation malware, new strategies are essential quickly identify classify samples so that their behavior can be analyzed. Machine approaches becoming popular classifying however, most existing machine methods classification use shallow algorithms...

Deepfake content is created or altered synthetically using artificial intelligence (AI) approaches to appear real. It can include synthesizing audio, video, images, and text. Deepfakes may now produce natural-looking content, making them harder identify. Much progress has been achieved in identifying video deepfakes recent years; nevertheless, most investigations detecting audio have employed the ASVSpoof AVSpoof dataset various machine learning, deep learning algorithms. This research uses...

Due to the rapid development of Internet technologies and social media, sentiment analysis has become an important opinion mining technique. Recent research work described effectiveness different classification techniques ranging from simple rule-based lexicon-based approaches more complex machine learning algorithms. While have suffered lack dictionaries labeled data, fallen short in terms accuracy. This paper proposes integrated framework which bridges gap between achieve better accuracy...

Authorship analysis (AA) is the study of unveiling hidden properties authors from textual data. It extracts an author's identity and sociolinguistic characteristics based on reflected writing styles in text. The process essential for various areas, such as cybercrime investigation, psycholinguistics, political socialization, etc. However, most previous techniques critically depend manual feature engineering process. Consequently, choice set has been shown to be scenario- or...

Efficient and reliable systems are required to detect monitor disasters such as wildfires well notify the people in disaster-affected areas. Internet of Things (IoT) is key paradigm that can address multitude problems related disaster management. In addition, an unmanned aerial vehicles (UAVs)-enabled IoT platform connected via cellular network further enhance robustness management system. The UAV-enabled based on three main research areas: (i) ground network; (ii) communication technologies...

Abstract With time, textual data is proliferating, primarily through the publications of articles. this rapid increase in data, anonymous content also increasing. Researchers are searching for alternative strategies to identify author an unknown text. There a need develop system actual texts based on given set writing samples. This study presents novel approach ensemble learning, DistilBERT , and conventional machine learning techniques authorship identification. The proposed extracts...

There is an alarming increase in the number of cybercrime incidents through anonymous e-mails. The problem e-mail authorship attribution to identify most plausible author from a group potential suspects. Most previous contributions employed traditional classification approach, such as decision tree and Support Vector Machine (SVM), studied effects different writing style features on accuracy. However, little attention has been given ensuring quality evidence. In this paper, we introduce...

Summary The rapid proliferation of Internet things (IoT) devices, such as smart meters and water valves, into industrial critical infrastructures control systems has put stringent performance scalability requirements on modern Supervisory Control Data Acquisition (SCADA) systems. While cloud computing enabled SCADA to cope with the increasing amount data generated by sensors, actuators, there been a growing interest recently deploy edge centers in fog architectures secure low‐latency...

Powerful information acquisition and processing capabilities, coupled with intelligent surveillance reconnaissance features, have contributed to increased popularity of Unmanned Aerial Vehicles (UAVs), also known as drones. In addition the numerous beneficial uses, UAVs been misused launch illegal sometimes criminal activities that pose direct threats individuals, organizations, public safety national security. Despite its importance, "drone forensics" remains a relatively unexplored...

Abstract With time, numerous online communication platforms have emerged that allow people to express themselves, increasing the dissemination of toxic languages, such as racism, sexual harassment, and other negative behaviors are not accepted in polite society. As a result, language identification has critical application natural processing. Numerous academic industrial researchers recently researched using machine learning algorithms. However, Nontoxic comments, including particular...

Aim/Purpose: This study explores the Knowledge, Attitude, and Perception (KAP) towards ChatGPT among university students faculty. It also examines faculty’s readiness to cope with challenges leverage opportunities presented by AI-powered conversational models. Background: Launched on November 30, 2022, took world storm its capability generate high-quality written expressions in a manner. The reactions this innovation varied, from enthusiasm regarding potential enrich students’ learning...

Everyday, security experts face a growing number of events that affecting people well-being, their information systems and sometimes the critical infrastructure. The sooner they can detect understand these threats, more mitigate forensically investigate them. Therefore, need to have situation awareness existing possible effects. However, given large events, it be difficult for analysts researchers handle this flow in an adequate manner answer following questions near-real time: what are...

Recent advances in artificial intelligence have led to deepfake images, enabling users replace a real face with genuine one. images recently been used malign public figures, politicians, and even average citizens. but realistic stir political dissatisfaction, blackmail, propagate false news, carry out bogus terrorist attacks. Thus, identifying from fakes has got more challenging. To avoid these issues, this study employs transfer learning data augmentation technique classify images. For...

The current descriptive study explored teachers' perspectives on integrating artificial intelligence in higher education institutions. study's population was comprised of all males and females (N = 220). Instructors are working various departments the faculty social sciences at public universities Multan, Punjab, Pakistan. A sample one hundred sixty teachers (N= 160), including forty-one (M, 41) nineteen (F, 119), were chosen through convenient sampling from to accomplish this research....

Integrating Internet of Things (IoT) devices into smart homes has necessitated the development novel strategies to address difficulties and complexities cyber-attacks privacy concerns in current digital threat landscape. One unaddressed challenge is lack clarity information collected stored by these IoT homes. The data storage process compliance home appliances, such as security cameras, thermostats, speakers, are examined this study. More specifically, study focuses on sensitive potential...

The Internet provides a convenient platform for cyber criminals to anonymously conduct their illegitimate activities, such as phishing and spamming. As result, in recent years, authorship analysis of anonymous e-mails has received some attention the forensic data mining communities. In this paper, we study problem verification: given set written by suspect along with an e-mail dataset collected from sample population, want determine whether or not is suspect. To address verification textual...

Cybercriminals exploit the opportunities provided by information revolution and social media to communicate conduct underground illicit activities, such as online fraudulence, cyber predation, cyberbullying, hacking, blackmailing, drug smuggling. To combat increasing number of criminal structure content analysis communities can provide insight facilitate cybercrime forensics. In this paper, we propose a framework analyze chat logs for crime investigation using data mining natural language...