Abstract: Devices, systems, and methods of detecting whether an electronic device or computerized device or computer, is being controlled by a legitimate human user, or by an automated cyber-attack unit or malware or automatic script. The system monitors interactions performed via one or more input units of the electronic device. The system searches for abnormal input-user interactions; or for an abnormal discrepancy between: the input-unit gestures that were actually registered by the input unit, and the content that the electronic device reports as allegedly entered via such input units. A discrepancy or abnormality indicates that more-possibly a malware or automated script is controlling the electronic device, rather than a legitimate human user. Optionally, an input-output aberration or interference is injected, in order to check for manual corrective actions that only a human user, and not an automated script, is able to perform.

Abstract: Devices, systems, and methods of user authentication, as well as automatic differentiation between a legitimate user and a cyber-attacker. A system detects that two different accounts of the same computerized service, were accessed by a single computing device over a short period of time. The system may employ various techniques in order to determine automatically whether a legitimate user accessed the two different account, such as, a husband accessing his own bank account and shortly after that accessing also his wife's bank account, or a payroll company accessing bank accounts of two clients for payroll management purposes. Conversely, the system is able to detect that the same user exhibited the same pattern of interactions when operating the two accounts, a pattern of interactions that does not frequently appear in the general population of legitimate users, thereby indicating that the single user is a cyber-attacker.

Abstract: Devices, systems, and methods of contextual mapping of web-page elements and other User Interface elements, for the purpose of differentiating between fraudulent transactions and legitimate transactions, or for the purpose of distinguishing between a fraudulent user and a legitimate user. User Interface elements of a website or webpage or application or other computerized service, are contextually analyzed. A first User Interface element is assigned a low fraud-relatedness score-value, since user engagement with the first User Interface element does not create a security risk or a monetary exposure. A second, different, User Interface element is assigned a high fraud-relatedness score-value, since user engagement with the second User Interface element creates a security risk or a monetary exposure.

Abstract: Devices, systems, and methods of user authentication. A system includes a spatial challenge unit to distinguish between a human user and a non-human user. The spatial challenge unit requires the user to perform one or more spatial operations that modify the spatial properties of an electronic device operated by the user. Correct performance of the required spatial operations, indicates that the user is human. The system also includes a spatial password unit, which tracks a manner in which a human user handles the electronic device while the user enters a password; and then utilizes this user-specific manner for user authentication, by checking whether a manner in which the user enters his password matches a reference manner of password entry or a historical manner of password entry. The system also utilizes sequence of spatial operations or spatial gestures, as a pure spatial password or purely-spatial user-authentication factor.

Abstract: Devices, systems, and methods of password recovery and password reset, as well as resetting or recovering other types of user-authentication factor. A system monitors and tracks user-interactions that are performed by a user of an electronic device or a computerized service. The system defines a user-specific task or challenge, in which the user is requested to enter a phrase or perform a task. A user-specific feature is extracted from the manner in which the user performs the task. Subsequently, that user-specific feature is utilized instead of a security question, in order to verify the identity of the user and to allow the user to perform password reset or to perform a reset of another user-authentication factor; by presenting to the user the same task or a similar task, and monitoring the manner in which the user performs the fresh task.

Abstract: Devices, systems, and methods of detecting user identity, differentiating between users of a computerized service, and detecting a possible attacker. The methods include monitoring of user-side input-unit interactions, in general and in response to an interference introduced to user-interface elements. The monitored interactions are used for detecting an attacker that utilizes a remote access channel; for detecting a malicious automatic script, as well as malicious code injection; to identify a particular hardware assembly; to perform user segmentation or user characterization; to enable a visual login process with implicit two-factor authentication; to enable stochastic cryptography; and to detect that multiple users are utilizing the same subscription account.

Abstract: Devices, systems, and methods of detecting user identity, differentiating between users of a computerized service, and detecting a cyber-attacker. An end-user device (a desktop computer, a laptop computer, a smartphone, a tablet, or the like) interacts and communicates with a server of a computerized server (a banking website, an electronic commerce website, or the like). The interactions are monitored, tracked and logged. User Interface (UI) interferences or irregularities are intentionally introduced to the communication session; and the server tracks the response or the reaction of the end-user to such communication interferences. The system determines whether the user is a legitimate human user, or a cyber-attacker or automated script posing as the legitimate human user. The system further detects click-fraud, and prevents or mitigates Application Distributed Denial-of-Service attacks.

Abstract: Devices, systems, and methods of detecting user identity, differentiating between users of a computerized service, and detecting possible attackers; as well as password-less user authentication, and password-less detection of user identity. A system or a computing device requires a user to perform a particular unique non-user-defined task, the task optionally being an on-screen connect-the-dots task. The system monitors user interactions, extracts user-specific features that characterizes the manner in which the user performs the tasks; and subsequently relies on such user-specific features as a means for user authentication, optionally without utilizing a password or passphrase. Optionally, a user interface anomaly or interference is intentionally introduced in order to elicit the user to perform corrective gestures, which are optionally used for extraction of additional user-specific features.

Abstract: Device, system, and method of detecting identity of a user based on motor-control loop model. A method includes: during a first session of a user who utilizes a pointing device for interacting with a computerized service, monitoring the pointing device dynamics and gestures of the user; based on the monitored dynamics and gestures, estimating parameters that characterize a sensorimotor control loop model of the user; storing in a database a record indicating that the user is associated with the parameters that characterize the sensorimotor control loop model of the user.

Abstract: Device, system, and method of detecting identity of a user based on motor-control loop model. A method includes: during a first session of a user who utilizes a pointing device for interacting with a computerized service, monitoring the pointing device dynamics and gestures of the user; based on the monitored dynamics and gestures, estimating parameters that characterize a sensorimotor control loop model of the user; storing in a database a record indicating that the user is associated with the parameters that characterize the sensorimotor control loop model of the user.

Abstract: Devices, systems, and methods of detecting user identity, differentiating between users of a computerized service, detecting a possible cyber-attacker, detecting a remote access user, and detecting an automated script or malware. The methods include monitoring of user-side input-unit interactions, in general and in response to an interference introduced to user-interface elements. The monitored interactions are used for detecting an attacker that utilizes a remote access channel; for detecting a malicious automatic script, as well as malicious code injection; to identify a particular hardware assembly; to perform user segmentation or user characterization; to enable a visual login process with implicit two-factor authentication; to enable stochastic cryptography; and to detect that multiple users are utilizing the same subscription account.

Abstract: A method for confirming identity of a user of a mobile electronic device, the method including: receiving touch data from a touch-screen of the mobile electronic device; receiving acceleration data from an accelerometer of the mobile electronic device; correlating between the touch data and the acceleration data; based on the correlating, generating a user-specific trait indicative of said user. The method further includes storing a reference value of the user-specific trait, indicative of said user; in a subsequent usage session of the mobile electronic device, generating a current value of the user-specific trait correlating between touch data and acceleration data; and based on a comparison between the current value of the user-specific trait and the reference value of the user-specific trait, determining whether or not a current user of the mobile electronic device is an authorized user of the mobile electronic device.

Abstract: Devices, systems, and methods of detecting user identity, differentiating between users of a computerized service, and detecting a cyber-attacker. An end-user device interacts and communicates with a server of a computerized service, or with a local application or Web-browser running on the end-user device. A usage interference is injected or introduced, or an input/output mismatch or abnormality is created, causing an output displayed on the screen of the end-user device, to be non-matching to the expected or intended output that is typically displayed in response to regular non-interfered user gestures or regular non-interfered user input. The reaction or corrective manual actions of the user are tracked and analyzed, to differentiate among users, or to differentiate between an authorized human user and a human cyber-attacker, or to differentiate between an authorized human user and a computer bot or an automated computerized script.

Abstract: Devices, systems, and methods of detecting user identity, differentiating between users of a computerized service, and detecting a cyber-attacker. An end-user device (a desktop computer, a laptop computer, a smartphone, a tablet, or the like) interacts and communicates with a server of a computerized server (a banking website, an electronic commerce website, or the like). The interactions are monitored, tracked and logged. User Interface (UI) interferences are intentionally introduced to the communication session; and the server tracks the response or the reaction of the end-user to such communication interferences. The system determines whether the user is a legitimate human user; or a cyber-attacker posing as the legitimate human user. The system displays gauges indicating cyber fraud scores or cyber-attack threat-levels.

Abstract: Devices, systems, and methods of detecting user identity, differentiating between users of a computerized service, and detecting a cyber-attacker. An end-user device (a desktop computer, a laptop computer, a smartphone, a tablet, or the like) interacts and communicates with a server of a computerized server (a banking website, an electronic commerce website, or the like). The interactions are monitored, tracked and logged. Communication interferences are intentionally introduced to the communication session; and the server tracks the response or the reaction of the end-user device to such communication interferences. The system determines whether the user is a legitimate human user; or a cyber-attacker posing as a legitimate human user but actually utilizing a Virtual Machine.

Abstract: Devices, systems, and methods of detecting user identity, differentiating between users of a computerized service, and detecting a cyber-attacker. An end-user device (a desktop computer, a laptop computer, a smartphone, a tablet, or the like) interacts and communicates with a server of a computerized server (a banking website, an electronic commerce website, or the like). The interactions are monitored, tracked and logged. User Interface (UI) interferences or irregularities are intentionally introduced to the communication session; and the server tracks the response or the reaction of the end-user to such communication interferences. The system determines whether the user is a legitimate human user, or a cyber-attacker or automated script posing as the legitimate human user. The system further detects click-fraud, and prevents or mitigates Application Distributed Denial-of-Service attacks.

Abstract: Devices, systems, and methods of detecting user identity, differentiating between users of a computerized service, and detecting a cyber-attacker. An end-user device (a desktop computer, a laptop computer, a smartphone, a tablet, or the like) interacts and communicates with a server of a computerized server (a banking website, an electronic commerce website, or the like). The interactions are monitored, tracked and logged. User Interface (UI) interferences or irregularities are intentionally introduced to the communication session; and the server tracks the response or the reaction of the end-user to such communication interferences. The system determines whether the user is a legitimate human user, or a cyber-attacker or automated script posing as the legitimate human user. The system further detects click-fraud, and prevents or mitigates Application Distributed Denial-of-Service attacks.

Abstract: Devices, systems, and methods of detecting user identity, differentiating between users of a computerized service, and detecting a cyber-attacker. An end-user device interacts and communicates with a server of a computerized server (a banking website, an electronic commerce website, or the like). The interactions are monitored, tracked and logged. User Interface (UI) interferences or irregularities are introduced; and the server tracks the response or the reaction of the end-user to such interferences. The system determines whether the user is a legitimate user, or a cyber-attacker or automated script posing as the legitimate user. The system utilizes classification of users into classes or groups, to deduce or predict how a group-member would behave when accessing the service through a different type of device. The system identifies user-specific traits that are platform-independent and thus can be further monitored when the user switches from a first platform to a second platform.

Abstract: Devices, systems, and methods of detecting user identity, differentiating between users of a computerized service, and detecting a cyber-attacker. An end-user device (a desktop computer, a laptop computer, a smartphone, a tablet, or the like) interacts and communicates with a server of a computerized server (a banking website, an electronic commerce website, or the like). The interactions are monitored, tracked and logged. User Interface (UI) interferences are intentionally introduced to the communication session; and the server tracks the response or the reaction of the end-user to such communication interferences. The system determines whether the user is a legitimate human user, or a cyber-attacker posing as the legitimate human user.

Abstract: Devices, systems, and methods of detecting user identity, differentiating between users of a computerized service, and detecting a cyber-attacker. An end-user device interacts and communicates with a server of a computerized server (a banking website, an electronic commerce website, or the like). The interactions are monitored, tracked and logged. User Interface (UI) interferences or irregularities are introduced; and the server tracks the response or the reaction of the end-user to such interferences. The system determines whether the user is a legitimate user, or a cyber-attacker or automated script posing as the legitimate user. The system utilizes classification of users into classes or groups, to deduce or predict how a group-member would behave when accessing the service through a different type of device. The system identifies user-specific traits that are platform-independent and thus can be further monitored when the user switches from a first platform to a second platform.