Abstract: A new approach is proposed to support integration of EDR data from a plurality of EDR tools/sources into an Open XDR framework in an automated manner. First, EDR data generated by each of the plurality of EDR tools covering a plurality of assets is ingested into the Open XDR framework. The ingested EDR data is then normalized through a unified EDR data model. The normalized EDR data is further enriched with one or more new data fields to better correlate the EDR normalized data from the plurality of EDR tools. A plurality of alerts are then generated from the normalized and enriched data along one or more alert pathways to improve fidelity of the plurality of alerts. The plurality of alerts are correlated with the contextual information of the plurality of assets as well as information from other data sources to identify a set of incidents of suspicious activities.

Abstract: A movable controlled atmosphere store for fruits and vegetables, including: a store body in rectangular container structure and successively provided with an equipment room and a storage room along length direction; the equipment room is provided with an equipment door respectively on left and right sides; the storage room is in thermal insulation and sealing structure and provided with a sealing door at an end far away from the equipment room, and is provided with a sampling door on a side which is provided with a sealing film connected around a frame thereof, and a sampling assembly connected with the sealing film in cylindrical structure; a controlled atmosphere control system, including a control panel, as well as a refrigerator, a humidifier, a sterilizer, a nitrogen generator, a carbon dioxide adsorber, an ethylene adsorber, a temperature and humidity sensor and a gas concentration sensing device connected with the control panel.

Abstract: A method for detecting malicious program behavior includes performing program verification based on system activity data, analyzing unverified program data identified from the program verification to detect abnormal events, including analyzing host-level events to detect abnormal host-level events by learning a program representation as a graph embedding through an attentional architecture based on an invariant graph between different system entities, generating detection results based on the analysis, and performing at least one corrective action based on the detection results.

Abstract: A method for implementing confidential machine learning with program compartmentalization includes implementing a development stage to design an ML program, including annotating source code of the ML program to generate an ML program annotation, performing program analysis based on the development stage, including compiling the source code of the ML program based on the ML program annotation, inserting binary code based on the program analysis, including inserting run-time code into a confidential part of the ML program and a non-confidential part of the ML program, and generating an ML model by executing the ML program with the inserted binary code to protect the confidentiality of the ML model and the ML program from attack.

Abstract: Systems and methods for implementing a system architecture to support a trusted execution environment (TEE) with computational acceleration are provided. The method includes establishing a first trusted channel between a user application stored on an enclave and a graphics processing unit (GPU) driver loaded on a hypervisor. Establishing the first trusted channel includes leveraging page permissions in an extended page table (EPT) to isolate the first trusted channel between the enclave and the GPU driver in a physical memory of an operating system (OS). The method further includes establishing a second trusted channel between the GPU driver and a GPU device. The method also includes launching a unified TEE that includes the enclave and the hypervisor with execution of application code of the user application.

Abstract: A computer-implemented method for implementing protocol-independent anomaly detection within an industrial control system (ICS) includes implementing a detection stage, including performing byte filtering using a byte filtering model based on at least one new network packet associated with the ICS, performing horizontal detection to determine whether a horizontal constraint anomaly exists in the at least one network packet based on the byte filtering and a horizontal model, including analyzing constraints across different bytes of the at least one new network packet, performing message clustering based on the horizontal detection to generate first cluster information, and performing vertical detection to determine whether a vertical anomaly exists based on the first cluster information and a vertical model, including analyzing a temporal pattern of each byte of the at least one new network packet.

Abstract: Methods and systems for security monitoring and response include assigning an anomaly score to each of a plurality of event paths that are stored in a first memory. Events that are cold, events that are older than a threshold, and events that are not part of a top-k anomalous path are identified. The identified events are evicted from the first memory to a second memory. A threat associated with events in the first memory is identified. A security action is performed responsive to the identified threat.

Abstract: A method for implementing automated threat alert triage via data provenance includes receiving a set of alerts and security provenance data, separating true alert events within the set of alert events corresponding to malicious activity from false alert events within the set of alert events corresponding to benign activity based on an alert anomaly score assigned to the at least one alert event, and automatically generating a set of triaged alert events based on the separation.

Abstract: A movable controlled atmosphere store for fruits and vegetables, including: a store body in rectangular container structure and successively provided with an equipment room and a storage room along length direction; the equipment room is provided with an equipment door respectively on left and right sides; the storage room is in thermal insulation and sealing structure and provided with a sealing door at an end far away from the equipment room, and is provided with a sampling door on a side which is provided with a sealing film connected around a frame thereof, and a sampling assembly connected with the sealing film in cylindrical structure; a controlled atmosphere control system, including a control panel, as well as a refrigerator, a humidifier, a sterilizer, a nitrogen generator, a carbon dioxide adsorber, an ethylene adsorber, a temperature and humidity sensor and a gas concentration sensing device connected with the control panel.

Abstract: Systems and methods for mining and compressing commercial data including a network of point of sale devices to log commercial activity data including independent commercial events and corresponding dependent features. A middleware system is in communication with the network of point of sale devices to continuously collect and compress a stream of the commercial activity data and concurrently store the compressed commercial activity data. Compressing the stream includes a file access table corresponding to the commercial activity data, producing compressible file access templates (CFATs) according to frequent patterns of commercial activity data using the file access table, and replacing dependent feature sequences with a matching compressible file access template. A database is in communication with the middleware system to store the compressed commercial data.

Abstract: A method and system are provided for improving threat detection in a computer system by performing an inter-application dependency analysis on events of the computer system. The method includes receiving, by a processor operatively coupled to a memory, a Tracking Description Language (TDL) query including general constraints, a tracking declaration and an output specification, parsing, by the processor, the TDL query using a language parser, executing, by the processor, a tracking analysis based on the parsed TDL query, generating, by the processor, a tracking graph by cleaning a result of the tracking analysis, and outputting, by the processor and via an interface, query results based on the tracking graph.

Abstract: Systems and methods are disclosed for enhancing cybersecurity in a computer system by detecting safeness levels of executables. An installation lineage of an executable is identified in which entities forming the installation lineage include at least an installer of the monitored executable, and a network address from which the executable is retrieved. Each entity of the entities forming the installation lineage is individually analyzed using at least one safeness analysis. Results of the at least one safeness analysis of each entity are inherited by other entities in the lineage of the executable. A backtrace result for the executable is determined based on the inherited safeness evaluation of the executable. A total safeness of the executable, based on at least the backtrace result, is evaluated against a set of thresholds to detect a safeness level of the executable. The safeness level of the executable is output on a display screen.

Abstract: Systems and methods for an automotive security gateway include an in-gateway security system that monitors local host behaviors in vehicle devices to identify anomalous local host behaviors using a blueprint model trained to recognize secure local host behaviors. An out-of-gateway security system monitors network traffic across remote hosts, local devices, hotspot network, and in-car network to identify anomalous behaviors using deep packet inspection to inspect packets of the network. A threat mitigation system issues threat mitigation instructions corresponding to the identified anomalous local host behaviors and the anomalous remote host behaviors to secure the vehicle devices by removing the identified anomalous local host behaviors and the anomalous remote host behaviors. Automotive security gateway services and vehicle electronic control units operate the vehicle devices according to the threat mitigation instructions.

Abstract: A computer-implemented method for implementing alert interpretation in enterprise security systems is presented. The computer-implemented method includes employing a plurality of sensors to monitor streaming data from a plurality of computing devices, generating alerts based on the monitored streaming data, employing an alert interpretation module to interpret the alerts in real-time, matching problematic entities to the streaming data, retrieving following events, and generating an aftermath graph on a visualization component.

Abstract: A computer-implemented method for implementing alert interpretation in enterprise security systems is presented. The computer-implemented method includes employing a plurality of sensors to monitor streaming data from a plurality of computing devices, generating alerts based on the monitored streaming data, and employing an alert interpretation module to interpret the alerts in real-time, the alert interpretation module including a process-star graph constructor for retrieving relationships from the streaming data to construct process-star graph models and an alert cause detector for analyzing the alerts based on the process-star graph models to determine an entity that causes an alert.

Abstract: A system and method are provided for identifying security risks in a computer system. The system includes an event stream generator configured to collect system event data from the computer system. The system further includes a query device configured to receive query requests that specify parameters of a query. Each query request includes at least one anomaly model. The query request and the anomaly model are included in a first syntax in which a system event is expressed as {subject-operation-object}. The system further includes a detection device configured to receive at least one query request from the query device and continuously compare the system event data to the anomaly models of the query requests to detect a system event that poses a security risk. The system also includes a reporting device configured to generate an alert for system events that pose a security risk detected by the detection device.

Abstract: Methods for querying a database and database systems include optimizing a database query for parallel execution using spatial and temporal information relating to elements in the database, the optimized database query being split into sub-queries with sub-queries being divided spatially according to host and temporally according to time window. The sub-queries are executed in parallel. The results of the database query are outputted progressively.

Abstract: A computer-implemented method for implementing alert interpretation in enterprise security systems is presented. The computer-implemented method includes employing a plurality of sensors to monitor streaming data from a plurality of computing devices, generating alerts based on the monitored streaming data, automatically analyzing the alerts, in real-time, by using a graph-based alert interpretation engine employing process-star graph models, retrieving a cause of the alerts, an aftermath of the alerts, and baselines for the alert interpretation, and integrating the cause of the alerts, the aftermath of the alerts, and the baselines to output an alert interpretation graph to a user interface of a user device.

Abstract: Systems and a method are provided. A system includes a Temporal Behavior Query Language (TBQL) server having a processor and a memory operably coupled to the processor. The TBQL server configured to construct a TBQL query using a grammar inference technique based on syntactic sugar to expedite query construction. The TBQL server is further configured to execute the TBQL query to generate TBQL query results.

Abstract: Systems and methods are disclosed for securing an enterprise environment by detecting suspicious software. A global program lineage graph is constructed. Construction of the global program lineage graph includes creating a node for each version of a program having been installed on a set of user machines. Additionally, at least two nodes are linked with a directional edge. For each version of the program, a prevalence number of the set of user machines on which each version of the program had been installed is determined; and the prevalence number is recorded to the metadata associated with the respective node. Anomalous behavior is identified based on structures formed by the at least two nodes and associated directional edge in the global program lineage graph. An alarm is displayed on a graphical user interface for each suspicious software based on the identified anomalous behavior.