Abstract: One or more techniques and/or systems are provided for risk assessment. Historical authentication data and/or compromised user account data may be evaluated to identify a set of authentication context properties associated with user authentication sessions and/or a set of malicious account context properties associated with compromised user accounts (e.g., properties indicative of whether a user recently visited a malicious site, created a fake social network profile, logged in from unknown locations, etc.). The set of authentication context properties and/or the set of malicious account context properties may be annotated to create an annotated context property training set that may be used to train a risk assessment machine learning model to generate a risk assessment model. The risk assessment model may be used to evaluate user context properties of a user account event to generate a risk analysis metric indicative of a likelihood the user account event is malicious or safe.

Abstract: One or more techniques and/or systems are provided for risk assessment. Historical authentication data and/or compromised user account data may be evaluated to identify a set of authentication context properties associated with user authentication sessions and/or a set of malicious account context properties associated with compromised user accounts (e.g., properties indicative of whether a user recently visited a malicious site, created a fake social network profile, logged in from unknown locations, etc.). The set of authentication context properties and/or the set of malicious account context properties may be annotated to create an annotated context property training set that may be used to train a risk assessment machine learning model to generate a risk assessment model. The risk assessment model may be used to evaluate user context properties of a user account event to generate a risk analysis metric indicative of a likelihood the user account event is malicious or safe.

Abstract: One or more techniques and/or systems are provided for risk assessment. Historical authentication data and/or compromised user account data may be evaluated to identify a set of authentication context properties associated with user authentication sessions and/or a set of malicious account context properties associated with compromised user accounts (e.g., properties indicative of whether a user recently visited a malicious site, created a fake social network profile, logged in from unknown locations, etc.). The set of authentication context properties and/or the set of malicious account context properties may be annotated to create an annotated context property training set that may be used to train a risk assessment machine learning model to generate a risk assessment model. The risk assessment model may be used to evaluate user context properties of a user account event to generate a risk analysis metric indicative of a likelihood the user account event is malicious or safe.

Abstract: One or more techniques and/or systems are provided for risk assessment. Historical authentication data and/or compromised user account data may be evaluated to identify a set of authentication context properties associated with user authentication sessions and/or a set of malicious account context properties associated with compromised user accounts (e.g., properties indicative of whether a user recently visited a malicious site, created a fake social network profile, logged in from unknown locations, etc.). The set of authentication context properties and/or the set of malicious account context properties may be annotated to create an annotated context property training set that may be used to train a risk assessment machine learning model to generate a risk assessment model. The risk assessment model may be used to evaluate user context properties of a user account event to generate a risk analysis metric indicative of a likelihood the user account event is malicious or safe.

Abstract: The present invention provides a crosslinkable polymer system that can be crosslinked to form a wide variety of polymeric, copolymeric and oligomeric compounds. The crosslinkable system comprises (a) product Q formed from an aromatic ethylenically unsaturated moiety and a first reactive ethylenically unsaturated moiety, and (b) a second reactive ethylenically unsaturated moiety at least partially reacted with the first reactive ethylenically unsaturated moiety.

Abstract: The present invention provides a crosslinkable polymer system that can be crosslinked to form a wide variety of polymeric, copolymeric and oligomeric compounds. The crosslinkable system comprises a product Q formed from an aromatic ethylenically unsaturated moiety and a first reactive ethylenically unsaturated moiety, and a second reactive ethylenically unsaturated moiety at least partially reacted with the first reactive ethylenically unsaturated moiety, and a first terminal moiety comprising a covalently bonded nitroxide containing group.

Abstract: The present invention provides a crosslinkable polymer system that can be crosslinked to form a wide variety of polymeric, copolymeric and oligomeric compounds. The crosslinkable system comprises (a) product Q formed from an aromatic ethylenically unsaturated moiety and a first reactive ethylenically unsaturated moiety, and (b) a second reactive ethylenically unsaturated moiety at least partially reacted with the first reactive ethylenically unsaturated moiety.