Distributed detection of security threats in a remote network management platform
AssigneeServiceNow, Inc.
InventorsDavid Joshua Wiener, Barak Pinchovski, Nir Yariv
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AssigneeServiceNow, Inc.
InventorsDavid Joshua Wiener, Barak Pinchovski, Nir Yariv
Estimating the term…
A system may include a plurality of computational instances dedicated to different managed networks and a central instance communicatively coupled to the plurality of computational instances. A first computing device disposed within a first computational instance may be configured to: obtain a profile of a software application operational within a first managed network to which the first computational instance is dedicated, calculate a threat level of the software application based on the profile, determine that the threat level exceeds a pre-determined threshold, and transmit, to the central instance, an indication that the threat level exceeds the pre-determined threshold. A second computing device disposed within the central instance may be configured to: receive the indication, determine that the software application is also operational within a second managed network to which a second computational instance, and transmit, to the second computational instance, an indication that the threat level exceeds the pre-determined threshold.
A remote network management platform comprising:
A computer-implemented method of operating a remote network management platform, comprising:
An article of manufacture including a non-transitory computer-readable medium, having stored thereon program instructions that, upon execution by a remote network management platform, cause the remote network management platform to perform operations comprising:
Dependencies are inferred from the claim text.
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Network architectures or network communication protocols for network security: for managing network security; network security policies in general
Services specially adapted for wireless communication networks; Facilities therefor: subscription-based services using application servers or…
Learning methods: supervised learning
Machine learning: ensemble learning
About 13 years 8 months of term left · ends 28 Jun 2040 (estimated)
Computer security threats take a variety of forms, and the impact of each threat can be anywhere from negligible, to inconvenient, to catastrophic. Types of threats include spyware, denial of service (DOS) attacks, phishing attempts, Trojan horses, worms, and viruses, just to name a few. The software that perpetrates these threats is referred to generally as “malware.”
Unless measures are taken to address security threats, malware can be used to obtain private, confidential, and/or personal information, inappropriately use computing resources, or to prevent or limit legitimate use of computing resources. Therefore, in addition to attempts to prevent the introduction of spyware to a system (e.g., through the use of firewalls, host-level security, and other security policies), it can be important to also periodically scan the system for known or suspected threats. Once a threat is identified, it can be further investigated, and then potentially disabled or eradicated.
Given their large and expanding scales, enterprise networks are particularly vulnerable to security threats. With hundreds, thousands, or even hundreds of thousands of devices and applications to manage, mitigating security risks in just a single enterprise can be challenging.
FIG. 1 illustrates a schematic drawing of a computing device, in accordance with example embodiments.
FIG. 2 illustrates a schematic drawing of a server device cluster, in accordance with example embodiments.
FIG. 3 depicts a remote network management architecture, in accordance with example embodiments.
Example methods, devices, and systems are described herein. It should be understood that the words “example” and “exemplary” are used herein to mean “serving as an example, instance, or illustration.” Any embodiment or feature described herein as being an “example” or “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments or features unless stated as such. Thus, other embodiments can be utilized and other changes can be made without departing from the scope of the subject matter presented herein.
Accordingly, the example embodiments described herein are not meant to be limiting. It will be readily understood that the aspects of the present disclosure, as generally described herein, and illustrated in the figures, can be arranged, substituted, combined, separated, and designed in a wide variety of different configurations. For example, the separation of features into “client” and “server” components may occur in a number of ways.
Further, unless context suggests otherwise, the features illustrated in each of the figures may be used in combination with one another. Thus, the figures should be generally viewed as component aspects of one or more overall embodiments, with the understanding that not all illustrated features are necessary for each embodiment.