Transactions on Engineering and Computing Sciences

Crimebots and Lawbots: Cyberwarfare Powered by Generative Artificial Intelligence

Peter E Murray — 2025-03-15

Crimebots are fueling the cybercrime pandemic by exploiting artificial intelligence (AI) to facilitate crimes such as fraud, misrepresentation, extortion, blackmail, identity theft, and security breaches. These AI-driven criminal activities pose a significant threat to individuals, businesses, online transactions, and even the integrity of the legal system. Crimebots enable unjust exonerations and wrongful convictions by fabricating evidence, creating deepfake alibis, and generating misleading crime reconstructions. In response, lawbots have emerged as a counterforce, designed to uphold justice. Legal professionals use lawbots to collect and analyze evidence, streamline legal processes, and enhance the administration of justice. To mitigate the risks posed by both crimebots and lawbots, many jurisdictions have established ethical guidelines promoting the responsible use of AI by lawyers and clients. Approximately 1.34% of lawyers have been involved in AI-related legal disputes, often revolving around issues such as fees, conflicts of interest, negligence, ethical violations, evidence tampering, and discrimination. Additional concerns include fraud, confidentiality breaches, harassment, and the misuse of AI for criminal purposes. For lawbots to succeed in the ongoing battle against crimebots, strict adherence to complex AI regulations is essential. Ensuring compliance with these guidelines minimizes malpractice risks, prevents professional sanctions, preserves client trust, and upholds the ethical and legal professional standards of excellence.

A Cognitive Analysis and Life Prediction Through AI Algorithm of Control Arm Using Manufacturing and Vehicle Driving Data

Byeong Sam Kim — 2025-03-11

This study aims to enhance vehicle safety by predicting the life perdition of control arms, critical suspension components. Traditional inspection methods have limitations in accurately predicting failures, leading to unexpected accidents occurring both before and after the vehicle's expected lifespan. The increasing complexity of control arm manufacturing, coupled with the growing volume of vehicle driving data and heightened competition, necessitates a more sophisticated approach to quality and safety. This system implements autonomy and intelligence of the production system by utilizing intelligent production system, big data, and artificial intelligence technologies, and supports optimal decision-making in real time. Data collection: There collected various sensor data from the production site, system data, MES system data, etc. In data refinement, data analysis and algorithm extraction of the Control Arm are performed, and the collected data is refined and preprocessed to be processed into a form suitable for analysis. Database construction: We build a relational database or NoSQL database to systematically manage data. This study represents a crucial step towards a more proactive and data-driven approach to vehicle safety and manufacturing. By integrating AI and big data technologies, the automotive industry can move towards a future characterized by minimized accidents and optimized production processes. Finally, we derived the results of predicting and optimizing the remaining useful life prediction of the remaining product.

Artificial Intelligence, Cybersecurity, and a Growing Ethical Dilemma

Steven Arvin — 2025-03-15

Currently, cybersecurity threats, particularly cyber-attacks, are a growing concern. As time goes on, it becomes increasingly challenging to hinder these attacks. Nevertheless, a new participant has entered the arena, known as artificial intelligence (AI). AI offers a way for cybersecurity experts to counteract the ever-evolving attacks. By utilizing techniques such as identifying threats and automated responses to incidents, organizations can enhance their security measures and safeguard confidential data. Despite the numerous advantages of adopting AI, it is equally important to remain vigilant about potential risks. In recent years, the rapid growth in cybersecurity threats has necessitated the development of more effective measures to protect sensitive information and systems. This paper delves into the ethical concerns of AI in cybersecurity, stressing the crucial balance between technological innovation and maintaining ethical standards.

Bridging the Gap between Business Practice and Data Science Approaches

Jiangping Wang — 2025-03-08

In data science and analytics, the driving force is not on how to perform analytics tasks or how to use advanced technology in analytics projects. Business problems and goals should always drive the overall approaches. Projects and applications in data science and analytics should serve business goals and help business decision making. In this paper, a case study that serves various directions in answering business questions is presented.