The present disclosure relates to securing workloads of a network by identifying compromised elements in communication with the network and preventing their access to network resources. In one aspect, a method includes monitoring network traffic at network elements of a network; detecting a compromised element in communication with one or more of the network elements, the compromised element being associated with at least one network threat; and based on a defined network policy, applying one of a number of different access prevention schemes to the compromised element to prevent access to the network by the compromised element.

The present disclosure relates to securing workloads of a network by identifying compromised elements in communication with the network and preventing their access to network resources. In one aspect, a method includes monitoring network traffic at network elements of a network; detecting a compromised element in communication with one or more of the network elements, the compromised element being associated with at least one network threat; and based on a defined network policy, applying one of a number of different access prevention schemes to the compromised element to prevent access to the network by the compromised element.

A security information visualization method including the steps of: preprocessing log data extracted from a security device; calculating, from the pre-processed log data, periodic data of element information related to internet protocol (IP) address information about a security action; and providing visualization information visualizing the IP address information and the calculated periodic data of element information.

Computer-implemented method of detecting potential cybersecurity threats from collected data pertaining to a monitored network, the collected data comprising network data and/or endpoint data. The method comprises structuring the collected data as at least one data matrix, each row of the data matrix being a datapoint and each column corresponding to a feature. The method also comprises identifying one or more datapoints as anomalous, thereby detecting a potential cybersecurity threat. The method also comprises extracting causal information about the anomalous datapoint based on an angular relationship between a second-pass coordinate vector of the anomalous datapoint and a second-pass coordinate vector of one or more features. The second-pass coordinate vectors are determined by applying a second-pass singular value decomposition (SVD) to a residuals matrix. The residuals matrix is computed between the data matrix and an approximation of the data matrix by applying a first-pass truncated SVD to the data matrix.

Methods, apparatus and computer software products implement embodiments of the present invention that include defining, for a given software category, respective, disjoint sets of communication ports that are used by each of a plurality of software systems in the given software category, including at least first and second disjoint sets. A set of port scans are identified in data traffic transmitted between multiple nodes that communicate over a network, each of the port scans including an access, in the data traffic, of a plurality of the communication ports on a given destination node by a given source node during a predefined time period. Upon detecting a port scan by one of the nodes including accesses of at least one of the communication ports in the first set and at least one of the communication ports in the second set, a preventive action is initiated.

A route anomaly detection and remediation system analyzes a prefix for each route received to validate the route. A route monitoring component provides a centralized querying system for all routers from all devices to study routing history. A route collection component receives and stores all routes from multiple routers at a server. A set of microservice analysis components performs prefix analysis on each received route. Each microservice analysis component analyzes one or more portions of the prefix for each route to detect hijacked routes, leaked routes, withdrawn routes and/or other unhealthy routes before the routes are utilized for routing traffic on the network. The analysis performs new prefix validation and identifies healthy routes. Alerts identifying invalid routes are transmitted to an incident management system. Healthy routes are approved for usage by routers on the network to prevent network outages while improving network reliability, availability and stability.

Techniques are discussed for grouping access requests made to a computer system using a log of access requests that includes a plurality of log entries of that include (a) a plurality of traffic indicators of the corresponding access request and/or (b) a plurality of identity indicators of a respective remote computer system that made the corresponding access request. The plurality of log entries is analyzed using a plurality of network analysis rules that are useable to group log entries according to traffic and/or identity indicators. Based on the analyzing, a plurality of groups of log entries are identified, and each group of log entries is assigned a corresponding common actor identifier (common actor ID). The determination of whether to grant a particular access request uses one or more assigned common actor IDs.

Embodiments for detecting malicious modification of data in a network, by: setting, by a first layer of network resources, a number of markers associated with input/output (I/O) operations of the network; saving the markers, location, and associated metadata in a marker database; reading, by a second layer of the network resources, the markers corresponding to relevant I/O operations; and verifying each scanned I/O operation against a corresponding marker to determine whether or not data for a scanned specific I/O operation has been improperly modified for the first and second layers and any intermediate layer resulting in a fault condition, and if so, taking remedial action to flag or abort the specific I/O operation.

A method of monitoring network traffic of a connected vehicle. The method includes receiving network traffic information from a vehicle gateway, the network traffic information including malicious and/or benign information. The method also includes storing the network traffic information on a data server and periodically updating the network traffic information stored on the data server. The method further includes: pre-processing the network traffic information, the pre-processing the network traffic information including filtering and normalizing the network traffic information; generating a learning model based on the pre-processed network traffic information, the learning model being generated by an artificial intelligence learning; updating the learning model based on additional network traffic information, the additional network traffic information including real-time network data; in accordance with the updated learning model, detecting an anomaly event in the incoming network data; and generating a notification and/or blocking one or more packets associated with the incoming network data.

A method for threat detection and automatic mitigated response to IP & DDOS born Cyber Security events and Threats. The Disclosed system can provide autonomous system numbers (ASNs) to prevent several network-born cyber threats. These ASN can be distributed to devices on a network along with IP addresses. Disclosed are an ASN record that can be incorporated into Global DNS Servers and systems and can store the IP Address and Private and Public ASN numbers. Also, the disclosed system and method can also provide anomaly detection techniques based on the ASN and Geolocation Proximity.