Systems and methods for capturing or analyzing time-series data

a time-series data and time-series technology, applied in the field of data processing, can solve the problems of increasing difficulty in detecting malicious activity carried on the network, more difficult to assess whether any particular portion of the data conveyed will cause harm, and detection systems fail to assess network traffi
US20140101762A1Inactive Publication Date: 2014-04-10VECTRA NETWORKS
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Patent Information

Authority / Receiving Office
US · United States
Patent Type
Applications(United States)
Current Assignee / Owner
VECTRA NETWORKS
Publication Date
2014-04-10
Estimated Expiration
Not applicable · inactive patent

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Abstract

Provided is an intrusion detection system configured to detect anomalies indicative of a zero-day attack by statistically analyzing substantially all traffic on a network in real-time. The intrusion detection system, in some aspects, includes a network interface; one or more processors communicatively coupled to the network interface; system memory communicatively coupled to the processors. The system memory, in some aspects, stores instructions that when executed by the processors cause the processors to perform steps including: buffering network data from the network interface in the system memory; retrieving the network data buffered in the system memory; applying each of a plurality of statistical or machine-learning intrusion-detection models to the retrieved network data; aggregating intrusion-likelihood scores from each of the intrusion-detection models in an aggregate score, and upon the aggregate score exceeding a threshold, outputting an alert.
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Description

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] The present application is a continuation of U.S. patent application Ser. No. 13 / 648,176, filed Oct. 9, 2012.BACKGROUND

[0002] 1. Field of the Invention

[0003] The present disclosure relates generally to data processing and, more specifically, to capturing, replaying, and analyzing time-series data.

[0004] 2. Description of the Related Art

[0005] In recent years, it has become increasingly difficult to detect malicious activity carried on networks. The volume of traffic moving through a given node on modern networks is substantially larger than even in the recent past, making it more difficult to assess whether any particular portion of the data conveyed will cause harm. Further, the sophistication of attacks has increased substantially, as entities with greater resources, such as organized crime and state actors, have directed resources towards developing new modes of attack. Many existing intrusion detection systems fail to assess network traff...

Claims

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