Scalable Intrusion Detection with Recurrent Neural Networks

The one-size-fits-all format adopted by most existing intrusion detection systems, has not succeeded in eradicating network attacks that are ever-changing in their nature. Furthermore, such IDS is not as economically sustainable for all organizations with unique levels of financial buoyancy, operational complexity, and network traffic. Nevertheless, a scalable IDS, with its several over-reaching advantages that range from adjustable economic costs to easy architectural design and applicability, from fast communication traffic to improved management of IDS, meets the match of the ever-changing nature of network attacks, as well as meeting unique sizes and economic buoyancy of organizations.

Provided by: Science and Development Network (SciDev.Net) Topic: Security Date Added: Jan 2011 Format: PDF

Find By Topic