A data center is an infrastructure that supports Internet service. Cloud comput the face of the Internet service infrastructure, enabling even small organizations to quickly ng is rapidly changing build Web and mobile...A data center is an infrastructure that supports Internet service. Cloud comput the face of the Internet service infrastructure, enabling even small organizations to quickly ng is rapidly changing build Web and mobile applications for millions of users by taking advantage of the scale and flexibility of shared physical infrastructures provided by cloud computing. In this scenario, multiple tenants save their data and applications in shared data centers, blurring the network boundaries between each tenant in the cloud. In addition, different tenants have different security requirements, while different security policies are necessary for different tenants. Network virtualization is used to meet a diverse set of tenant-specific requirements with the underlying physical network enabling multi-tenant datacenters to automatically address a large and diverse set of tenants requirements. In this paper, we propose the system implementation of vCNSMS, a collaborative network security prototype system used n a multi-tenant data center. We demonstrate vCNSMS with a centralized collaborative scheme and deep packet nspection with an open source UTM system. A security level based protection policy is proposed for simplifying the security rule management for vCNSMS. Different security levels have different packet inspection schemes and are enforced with different security plugins. A smart packet verdict scheme is also integrated into vCNSMS for ntelligence flow processing to protect from possible network attacks inside a data center network展开更多
Internet security problems remain a major challenge with many security concerns such as Internet worms, spam, and phishing attacks. Botnets, well-organized distributed network attacks, consist of a large number of bot...Internet security problems remain a major challenge with many security concerns such as Internet worms, spam, and phishing attacks. Botnets, well-organized distributed network attacks, consist of a large number of bots that generate huge volumes of spam or launch Distributed Denial of Service （DDoS） attacks on victim hosts. New emerging botnet attacks degrade the status of Internet security further. To address these problems, a practical collaborative network security management system is proposed with an effective collaborative Unified Threat Management （UTM） and traffic probers. A distributed security overlay network with a centralized security center leverages a peer-to-peer communication protocol used in the UTMs collaborative module and connects them virtually to exchange network events and security rules. Security functions for the UTM are retrofitted to share security rules. In this paper, we propose a design and implementation of a cloud-based security center for network security forensic analysis. We propose using cloud storage to keep collected traffic data and then processing it with cloud computing platforms to find the malicious attacks. As a practical example, phishing attack forensic analysis is presented and the required computing and storage resources are evaluated based on real trace data. The cloud- based security center can instruct each collaborative UTM and prober to collect events and raw traffic, send them back for deep analysis, and generate new security rules. These new security rules are enforced by collaborative UTM and the feedback events of such rules are returned to the security center. By this type of close-loop control, the collaborative network security management system can identify and address new distributed attacks more quickly and effectively.展开更多
基金supported in part by the National Key Basic Research and Development(973)Program of China(Nos.2013CB228206 and 2012CB315801)the National Natural Science Foundation of China(Nos.61233016 and 61140320)+1 种基金supported by the Intel Research Council with the title of "Security Vulnerability Analysis based on Cloud Platform with Intel IA Architecture"Huawei Corp
文摘A data center is an infrastructure that supports Internet service. Cloud comput the face of the Internet service infrastructure, enabling even small organizations to quickly ng is rapidly changing build Web and mobile applications for millions of users by taking advantage of the scale and flexibility of shared physical infrastructures provided by cloud computing. In this scenario, multiple tenants save their data and applications in shared data centers, blurring the network boundaries between each tenant in the cloud. In addition, different tenants have different security requirements, while different security policies are necessary for different tenants. Network virtualization is used to meet a diverse set of tenant-specific requirements with the underlying physical network enabling multi-tenant datacenters to automatically address a large and diverse set of tenants requirements. In this paper, we propose the system implementation of vCNSMS, a collaborative network security prototype system used n a multi-tenant data center. We demonstrate vCNSMS with a centralized collaborative scheme and deep packet nspection with an open source UTM system. A security level based protection policy is proposed for simplifying the security rule management for vCNSMS. Different security levels have different packet inspection schemes and are enforced with different security plugins. A smart packet verdict scheme is also integrated into vCNSMS for ntelligence flow processing to protect from possible network attacks inside a data center network
基金supported by the National Key Basic Research and Development (973) Program of China(Nos.2011CB302805,2011CB302505,2012CB315801,and2013CB228206)the National Natural Science Foundation of China(No.61233016)supported by Intel Research Councils UPO program with the title of Security Vulnerability Analysis Based on Cloud Platform
文摘Internet security problems remain a major challenge with many security concerns such as Internet worms, spam, and phishing attacks. Botnets, well-organized distributed network attacks, consist of a large number of bots that generate huge volumes of spam or launch Distributed Denial of Service （DDoS） attacks on victim hosts. New emerging botnet attacks degrade the status of Internet security further. To address these problems, a practical collaborative network security management system is proposed with an effective collaborative Unified Threat Management （UTM） and traffic probers. A distributed security overlay network with a centralized security center leverages a peer-to-peer communication protocol used in the UTMs collaborative module and connects them virtually to exchange network events and security rules. Security functions for the UTM are retrofitted to share security rules. In this paper, we propose a design and implementation of a cloud-based security center for network security forensic analysis. We propose using cloud storage to keep collected traffic data and then processing it with cloud computing platforms to find the malicious attacks. As a practical example, phishing attack forensic analysis is presented and the required computing and storage resources are evaluated based on real trace data. The cloud- based security center can instruct each collaborative UTM and prober to collect events and raw traffic, send them back for deep analysis, and generate new security rules. These new security rules are enforced by collaborative UTM and the feedback events of such rules are returned to the security center. By this type of close-loop control, the collaborative network security management system can identify and address new distributed attacks more quickly and effectively.
