Abstract: In one aspect, a method for implementing a cloud-platform push for one or more known data breaches includes the step of, for each data breach of the one or more known data breaches, providing a functionality that maps one or more kill chains or Tactics, Techniques, and Procedures (TTPs) for a specified set of security dimensions. A step includes generating a security rule for each mapped kill chain or TTP based on the functionality that maps the one or more kill chains or Tactics, Techniques, and Procedures (TTPs) for a specified set of security dimensions. A step includes pushing the security rule to an enterprise so that the enterprise is aware of a vulnerability in the data breach. A step includes generating a customized posture for a Virtual private cloud (VPC) in the enterprise's cloud-based network. A step includes determining that the data breach can occur within the enterprise's cloud-based network.

Abstract: In one aspect, a computerized system for locating anomalous query activity with a cloud-based database, comprising: with an atypical query engine: analyzing and understanding data within a cloud-based database, processing all accesses to the data within cloud-based database and SAAS environment, generating a list of user that accesses a table from a location in the cloud-based database using, and capture a set of specified key statistics about the cloud-based database query; and role suggestion engine: generating a user behavior fingerprint comprising a history of the user's behavior within the cloud-based database, identifying that a user is an outlier with respect to behavior with respect to the set of specified key statistics, and suggesting a new role within an enterprise managing the cloud-based database for the user, wherein the fingerprint of the outlier user is used to generate the suggestion for the new role.

Abstract: In one aspect, a computerized method for detecting hiding and data intelligence gathering in a data lake or a cloud warehouse, comprising: implementing a hiding and data intelligence collection analysis phase in the data lake or the cloud warehouse; implementing a discovery process in the data lake or the cloud warehouse; implementing a data gathering process in the data lake or the cloud warehouse; and performing one or more dynamic masking operations to detect a Dynamic Masking column anomalies and to detect one or more atypical commands in the data lake or the cloud warehouse.

Abstract: In one aspect, In one aspect, a computerized method for automatic grading, impact analysis and mapping to the CIA triad, comprising: identifying a value of a plurality of data stores; associating the value back to an attack scenario such that a measure of impact with respect to attack progression or susceptibility now has a pecuniary value and generating a grading score; associating the grading score mapped to Confidentiality, Integrity and Availability (CIA) Triad; associating an attack progression with the pecuniary value and priority; identifying a progression of the attack; determining a time that is available for a response before a damage occurs to a system under attack; determining a stage of the attack in an attack kill chain, wherein for every stage of the attack as the progress happens, associating the pecuniary value and an impact for such a stage; and automatically calculates an overall data threat grade of the system.

Abstract: In one aspect, a computerized method for automatically identifying and solving for vendor data abuse in an enterprise network, includes the step of implementing a vendor detection at one or more gateways of the enterprise network. The method includes the step of mapping a set of data along with any associated data attributes of the set of data that are being shared with a vendor via the one or more gateways. The method includes the step of detecting and identifying an access anomaly with respect to the set of data associated with a vendor access. The method includes the step of implementing a specified data minimization process to the access anomaly.

Abstract: In one aspect, a computerized method for detecting reconnaissance and infiltration in data lakes and cloud warehouses, comprising: monitoring a SaaS data store or a cloud-native data store from inside the data store; examining the attack and automatically identifies how far the attack has progressed in the attack lifecycle; identifying the target and scope of the attack evaluates how far the attackers have penetrated the system and what is their target; and establishing the value of the asset subject to the attackers' attack and maps the impact of the attack on the CIA (confidentiality, integrity and availability) triad.

Abstract: In one aspect, a computerized method for detecting data abuse and data exfiltration in a data store or a data lakes cloud warehouse, comprising: identifying a plurality of Command and control (CnC) channels in an enterprise data cloud infrastructure; identifying and detecting malicious compressed data transfers and encrypted data transfers; implementing a destination analysis from within the data store; and implementing data abuse detection and prevention operations.

Abstract: In one aspect, a computerized system for securing data cloning and sharing options on data warehouses, comprising: a clone determiner engine that determines that a data asset is a primary data asset or a clone data asset, wherein the clone determiner engine comprises: a log data analyzer that obtains and analyzes a set of logs of the data asset from a specified log source, and wherein set of logs are used to determine that the data asset is the primary data asset or the clone data asset, a timestamp analyzer engine that obtains a timestamp data of the data asset and reviews the timestamp data to analyze ordering of the data asset, and wherein the timestamp analyzer engine determines the data asset is a primary asset or a secondary asset, and a fingerprints analyzer that obtains and reviews the data asset and any metadata of data asset, and wherein the fingerprints analyzer creates a fingerprint based on a content of the data asset and the metadata of the data asset, and wherein the fingerprints analyzer then

Abstract: A blockchain-based supervision system of hazardous chemical production includes: a collection layer, for collecting production data information, wherein a collection device in the collection layer sets a TEE to encrypt or hash the collected production data information; a data layer, for uplinking a hash certificate of the production data information through an alliance chain, wherein the collection layer communicates with the data layer; a blockchain, for deploying a file uplink contract and encrypting and storing a file on a privacy computing server after the file is connected to the trusted environment; and a privacy computing system, for forming a metadata market of the data from file description information, recording the metadata information of the collected data. A data user applies for the right of use to a production enterprise that produces the data, and after obtaining authorization, the data user performs various applications on the privacy computing system.

Abstract: In one aspect, a computerized method for minimizing a data governance in order to improve data security, comprising: providing and imposing a set of access rules to a set of data, wherein the set of data is stored in a data warehouse; measuring a level of over provisioning of the set of data; measuring a level of data abuse susceptibility of the set of data; implementing a dark data governance operation on the set of data; and identifying a set of infrequently used roles in the set of data.

Abstract: A blockchain-based supervision system of hazardous chemical production includes: a collection layer, for collecting production data information, wherein a collection device in the collection layer sets a TEE to encrypt or hash the collected production data information; a data layer, for uplinking a hash certificate of the production data information through an alliance chain, wherein the collection layer communicates with the data layer; a blockchain, for deploying a file uplink contract and encrypting and storing a file on a privacy computing server after the file is connected to the trusted environment; and a privacy computing system, for forming a metadata market of the data from file description information, recording the metadata information of the collected data. A data user applies for the right of use to a production enterprise that produces the data, and after obtaining authorization, the data user performs various applications on the privacy computing system.

Abstract: The invention provide an assessment method and device for infectious disease transmission, computer equipment and storage medium. The method comprises: obtaining respective target track data corresponding to assessment objects within a preset area in a first time slice; determining a matching subarea to which each assessment object matches in the first time slice based on the target track data; taking at least one of the plurality of subareas as a target subarea, and assessing an assessment object within the target subarea based on an infectious disease model to determine a transmission trend of an infectious disease for the assessment object within the preset area in the first time slice; and taking a next time slice as the first time slice, and re-performing the above steps until end of the target time period to determine a transmission trend of the infectious disease among the assessment objects during the target time period.

Abstract: In one aspect, a computerized system for locating anomalous query activity with a cloud-based database, comprising: with an atypical query engine: analyzing and understanding data within a cloud-based database, processing all accesses to the data within cloud-based database and SAAS environment, generating a list of user that accesses a table from a location in the cloud-based database using, and capture a set of specified key statistics about the cloud-based database query; and role suggestion engine: generating a user behavior fingerprint comprising a history of the user's behavior within the cloud-based database, identifying that a user is an outlier with respect to behavior with respect to the set of specified key statistics, and suggesting a new role within an enterprise managing the cloud-based database for the user, wherein the fingerprint of the outlier user is used to generate the suggestion for the new role.

Abstract: In one aspect, a computerized method for locating one or more shadow vulnerable datastores for cloud-platform datastores includes the step of identifying a cloned data store of an original datastore in a cloud database instance. It includes the step of determining that the cloned datastore comprises a shadow vulnerable datastore. It includes the step of defining a security posture of the cloned datastore. It includes the step of publishing a digitized data clone security differential report comprising the security posture and one or more remediations to fix security posture issues.

Abstract: The present disclosure provides systems, methods, and computer-readable media for determining an objective measure of breach exposure of Application Programming Interface (API) infrastructure for microservices. In one aspect, a method includes analyzing header information of Application Programming Interface (API) call stacks between microservices; determining, for each API call stack, corresponding security key information based on the header information; determining location information of each of the microservices; and determining a vulnerability score for each of the microservices based on the corresponding security key information and corresponding location information of each of the microservices.

Abstract: A computerized method for implementing risk discovery with a set of unified security and privacy policies, includes the step of discovering a set of data and a set of data accesses within an enterprise computing system. The method includes the step of classifying the set of discovered data and the set of data accesses with an identification that shows which of the data assets are important or critical for the enterprise. The method includes the step of determining which of the set of discovered data and the set of data accesses have or are associated with sensitive information. The method includes the step of placing the set of discovered data and the set of data accesses that are associated with sensitive information into a set of discovered information about the infrastructure. The method includes the step of determining which of the set of discovered data and the set of data accesses are relevant in the context of a specified governmental data privacy regulation.