TY - GEN
T1 - Ransomware Detection in the Internet of Things (IoT)
T2 - 7th International Women in Data Science Conference at Prince Sultan University, WiDS-PSU 2024
AU - Albassam, Sarah Tawfiq
AU - Alamoudi, Khadijah Ahmed
AU - Alshalawi, Shahad Saad
AU - Alghamdi, Aseel Khaled
AU - Alnashwan, Hessah Abdulmohsen
AU - Alsaber, Sarah Mohammed
AU - Saqib, Nazar Abbas
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Ransomware attacks cause significant security risks to organizations and individuals, which can lead to financial loss and reputational damage. Therefore, it is essential to mitigate such attacks. As the number of connected devices to the Internet of Things (IoT) increases, particularly in sensitive networks, the number vulnerabilities explored in the IoT landscape increases as well. These vulnerabilities present opportunities for malicious actors to exploit and launch attacks, including ransomware. Security measures in IoT against recent attacks, ransomware attacks, in particular, are one of the concerns that face IoT. Yet, developing ransomware detection and mitigation methods becomes crucial to prevent the attack from being executed, by implementing early response to avoid any losses that ransomware can cause. This paper will review existing ransomware detection methods in IoT environments, faced challenges, and solutions. Furthermore, a comprehensive comparison of detection methods based on the classification of the ransomware, limitations, and addressed challenges will be presented.
AB - Ransomware attacks cause significant security risks to organizations and individuals, which can lead to financial loss and reputational damage. Therefore, it is essential to mitigate such attacks. As the number of connected devices to the Internet of Things (IoT) increases, particularly in sensitive networks, the number vulnerabilities explored in the IoT landscape increases as well. These vulnerabilities present opportunities for malicious actors to exploit and launch attacks, including ransomware. Security measures in IoT against recent attacks, ransomware attacks, in particular, are one of the concerns that face IoT. Yet, developing ransomware detection and mitigation methods becomes crucial to prevent the attack from being executed, by implementing early response to avoid any losses that ransomware can cause. This paper will review existing ransomware detection methods in IoT environments, faced challenges, and solutions. Furthermore, a comprehensive comparison of detection methods based on the classification of the ransomware, limitations, and addressed challenges will be presented.
KW - IoT
KW - Ransomware
KW - Ransomware Detection
UR - https://www.scopus.com/pages/publications/85198643326
U2 - 10.1109/WiDS-PSU61003.2024.00046
DO - 10.1109/WiDS-PSU61003.2024.00046
M3 - Conference contribution
AN - SCOPUS:85198643326
T3 - Proceedings - 2024 7th International Women in Data Science Conference at Prince Sultan University, WiDS-PSU 2024
SP - 183
EP - 190
BT - Proceedings - 2024 7th International Women in Data Science Conference at Prince Sultan University, WiDS-PSU 2024
A2 - Rehm, Amjad
A2 - Azar, Ahmad Taher
A2 - Saba, Tanzila
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 3 March 2024 through 4 March 2024
ER -