Abstract: In one embodiment, a device in a network obtains log data regarding replication of files stored on an endpoint client to a file replication service. The device tracks, based on the obtained logs, encryption changes to the files that convert the files from unencrypted files to encrypted files. The device determines that the tracked encryption changes to the files are indicative of a ransomware infection on the endpoint client. The device initiates a mitigation action regarding the ransomware infection.

Abstract: In one embodiment, a device in a network maintains a plurality of machine learning-based detectors for an intrusion detection system. Each detector is associated with a different portion of a feature space of traffic characteristics assessed by the intrusion detection system. The device provides data regarding the plurality of detectors to a user interface. The device receives an adjustment instruction from the user interface based on the data provided to the user interface regarding the plurality of detectors. The device adjusts the portions of the feature space associated with the plurality of detectors based on the adjustment instruction received from the user interface.

Abstract: In one embodiment, a traffic analysis service obtains telemetry data regarding network traffic associated with a device in a network. The traffic analysis service forms a histogram of frequencies of the traffic features from the telemetry data for the device. The traffic features are indicative of endpoints with which the device communicated. The traffic analysis service associates a device type with the device, by comparing the histogram of the traffic features from the telemetry data to histograms of traffic features associated with other devices. The traffic analysis service initiates, based on the device type associated with the device, an adjustment to treatment of the traffic associated with the device by the network.

Abstract: A user behavior activity detection method is provided in which network traffic relating to user behavior activities in a network is monitored. Data is stored representing network traffic within a plurality of time periods, each of the time periods serving as a transaction. Subsets of the network traffic in the transactions are identified as traffic suspected of relating to certain user behavior activities. The subsets of the network traffic in the transactions are assigned into one or more groups. A determination is made of one or more detection rules for each of the one or more groups based on identifying, for each of the groups, a number of user behavior activities common to each of the subsets of the network traffic. The one or more detection rules are used to monitor future network traffic in the network to detect occurrence of the certain user behavior activities.

Abstract: A method and system for processing particles contained in a liquid biological sample is presented. The method uses a rotatable vessel for processing particles contained in a liquid biological sample. The rotatable vessel has a longitudinal axis about which the vessel is rotatable, an upper portion having a top opening for receiving the liquid comprising the particles, a lower portion for holding the liquid while the rotatable vessel is resting, the lower portion having a bottom, and an intermediate portion located between the upper portion and the lower portion, the intermediate portion having a lateral collection chamber for holding the liquid while the rotatable vessel is rotating. The method employs dedicated acceleration and deceleration profiles for sedimentation and re-suspension of the particles of interest.

Abstract: Detecting illegitimate typosquatting with Internet Protocol (IP) information includes, at a computing device having connectivity to a network, obtaining a list of domains and filtering the list to generate a list of monitored domain strings. IP information is passively determined for domains associated with each of the monitored domain strings. A domain requested in network traffic for the network is identified as a candidate typosquatting domain and the candidate typosquatting domain is determined to be an illegitimate typosquatting domain based at least on the IP information. An action is initiated related to the illegitimate typosquatting domain.

Abstract: A pressure transmission liquid for a cellular analyzer, a system for transferring a liquid cellular sample for analysis by a cellular analyzer, and a method for transferring a liquid cellar sample for analysis are disclosed. The pressure transmission liquid includes an aqueous solution which is isotonic and substantially non-conductive characteristics. The cellular analyzer includes a pipetting module having a pipetting tip, a device for positioning the pipetting module, a sensor for detecting a liquid level of a liquid cellular sample to be analyzed, a pressure transmission liquid, and a pressure transmission liquid conduit connected to the pipetting tip and the pressure transmission liquid reservoir.

Abstract: In one embodiment, a device in a network receives traffic information regarding one or more secure sessions in the network. The device associates the one or more secure sessions with corresponding certificate validation check traffic indicated by the received traffic information. The device makes a self-signed certificate determination for an endpoint domain of a particular secure session based on whether the particular secure session is associated with certificate validation check traffic. The device causes the self-signed certificate determination for the endpoint domain to be used as input to a malware detector.

Abstract: A method for processing particles contained in a liquid biological sample is presented. The method uses a rotatable vessel for processing particles contained in a liquid biological sample. The rotatable vessel has a longitudinal axis about which the vessel is rotatable, an upper portion having a top opening for receiving the liquid comprising the particles, a lower portion for holding the liquid while the rotatable vessel is resting, the lower portion having a bottom, and an intermediate portion located between the upper portion and the lower portion, the intermediate portion having a lateral collection chamber for holding the liquid while the rotatable vessel is rotating. The method employs dedicated acceleration and deceleration profiles for sedimentation and re-suspension of the particles of interest.

Abstract: A laboratory system for a laboratory automation system is presented. The laboratory system comprises a sample container carrier. The sample container carrier is configured to carry a laboratory sample container and comprises a removal detector. The removal detector is configured to interact with the laboratory sample container to detect a removal of the carried laboratory sample container from the sample container carrier. Furthermore, the laboratory system is configured to determine based on the detected removal that a before valid logic assignment of the sample container carrier to the carried laboratory sample container is invalid.

Abstract: In one embodiment, a device in a network receives traffic information regarding one or more secure sessions in the network. The device associates the one or more secure sessions with corresponding certificate validation check traffic indicated by the received traffic information. The device makes a self-signed certificate determination for an endpoint domain of a particular secure session based on whether the particular secure session is associated with certificate validation check traffic. The device causes the self-signed certificate determination for the endpoint domain to be used as input to a malware detector.

Abstract: In an embodiment, the method comprises receiving an identification of an anomaly associated with a false positive identification of a security threat by the intrusion detection system, wherein a first set of feature data identifies features of the anomaly; creating a plurality of training sets each comprising identifications of a plurality of samples of network communications; for the anomaly and each training set of the plurality of training sets, training a decision tree that is stored in digital memory of the security analysis computer; based at least in part on the plurality of trained decision trees, extracting a set of features that distinguish the anomaly from the plurality of samples; generating one or more rules associated with the anomaly from the extracted set of features and causing programming the security analysis computer with the one or more rules.

Abstract: Rapidly detecting network threats with targeted detectors includes, at a computing device having connectivity to a network, determining features of background network traffic. Features are also extracted from a particular type of network threat. A characteristic of the particular type of network threat that best differentiates the features of the particular type of network threat from the features of the background network traffic is determined. A targeted detector for the particular type of network threat is created based on the characteristic and an action is applied to particular incoming network traffic identified by the targeted detector as being associated with the particular type of network threat.

Abstract: In one embodiment, a device in a network maintains a plurality of machine learning-based detectors for an intrusion detection system. Each detector is associated with a different portion of a feature space of traffic characteristics assessed by the intrusion detection system. The device provides data regarding the plurality of detectors to a user interface. The device receives an adjustment instruction from the user interface based on the data provided to the user interface regarding the plurality of detectors. The device adjusts the portions of the feature space associated with the plurality of detectors based on the adjustment instruction received from the user interface.

Abstract: A user behavior activity detection method is provided in which network traffic relating to user behavior activities in a network is monitored. Data is stored representing network traffic within a plurality of time periods, each of the time periods serving as a transaction. Subsets of the network traffic in the transactions are identified as traffic suspected of relating to certain user behavior activities. The subsets of the network traffic in the transactions are assigned into one or more groups. A determination is made of one or more detection rules for each of the one or more groups based on identifying, for each of the groups, a number of user behavior activities common to each of the subsets of the network traffic. The one or more detection rules are used to monitor future network traffic in the network to detect occurrence of the certain user behavior activities.

Abstract: A computing device having connectivity to a network stores one or more existing device models, where each of the one or more existing device models is a representation of a different client device used by a first authenticated user to access the network. The computing device obtains a device sample, which comprises network traffic data that is captured during a period of time and which is generated by a particular client device associated with the authenticated user of the network. The computing device determines, based on one or more relational criteria, whether the device sample should be assigned to one of the one or more existing device models or to an additional device model that has not yet been created. The computing device then determines relative identity of the particular client device based on whether the device sample is assigned to one of the one or more device models or to an additional device model that has not yet been created.

Abstract: In one embodiment, a device in a network receives traffic information regarding one or more secure sessions in the network. The device associates the one or more secure sessions with corresponding certificate validation check traffic indicated by the received traffic information. The device makes a self-signed certificate determination for an endpoint domain of a particular secure session based on whether the particular secure session is associated with certificate validation check traffic. The device causes the self-signed certificate determination for the endpoint domain to be used as input to a malware detector.

Abstract: In one embodiment, a device in a network detects an encrypted traffic flow associated with a client in the network. The device captures contextual traffic data regarding the encrypted traffic flow from one or more unencrypted packets associated with the client. The device performs a classification of the encrypted traffic flow by using the contextual traffic data as input to a machine learning-based classifier. The device generates an alert based on the classification of the encrypted traffic flow.

Abstract: Rapidly detecting network threats with targeted detectors includes, at a computing device having connectivity to a network, determining features of background network traffic. Features are also extracted from a particular type of network threat. A characteristic of the particular type of network threat that best differentiates the features of the particular type of network threat from the features of the background network traffic is determined. A targeted detector for the particular type of network threat is created based on the characteristic and an action is applied to particular incoming network traffic identified by the targeted detector as being associated with the particular type of network threat.

Abstract: Detecting illegitimate typosquatting with Internet Protocol (IP) information includes, at a computing device having connectivity to a network, obtaining a list of domains and filtering the list to generate a list of monitored domain strings. IP information is passively determined for domains associated with each of the monitored domain strings. A domain requested in network traffic for the network is identified as a candidate typosquatting domain and the candidate typosquatting domain is determined to be an illegitimate typosquatting domain based at least on the IP information. An action is initiated related to the illegitimate typosquatting domain.