Amazon Technologies, Inc.

Hardik Navin Nagda

Nima Sharifi Mehr

William Frederick Hingle Kruse

Ashish Rangole

Bharath Mukkati Prakash

Kunal Chadha

Chenxi Zhang

Jeffrey John Wierer

Kai Zhao

Radu Mihai Berciu

Matthew John Campagna

Arvinth Ravi

Phillip H Pruett, Iv

Prathiban Mohanasundaram

Sameer Choudhary

Nikhil Shah

Vishwas Narendra

James Zuber

Nishant Jain

Tyler Michael Jung

Bryan T Wilkinson

Zaher Dannawi

Rajesh Sampath

Suchindra Yogendra Agarwal

Pierre Vigneras

Janko Jerinic

Vijayasarathy Kannan

Nicholas Jacob Essenburg

Liming Ye

Anirudh Mattur Radhakrishna

Gergory Branchek Roth

David Grant Emeny-Smith

Systems and methods are provided for efficiently maintaining a transaction sequence witness service to ensure that requests to read data provide consistent results across all storage nodes in a distributed system. When a storage node receives a request for a data object, the node may obtain&#x2014;from transaction sequence witness service&#x2014;the latest sequence number associated with the object. If the sequence number indicates the object has been modified in the period of time since the currently stored version was stored, the node can obtain the current version from persistent storage.

Witness service for ensuring data consistency in a distributed storage system

A computing resource service receives a request to access the service and perform various actions. In response to the request, the computing resource service obtains a set of active policies that are applicable to the request. As a result of the service determining that the set of active policies fail to provide sufficient permissions for fulfillment of the request, the service determines if an enforcement policy is available that is applicable to the request. The service evaluates the request using the enforcement policy such that if the enforcement policy includes permissions sufficient for fulfillment of the request, the request is fulfilled.

Access control monitoring through policy management

A policy/resource decommissioning service determines whether a resource has been inactive for a period of time greater than at least one period of time threshold for decommissioning. If the resource has been inactive greater than a first period of time threshold, the service disables the resource such that requests to access the resource are denied. If the resource has been inactive for a period of time greater than a second threshold, longer than the first period of time threshold, the service archives the resource. The service deletes the resource if the inactivity period of the resource is greater than a third period of time threshold, where the third period of time threshold is longer than the first and the second period of time thresholds.

Automatic account resource and policy decommissioning

A customer's resources are protected from malicious or accidental deletion or termination. In some embodiments anomaly detection is used for identifying suspicious activities, which is combined with options to restore previously deleted resources. To define and detect anomalies, resource profiles are generated indicative of how resources are being used, and user profiles of how users use resources of the compute service provider. Instead of immediately deleting a resource, a temporary marker can be placed on the resource. The temporary marker blocks attempts to access the resource just as if the resource was deleted. However, the resource can easily be recovered by simply removing the marker. When a deletion event is identified as anomalous, an alert is generated to the customer. Upon receiving the alert, customers can opt to restore the resource that has been deleted, which will remove the marker.

Anamoly detection and recovery of a corrupted computing resource

Sensitive data can be obfuscated before being provided for processing (i.e., aggregating, sorting, grouping, or transforming) using a pair of keys to generate a token that contains the sensitive data. The token can include a synthetic initialization vector, generated using a first key, and a ciphertext portion including the sensitive data encrypted under a second key. This tokenization can be performed by a data service or by an intermediate service that acts as an overlay or proxy for the underlying data service. The tokenized data can be provided for processing, and can remain tokenized until being received by an entity or system having access to at least the second key. A receiving entity with access to the second key can decrypt the ciphertext to obtain the plaintext, and if the first key is available the entity can perform a further integrity check on the tokenized data.

Data obfuscation

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Seattle, WA, United States of America

Hardik Navin Nagda