PDF malware detection based on optimizable decision trees

Q Abu Al-Haija, A Odeh, H Qattous - Electronics, 2022 - mdpi.com
Portable document format (PDF) files are one of the most universally used file types. This
has incentivized hackers to develop methods to use these normally innocent PDF files to …

A new framework for fraud detection in bitcoin transactions through ensemble stacking model in smart cities

N Nayyer, N Javaid, M Akbar, A Aldegheishem… - IEEE …, 2023 - ieeexplore.ieee.org
Bitcoin has a reputation of being used for unlawful activities, such as money laundering,
dark web transactions, and payments for ransomware in the context of smart cities …

[HTML][HTML] Cybersecurity Attacks and Detection Methods in Web 3.0 Technology: A Review

B Alotaibi - Sensors, 2025 - mdpi.com
Web 3.0 marks the beginning of a new era for the internet, characterized by distributed
technology that prioritizes data ownership and value expression. Web 3.0 aims to empower …

Meticulously intelligent identification system for smart grid network stability to optimize risk management

Q Abu Al-Haija, AA Smadi, MF Allehyani - Energies, 2021 - mdpi.com
The heterogeneous and interoperable nature of the cyber-physical system (CPS) has
enabled the smart grid (SG) to operate near the stability limits with an inconsiderable …

Scams and solutions in cryptocurrencies—A survey analyzing existing machine learning models

LP Krishnan, I Vakilinia, S Reddivari, S Ahuja - Information, 2023 - mdpi.com
With the emergence of cryptocurrencies and Blockchain technology, the financial sector is
turning its gaze toward this latest wave. The use of cryptocurrencies is becoming very …

[图书][B] Cyber security for next-generation computing technologies

IU Khan, M Ouaissa, M Ouaissa, Z Abou El Houda… - 2024 - books.google.com
This book sheds light on the cyber security challenges associated with nextgeneration
computing technologies, emphasizing the serious threats posed to individuals, businesses …

[PDF][PDF] Empirical evaluation of machine learning performance in forecasting cryptocurrencies

L Al Hawi, S Sharqawi, QA Al-Haija, A Qusef - Journal of Advances in …, 2023 - jait.us
Cryptocurrencies like Bitcoin are one of today's financial system's most contentious and
difficult technological advances. This study aims to evaluate the performance of three …

Unveiling bitcoin network attack using deep reinforcement learning with Boltzmann exploration

M Shetty, S Tamane - Peer-to-Peer Networking and Applications, 2025 - Springer
This study tackles the critical issue of identifying ransomware transactions within the Bitcoin
network. These transactions threaten the stability and security of the cryptocurrency world …

Deep Set Classifier for Financial Forensics: An application to detect money laundering

J Pan - arXiv preprint arXiv:2207.07863, 2022 - arxiv.org
Financial forensics has an important role in the field of finance to detect and investigate the
occurrence of finance related crimes like money laundering. However, as with other forms of …

Integrating blockchain and machine learning for enhanced anti-money laundering system

KM Shafin, S Reno - International Journal of Information Technology, 2024 - Springer
Money laundering is a serious threat to global financial systems, causing instability and
inflation, and especially hurting middle-class savings. This paper suggests a new way to …