Internet of Things (IoT) devices have increased rapidly in recent years, revolutionizing many industries, including healthcare, manufacturing, and transportation, and bringing benefits to both individuals and industries. However, this increase in IoT device usage has exposed IoT ecosystems to numerous security threats and digital forensic challenges. This thesis investigates the most common IoT security threats and attacks, students’ awareness of them and their mitigation strategies, and the key challenges associated with IoT forensic investigations. A mixed-method approach is adopted in this thesis combining a literature review and a survey study. The survey assesses students’ knowledge of IoT security threats, mitigation techniques, and perceptions of the most effective ways to enhance IoT security. The survey also emphasizes the importance of user training and awareness in mitigating IoT threats, highlighting the most effective strategies, such as stronger regulations and improved device security by manufacturers. The literature review provides a comprehensive overview of the most common IoT security threats and attacks, such as malware, malicious code injection, replay attacks, Man in the Middle (MITM), botnets, and Distributed Denial of Service Attacks (DDoS). The mitigation techniques to these threats are overviewed as well as real-world incidents and crimes, such as the Mirai botnet, St. Jude Medical implant cardiac devices hack, and the Verkada hack, are examined to understand the consequences of these attacks. Moreover, this work also highlights the definition and the process of digital and IoT forensics, the importance of IoT forensics, and different data sources in IoT ecosystems. The key challenges associated with IoT forensics and how they impact the effectiveness of digital investigations in the IoT ecosystem are examined in detail. Overall, the results of this work contribute to ongoing research to improve IoT device security, highlight the importance of increased awareness and user training, and address the challenges associated with IoT forensic investigations.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:lnu-121500 |
| Date | January 2023 |
| Creators | Al Allaf, Abdulrahman, Totonji, Waseem |
| Publisher | Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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