Machine-Learning Based Evaluation of Access Control Lists to Identify Anomalies

Access control lists (ACLs) are a commonly used mechanism to limit the distribution of data in an organization and to protect data from improper access. As ACL size grows one task to be solved is to keep the lists up-to-date and validate that each person in the ACL has appropriate levels of access to data. Currently, managing ACLs and detecting the presence of anomalous individuals in the lists is a manual task. This disclosure describes the application of a trained machine learning model that utilizes as input various factors such as employee roles and organization structure to detect and flag ACLs with dispersion patterns that are likely indicative of potential improper access

The Pirate Party

The “Pirate Party” has started to enter the mainstream. Regional pirate parties with a focus on promoting Internet privacy, digital intellectual property reform, and government transparency began forming around the world in the past few years. In 2010, the Pirate Parties International was formed as an umbrella organization to help support and promote the movement and its ideas. This post was originally published on the Cardozo Arts & Entertainment Law Journal website on February 13, 2012. The original post can be accessed via the Archived Link button above