Yaman Salem

Work place: Department of Natural Engineering and Technology Sciences, Arab American University (AAUP), Ramallah, Palestine

E-mail: y.salem3@student.aaup.edu

Website:

Research Interests:

Biography

Yaman Salem works as a 'Content Development and Authoring Subject Matter Expert' at Security First Company in Dubai. Her professional journey in information security started in 2015 as an 'Associate Information Security Consultant at IT Security C&T company, progressing to the role of 'Security Awareness Content Team Leader,' managing an information security content team. She gained an MSc in Cybercrime and Digital Forensics from the Arab American University in Palestine in 2022, and she has a bachelor's in Telecommunications Engineering. She is certified in CIHE, CPTE, CCNA Security, CCNA, and Network+.

Author Articles
Towards Digital Forensics 4.0: A Multilevel Digital Forensics Framework for Internet of Things (IoT) Devices

By Yaman Salem Majdi Owda Amani Yousef Owda

DOI: https://doi.org/10.5815/ijwmt.2024.02.03, Pub. Date: 8 Apr. 2024

The Internet of Things (IoT) driven Industrial Revolution 4.0 (IR4.0) and this is impacting every sector of the global economy. With IoT devices, everything is computerized. Today's digital forensics is no longer limited to computers, mobiles, or networks. The current digital forensics landscape demands a significantly different approach. The traditional digital forensics frameworks no longer meet the current requirements. Therefore, in this paper, we propose a novel framework called “Multi-level Artifact of Interest Digital Forensics Framework for IoT” (MAoIDFF-IoT). The keynote "Multi-level" aims to cover all levels of the IoT architecture. Our novel IoT digital forensics framework focuses on the Artifact of Interest (AoI). Additionally, it proposes the action/detection matrix. It encompasses the advantages of the previous frameworks while introducing new features specifically designed to make the framework suitable for current and future IoT investigation scenarios. The MAoIDFF-IoT framework is designed to face the challenges of IoT forensic analysis and address the diverse architecture of IoT environments. Our proposed framework was evaluated through real scenario experiments. The evaluation of the experimental results reveals the superiority of our framework over existing frameworks in terms of usability, inclusivity, focus on the (AoI), and acceleration of the investigation process.

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