Amazon Technologies, Inc.

Nec Corporation

Mingda Li

Gaurav Saxena

Naresh Chainani

Haifeng Chen

Cristian Lumezanu

Bo Zong

Nipun Arora

Daeki Cho

Ippokratis Pandis

Mengchu Cai

Mohammad Rezaur Rahman

A primary query engine may receive a query and determine whether the query is eligible for performance at a secondary query engine. If eligible, the primary query engine may evaluate the availability of the first query engine to perform the query. The first query engine may determine whether to assign the query to the primary query engine or to the secondary query according to availability evaluation. For queries assigned to the secondary query engine, the primary query engine may send a request to the secondary query engine to being processing of the query.

Dynamically assigning queries to secondary query processing resources

Context dependent execution time prediction may be applied to redirect queries to additional query processing resources. A query to a database may be received at a first query engine. A prediction model for executing queries at the first query engine may be applied to determine predicted query execution time for the first query engine. A prediction model for executing queries at a second query engine may also be applied to determine predicted query execution time for the second query engine. One of the query engines may be selected to perform the query based on a comparison of the predicted query execution times.

Context dependent execution time prediction for redirecting queries

Endpoint security systems and methods include a distance estimation module configured to calculate a travel distance between a source Internet Protocol (IP) address and an IP address for a target network endpoint system from a received packet received by a network gateway system based on time-to-live (TTL) information from the received packet. A machine learning model is configured to estimate an expected travel distance between the source IP address and the target network endpoint system IP address based on a sparse set of known source/target distances. A spoof detection module is configured to determine that the received packet has a spoofed source IP address based on a comparison between the calculated travel distance and the expected travel distance. A security module is configured to perform a security action at the network gateway system responsive to the determination that the received packet has a spoofed source IP address.

Network gateway spoofing detection and mitigation

Methods and systems for mitigating a spoofing-based attack include calculating a travel distance between a source Internet Protocol (IP) address and a target IP address from a received packet based on time-to-live information from the received packet. An expected travel distance between the source IP address and the target IP address is estimated based on a sparse set of known source/target distances. It is determined that the received packet has a spoofed source IP address based on a comparison between the calculated travel distance and the expected travel distance. A security action is performed responsive to the determination that the received packet has a spoofed source IP address.

Neural network based spoofing detection

Endpoint security systems and methods include a distance estimation module configured to calculate a travel distance between a source Internet Protocol (IP) address and an IP address for a target network endpoint system from a received packet received by the target network endpoint system based on time-to-live (TTL) information from the received packet. A machine learning model is configured to estimate an expected travel distance between the source IP address and the target network endpoint system IP address based on a sparse set of known source/target distances. A spoof detection module is configured to determine that the received packet has a spoofed source IP address based on a comparison between the calculated travel distance and the expected travel distance. A security module is configured to perform a security action at the target network endpoint system responsive to the determination that the received packet has a spoofed source IP address.

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Los Angeles, CA, United States of America

Mingda Li