Abstract: A method, computer system, and a computer program for malware detection in containerized environments are provided. The method may include monitoring operation of a container image by receiving a plurality of system calls performed during the operation of the container image. The method further includes comparing the plurality of system calls to prior container behavior associated with previous operation of a prior container image, and identifying a deviation from the prior container behavior. The method further includes isolating a subset of the plurality of system calls and classifying the subset to a malware class of a plurality of malware classes.

Abstract: A technique for privacy-preserving homomorphic inferencing using a neural network having an activation function, such as a non-linear high-degree polynomial. The network is trained to learn input features of an input feature vector together with their associated inverses. During inferencing, an encrypted data point is received at the network. The data point comprises an input feature vector that has been extended with a set of one or more additional feature values, the set of one or more additional feature values having been generated by applying a normalized inverse function to respective one or more features in the feature vector. Homomorphic inferencing is performed on the encrypted data point using the machine learning model to generate an encrypted result, which is then returned. By applying the normalized inverse function, the high-degree polynomial can use any value of an input feature during inferencing, whether the value is within or outside of a particular input range.

Abstract: A method, a structure, and a computer system for expanding database column names. Exemplary embodiments may include identifying glossary terms that sufficiently syntactically match a column name, extracting partial expansions from the glossary terms, selectively combining a set of the partial expansions, and storing the combined set of partial expansions in association with the column name.

Abstract: A method, a structure, and a computer system for expanding database column names. Exemplary embodiments may include identifying glossary terms that sufficiently syntactically match a column name, extracting partial expansions from the glossary terms, selectively combining a set of the partial expansions, and storing the combined set of partial expansions in association with the column name.

Abstract: A technique for privacy-preserving homomorphic inferencing using a neural network having an activation function, such as a non-linear high-degree polynomial. The network is trained to learn input features of an input feature vector together with their associated inverses. During inferencing, an encrypted data point is received at the network. The data point comprises an input feature vector that has been extended with a set of one or more additional feature values, the set of one or more additional feature values having been generated by applying a normalized inverse function to respective one or more features in the feature vector. Homomorphic inferencing is performed on the encrypted data point using the machine learning model to generate an encrypted result, which is then returned. By applying the normalized inverse function, the high-degree polynomial can use any value of an input feature during inferencing, whether the value is within or outside of a particular input range.

Abstract: A method, computer system, and a computer program for malware detection in containerized environments are provided. The method may include monitoring operation of a container image by receiving a plurality of system calls performed during the operation of the container image. The method further includes comparing the plurality of system calls to prior container behavior associated with previous operation of a prior container image, and identifying a deviation from the prior container behavior. The method further includes isolating a subset of the plurality of system calls and classifying the subset to a malware class of a plurality of malware classes.

Abstract: Detecting sequences of computer-executed operations, including training a BLSTM to determine forward and backward probabilities of encountering each computer-executed operations within a training set of consecutive computer-executed operations in forward and backward execution directions of the operations, and identifying reference sequences of operations within the training set where for each given one of the sequences the forward probability of encountering a first computer-executed operation in the given sequence is below a predefined lower threshold, the forward probability of encountering a last computer-executed operation in the given sequence is above a predefined upper threshold, the backward probability of encountering the last computer-executed operation in the given sequence is below the predefined lower threshold, and the backward probability of encountering the first computer-executed operation in the given sequence is above the predefined upper threshold, and where the predefined lower threshold

Abstract: Detecting sequences of computer-executed operations, including training a BLSTM to determine forward and backward probabilities of encountering each computer-executed operations within a training set of consecutive computer-executed operations in forward and backward execution directions of the operations, and identifying reference sequences of operations within the training set where for each given one of the sequences the forward probability of encountering a first computer-executed operation in the given sequence is below a predefined lower threshold, the forward probability of encountering a last computer-executed operation in the given sequence is above a predefined upper threshold, the backward probability of encountering the last computer-executed operation in the given sequence is below the predefined lower threshold, and the backward probability of encountering the first computer-executed operation in the given sequence is above the predefined upper threshold, and where the predefined lower threshold

Abstract: Embodiments of the present invention may provide the capability to identify security breaches in computer systems from clustering properties of clusters generated based on monitored behavior of users of the computer systems by using techniques that provide improved performance and reduced resource requirements. For example, behavior of users or resources may be monitored and analyzed to generate clusters and train clustering models. Labeling information relating to some user or resource may be received. When users or resources are clustered and when a cluster contains some labeled users/resources then an anomaly score can be determined for a user/resource belonging to the cluster. A user or resource may be detected to be an outlier of at least one cluster to which the user or resource has been assigned, and an alert indicating detection of the outlier may be generated.

Abstract: Embodiments of the present systems and methods may provide data watermarking without reliance on error-tolerant fields, thereby providing for the incorporation of watermarks in data that was not considered suitable for watermarking. For example, in an embodiment, a computer-implemented method for watermarking data may comprise inserting watermark data into a field that requires format-preserving encryption.

Abstract: Embodiments of the present systems and methods may provide data watermarking without reliance on error-tolerant fields, thereby providing for the incorporation of watermarks in data that was not considered suitable for watermarking. For example, in an embodiment, a computer-implemented method for watermarking data may comprise inserting watermark data into a field that requires format-preserving encryption.

Abstract: A system for detecting cyber security events can include a processor to generate a first set of a plurality of time series and aggregate statistics based on a plurality of properties corresponding to user actions for each user in a set of users. The processor can also separate the set of users into a plurality of clusters based on the first set of the plurality of time series or aggregate statistics for each user and assign an identifier to each of the plurality of clusters. Additionally, the processor can generate a second set of a plurality of time series based on properties of the plurality of clusters, wherein the properties of a cluster correspond to a membership, a diameter, and a centroid and detect an anomaly based on a new value stored in the second set of the time series. Furthermore, the processor can execute a prevention instruction.

Abstract: Methods, computing systems and computer program products implement embodiments of the present invention that include assigning, to multiple users, respective sets of original roles for accessing data stored on a computer system, and performing, in response to requests from the users, multiple operations on the data. While performing the multiple operations on the data, a transaction log is generated that includes a plurality of entries, each of the entries storing attributes of a given operation. Based on the entries in the log file, a respective set of learned roles for respective users is identified, and the respective sets of the learned roles are assigned to the respective users.

Abstract: A system for detecting cyber security events can include a processor to generate a first set of a plurality of time series and aggregate statistics based on a plurality of properties corresponding to user actions for each user in a set of users. The processor can also separate the set of users into a plurality of clusters based on the first set of the plurality of time series or aggregate statistics for each user and assign an identifier to each of the plurality of clusters. Additionally, the processor can generate a second set of a plurality of time series based on properties of the plurality of clusters, wherein the properties of a cluster correspond to a membership, a diameter, and a centroid and detect an anomaly based on a new value stored in the second set of the time series. Furthermore, the processor can execute a prevention instruction.

Abstract: Embodiments of the present invention may provide the capability to identify security breaches in computer systems from clustering properties of clusters generated based on monitored behavior of users of the computer systems by using techniques that provide improved performance and reduced resource requirements. For example, behavior of users or resources may be monitored and analyzed to generate clusters and train clustering models. Labeling information relating to some user or resource may be received. When users or resources are clustered and when a cluster contains some labeled users/resources then an anomaly score can be determined for a user/resource belonging to the cluster. A user or resource may be detected to be an outlier of at least one cluster to which the user or resource has been assigned, and an alert indicating detection of the outlier may be generated.

Abstract: Methods, computing systems and computer program products implement embodiments of the present invention that include defining multiple primitives, each of the primitives including ranking and unranking methods. Two or more of the multiple primitives are selected, and an operation is performed on the selected primitives, thereby defining a complex format. Upon an encryption processor receiving a data record including a plaintext, the complex format is applied to the plaintext, thereby generating a non-reversible token. In some embodiments, the generated token is transmitted a remote computer.

Abstract: Methods, computing systems and computer program products implement embodiments of the present invention that include assigning, to multiple users, respective sets of original roles for accessing data stored on a computer system, and performing, in response to requests from the users, multiple operations on the data. While performing the multiple operations on the data, a transaction log is generated that includes a plurality of entries, each of the entries storing attributes of a given operation. Based on the entries in the log file, a respective set of learned roles for respective users is identified, and the respective sets of the learned roles are assigned to the respective users.

Abstract: A method comprising using at least one hardware processor for: receiving input from a user with respect to masking of a data element in one or more documents of a java script object notation (JSON) type, wherein the input comprises: an identifier of the data element, and one or more constraints for masking the data element based on the hierarchy of the one or more documents of the JSON-type; and generating a masking rule for the one or more documents of the JSON-type based on the input.

Abstract: Methods, computing systems and computer program products implement embodiments of the present invention that include defining multiple primitives, each primitive including ranking and unranking methods. Two or more of the multiple primitives are selected, and an operation is performed on the selected primitives, thereby defining a complex format. Upon and encryption processor receiving a data record comprising a plaintext, the complex format is applied to the plaintext, thereby generating a ciphertext, and the ciphertext is transmitted to a remote computer. Upon receiving the ciphertext, the remote computer can apply the complex format to the received ciphertext, thereby regenerating the plaintext.

Abstract: Methods, computing systems and computer program products implement embodiments of the present invention that include defining multiple primitives, each of the primitives including ranking and unranking methods. Two or more of the multiple primitives are selected, and an operation is performed on the selected primitives, thereby defining a complex format. Upon an encryption processor receiving a data record including a plaintext, the complex format is applied to the plaintext, thereby generating a non-reversible token. In some embodiments, the generated token is transmitted a remote computer.