The growth and proliferation of computers and computer networks allow businesses to efficiently communicate with their own components as well as with their business partners, customers, and suppliers. However, the flexibility and efficiencies provided by such computers and computer networks come with increasing risks, including security breaches from outside the corporation, accidental release of vital information from within it, and inappropriate use of the LAN, WAN, Internet, or extranet.
In managing the growth of computer networks as well as addressing the various security issues, network managers often turn to network policy management services such as firewall protection, Network Address Translation, spam email filtering, DNS caching, Web caching, virtual private network (VPN) organization and security, and URL blocking for keeping network users from accessing certain web sites through use of the organization's ISP. Each policy management service, however, generally requires a separate device that needs to be configured, managed, and monitored. Furthermore, as an organization grows and spreads across multiple locations, the devices maintained also multiplies, multiplying the associated expenditures and efforts to configure, manage, and monitor the devices.
The solution to this problem is not as simple as just integrating multiple network policy management functions into a single device at each location and allowing each location to share its policy information with other locations. In fact, there are many obstacles and challenges in adopting such an approach. One of these challenges is collecting logs and statistics information from remote private networks in a large distributed policy management system. Conventionally, only raw packet information is logged and saved, generally requiring time-consuming and custom-generated programs to be run on the raw data off-line to produce meaningful reports and statistics.
Accordingly, there remains a need in the art for a network policy management device and method that can effectively collect logs and statistics, even in a large distributed system.