TY - GEN
T1 - Security-aware resource allocation in clouds
AU - Al-Haj, Saeed
AU - Al-Shaer, Ehab
AU - Ramasamy, Hari Govind V.
PY - 2013
Y1 - 2013
N2 - Elasticity and economic considerations make Infrastructure-as-a-Service (IaaS) clouds attractive propositions for hosting enterprise IT applications. However, for prospective cloud customers, that potential is tempered by concerns, chief among them being security. We consider the problem of resource allocation in IaaS clouds while factoring in reachability and access control requirements of the cloud virtual machines (VMs). We describe a security-aware resource allocation framework that allows for effective enforcement of defense-in-depth for cloud VMs by determining (1) the grouping of VMs into security groups based on the similarity of their reachability requirements, and (2) the placement of virtual machines in a manner that reduces residual risks for individual VMs as well as security groups. We formalize security-aware resource allocation as a Constraint Satisfaction Problem (CSP), which can be solved using widely available Satisfiability Modulo Theories (SMT) solvers. Our experimental evaluation shows the effectiveness of our approach in reducing risk and improving manageability of security configurations for the cloud VMs.
AB - Elasticity and economic considerations make Infrastructure-as-a-Service (IaaS) clouds attractive propositions for hosting enterprise IT applications. However, for prospective cloud customers, that potential is tempered by concerns, chief among them being security. We consider the problem of resource allocation in IaaS clouds while factoring in reachability and access control requirements of the cloud virtual machines (VMs). We describe a security-aware resource allocation framework that allows for effective enforcement of defense-in-depth for cloud VMs by determining (1) the grouping of VMs into security groups based on the similarity of their reachability requirements, and (2) the placement of virtual machines in a manner that reduces residual risks for individual VMs as well as security groups. We formalize security-aware resource allocation as a Constraint Satisfaction Problem (CSP), which can be solved using widely available Satisfiability Modulo Theories (SMT) solvers. Our experimental evaluation shows the effectiveness of our approach in reducing risk and improving manageability of security configurations for the cloud VMs.
UR - https://www.scopus.com/pages/publications/84891951882
U2 - 10.1109/SCC.2013.36
DO - 10.1109/SCC.2013.36
M3 - Conference contribution
AN - SCOPUS:84891951882
SN - 9780768550268
T3 - Proceedings - IEEE 10th International Conference on Services Computing, SCC 2013
SP - 400
EP - 407
BT - Proceedings - IEEE 10th International Conference on Services Computing, SCC 2013
T2 - 2013 IEEE 10th International Conference on Services Computing, SCC 2013
Y2 - 27 June 2013 through 2 July 2013
ER -