Abstract: An account protection service to prevent user login or other protected endpoint request abuse. In one embodiment, the service collects user recognition data, preferably for each login attempt (e.g. data about the connection, session, and other relevant context), and it constructs a true user profile for each such user over time, preferably using the recognition data from successful logins. The profile evolves as additional recognition data is collected from successful logins. The profile is a model of what the user “looks like” to the system. For a subsequent login attempt, the system then calculates a true user score. This score represents how well the current user recognition data matches the model represented by the true user profile. The user recognition service is used to drive policy decisions and enforcement capabilities.

Abstract: An account protection service to prevent user login or other protected endpoint request abuse. In one embodiment, the service collects user recognition data, preferably for each login attempt (e.g. data about the connection, session, and other relevant context), and it constructs a true user profile for each such user over time, preferably using the recognition data from successful logins. The profile evolves as additional recognition data is collected from successful logins. The profile is a model of what the user “looks like” to the system. For a subsequent login attempt, the system then calculates a true user score. This score represents how well the current user recognition data matches the model represented by the true user profile. The user recognition service is used to drive policy decisions and enforcement capabilities. Preferably, user recognition works in association with bot detection in a combined solution.

Abstract: An account protection service to prevent user login or other protected endpoint request abuse. In one embodiment, the service collects user recognition data, preferably for each login attempt (e.g. data about the connection, session, and other relevant context), and it constructs a true user profile for each such user over time, preferably using the recognition data from successful logins. The profile evolves as additional recognition data is collected from successful logins. The profile is a model of what the user “looks like” to the system. For a subsequent login attempt, the system then calculates a true user score. This score represents how well the current user recognition data matches the model represented by the true user profile. The user recognition service is used to drive policy decisions and enforcement capabilities. Preferably, user recognition works in association with bot detection in a combined solution.

Abstract: An account protection service to prevent user login or other protected endpoint request abuse. In one embodiment, the service collects user recognition data, preferably for each login attempt (e.g. data about the connection, session, and other relevant context), and it constructs a true user profile for each such user over time, preferably using the recognition data from successful logins. The profile evolves as additional recognition data is collected from successful logins. The profile is a model of what the user “looks like” to the system. For a subsequent login attempt, the system then calculates a true user score. This score represents how well the current user recognition data matches the model represented by the true user profile. The user recognition service is used to drive policy decisions and enforcement capabilities. Preferably, user recognition works in association with bot detection in a combined solution.

Abstract: An account protection service to prevent user login or other protected endpoint request abuse. In one embodiment, the service collects user recognition data, preferably for each login attempt (e.g. data about the connection, session, and other relevant context), and it constructs a true user profile for each such user over time, preferably using the recognition data from successful logins. The profile evolves as additional recognition data is collected from successful logins. The profile is a model of what the user “looks like” to the system. For a subsequent login attempt, the system then calculates a true user score. This score represents how well the current user recognition data matches the model represented by the true user profile. The user recognition service is used to drive policy decisions and enforcement capabilities. Preferably, user recognition works in association with bot detection in a combined solution.