TY - JOUR
T1 - A cloud-edge based data security architecture for sharing and analysing cyber threat information
AU - Chadwick, David W.
AU - Fan, Wenjun
AU - Costantino, Gianpiero
AU - de Lemos, Rogerio
AU - Di Cerbo, Francesco
AU - Herwono, Ian
AU - Manea, Mirko
AU - Mori, Paolo
AU - Sajjad, Ali
AU - Wang, Xiao Si
N1 - Publisher Copyright:
© 2019
PY - 2020/1
Y1 - 2020/1
N2 - Cyber-attacks affect every aspect of our lives. These attacks have serious consequences, not only for cyber-security, but also for safety, as the cyber and physical worlds are increasingly linked. Providing effective cyber-security requires cooperation and collaboration among all the entities involved. Increasing the amount of cyber threat information (CTI) available for analysis allows better prediction, prevention and mitigation of cyber-attacks. However, organizations are deterred from sharing their CTI over concerns that sensitive and confidential information may be revealed to others. We address this concern by providing a flexible framework that allows the confidential sharing of CTI for analysis between collaborators. We propose a five-level trust model for a cloud-edge based data sharing infrastructure. The data owner can choose an appropriate trust level and CTI data sanitization approach, ranging from plain text, through anonymization/pseudonymization to homomorphic encryption, in order to manipulate the CTI data prior to sharing it for analysis. Furthermore, this sanitization can be performed by either an edge device or by the cloud service provider, depending upon the level of trust the organization has in the latter. We describe our trust model, our cloud-edge infrastructure, and its deployment model, which are designed to satisfy the broadest range of requirements for confidential CTI data sharing. Finally we briefly describe our implementation and the testing that has been carried out so far by four pilot projects that are validating our infrastructure.
AB - Cyber-attacks affect every aspect of our lives. These attacks have serious consequences, not only for cyber-security, but also for safety, as the cyber and physical worlds are increasingly linked. Providing effective cyber-security requires cooperation and collaboration among all the entities involved. Increasing the amount of cyber threat information (CTI) available for analysis allows better prediction, prevention and mitigation of cyber-attacks. However, organizations are deterred from sharing their CTI over concerns that sensitive and confidential information may be revealed to others. We address this concern by providing a flexible framework that allows the confidential sharing of CTI for analysis between collaborators. We propose a five-level trust model for a cloud-edge based data sharing infrastructure. The data owner can choose an appropriate trust level and CTI data sanitization approach, ranging from plain text, through anonymization/pseudonymization to homomorphic encryption, in order to manipulate the CTI data prior to sharing it for analysis. Furthermore, this sanitization can be performed by either an edge device or by the cloud service provider, depending upon the level of trust the organization has in the latter. We describe our trust model, our cloud-edge infrastructure, and its deployment model, which are designed to satisfy the broadest range of requirements for confidential CTI data sharing. Finally we briefly describe our implementation and the testing that has been carried out so far by four pilot projects that are validating our infrastructure.
KW - Cloud security
KW - Cloud-edge trust
KW - Cyber threat information
KW - Data outsourcing
KW - Data security architecture
KW - Edge computing
UR - http://www.scopus.com/inward/record.url?scp=85072553349&partnerID=8YFLogxK
U2 - 10.1016/j.future.2019.06.026
DO - 10.1016/j.future.2019.06.026
M3 - Article
AN - SCOPUS:85072553349
SN - 0167-739X
VL - 102
SP - 710
EP - 722
JO - Future Generation Computer Systems
JF - Future Generation Computer Systems
ER -