Nominum, Inc.

Akamai Technologies, Inc.

Robert S Wilbourn

Paul O'Leary

James Paugh

Thanh Nguyen

Iurii Iuzifovich

Hongliang Liu

Ali Fakeri-Tabrizi

Mikael Kullberg

Robert Thomas Halley

Srinivas Avirneni

Brian Wellington

Erik D Fears

Yuriy Yuzifovich

Hongche Liu

Tom C Tovar

Jonathan P Wood

Vivian Neou

Handong Wu

Eileen Liu

Colleen Shannon

Sam Bretheim

Gopala Tumuluri

Provided is a method for domain name ranking. An example method includes receiving Domain Name System (DNS) data, which includes domain names. The DNS data is processed to obtain multiple metric values for each of the domain names. The metric values can include a query count (QC), a client count (CC), and a network count (NC). The method proceeds with calculating a score for each of the domain names based on the metric values. The calculation can be performed using the following equation: Score=NC&#xb7;CC&#xb7;(1+log(QC)). Furthermore, the method ranks the domain names based on the score for each of the domain names. The ranking can be based on normalization of the scores or based on converting the scores into respective percentile ranks.

DNS-based ranking of domain names

The present disclosure is related to a computer-implemented method and system for distinguishing human-driven Doman Name System (DNS) queries from Machine-to-Machine (M2M) DNS queries. The method includes receiving a DNS query, which includes a domain name, generating a probability score for the domain name based on one or more predetermined rules, and categorizing the DNS query as a human-driven DNS query or a M2M DNS query based on the probability score.

Distinguishing human-driven DNS queries from machine-to-machine DNS queries

The disclosure is related to computer-implemented methods for domain name scoring. In one example, the method includes receiving a request to provide a reputation score of a domain name, receiving input data associated with the domain name, extracting a plurality of features from the input data and the domain name, generating a feature vector based on the plurality of features, and calculating the reputation score of the domain name by a machine-learning classifier based on a graph database, which includes feature vectors associated with at least a plurality of reference domain names, a plurality of servers, a plurality of domain name owners, and so forth. In another example, the method can calculate the reputation score by finding a similarity between the feature vector and one of domain name clusters in the graph database. The reputation score represents a probability that the domain name is associated with malicious activity.

System for domain reputation scoring

A computer-implemented method for detecting anomalies in DNS requests comprises receiving a plurality of DNS requests generated within a predetermined period. The predetermined period includes a plurality of DNS data fragments. The method further includes receiving a first DNS request and selecting a plurality of second DNS requests from the plurality of DNS requests such that each of the second DNS requests is a subset of the first DNS request. The method also includes calculating a count value for each of the DNS data fragments, where each of the count values represents a number of instances the second DNS requests appear within one of the DNS data fragments. In some embodiments, the count values for each of the DNS data fragments can be normalized. The method further includes determining an anomaly trend, for example, based on determining that at least one of the count values exceeds a predetermined threshold value.

Analyzing DNS requests for anomaly detection

The present disclosure is related to a computer-implemented method and system for distinguishing human-driven Domain Name System (DNS) queries from Machine-to-Machine (M2M) DNS queries. The method includes receiving a DNS query, which includes a domain name, generating a probability score for the domain name based on one or more predetermined rules, and categorizing the DNS query as a human-driven DNS query or a M2M DNS query based on the probability score.

Provided is a method for delegation of local content delivery service. The method includes receiving a Domain Name System (DNS) query from a client to resolve a domain name to a network address associated with content provider by a content provider, determining that distribution of the content has been delegated by a content provider to a local content server associated with an Internet Service Provider (ISP), and based on predetermined criteria, resolving the domain name to the local content server. The resolution can include responding to the DNS query with an answer from a caching server, and returning, to the client, the answer pointing to the local content server, wherein upon receiving the answer, the client can establish a data communication channel with the local content server. The content can be downloaded to the local content server upon a request received by a provisioning system associated with the ISP.

Delegation of content delivery to a local service

A network protection method is provided. The network protection method may include receiving a Domain Name System (DNS) request, logging the DNS request, classifying the DNS request based on an analysis of a DNS name associated with the DNS request, taking a security action based on the classification, analyzing network traffic after taking the security action, and providing substantially real-time feedback associated with the network traffic to improve future DNS request classifications. The method may further include receiving a DNS response and logging the DNS response. The analysis of the DNS name may include receiving DNS data related to the DNS name from a plurality of sources, receiving reputation data related to the plurality of sources, scoring each of the plurality of sources based on the reputation data, and aggregating the DNS data related to the DNS name based on the scoring.

Network protection service

Redirecting DNS traffic includes receiving, at an Internet improvement platform, a DNS query issued from an Internet application running on a computing device. The Internet navigation platform determines an appropriate response to the DNS query. The response is then executed. Characteristics relative to the query and to the result of a served page may be recorded and later referenced by the Internet improvement platform.

Internet improvement platform with learning module

Systems and methods for resolving domain name system (DNS) queries are provided herein. Methods may include receiving a DNS query from a DNS client via a DNS server, responsive to the DNS query, generating the DNS response utilizing the at least one policy associated with the view, providing the DNS response to the DNS client from which the DNS query was received, and storing the DNS response in a shared cache, the shared cache including previously generated DNS responses that are available to the DNS server, wherein previously generated DNS responses may be provided to DNS clients upon receiving a DNS query corresponding to at least one of the previously generated DNS responses.

Growing community of inventors

Palo Alto, CA, United States of America

Robert S Wilbourn