Enabling Cyber Security Data Sharing for Large-scale Enterprises Using Managed Security Services.

IEEE Conference on Communications and Network Security(2018)

引用 11|浏览16
暂无评分
摘要
Large enterprises and organizations from both private and public sectors typically outsource a platform solution, as part of the Managed Security Services (MSSs), from 3rd party providers (MSSPs) to monitor and analyze their data containing cyber security information. Sharing such data among these large entities is believed to improve their effectiveness and efficiency at tackling cybercrimes, via improved analytics and insights. However, MSS platform customers currently are not able or not willing to share data among themselves because of multiple reasons, including privacy and confidentiality concerns, even when they are using the same MSS platform. Therefore any proposed mechanism or technique to address such a challenge need to ensure that sharing is achieved in a secure and controlled way. In this paper, we propose a new architecture and use case driven designs to enable confidential, flexible and collaborative data sharing among such organizations using the same MSS platform. MSS platform is a complex environment where different stakeholders, including authorized MSSP personnel and customers' own users, have access to the same platform but with different types of rights and tasks. Hence we make every effort to improve the usability of the platform supporting sharing while keeping the existing rights and tasks intact. As an innovative and pioneering attempt to address the challenge of data sharing in the MSS platform, we hope to encourage further work to follow so that confidential and collaborative sharing eventually happens among MSS platform customers.
更多
查看译文
关键词
Cyber security,privacy,policy,information,data sharing,data anonymization,data sanitization,data encryption,managed security service,managed security service provider,large-scale enterprise,organization,architecture,design,component,diagram,use case,multi-tenant,cloud service
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要