Disclosed is an improved method, system, and computer program product for detecting hosts and connections between hosts that are being used as relays by an actor to gain control of hosts in a network. It can further identify periods of time within the connection when the relay activities occurred. In some embodiments, the invention can also chain successive relays to identify the true source and true target of the relay.

A computer-implemented method includes providing, for use by a third-party, injectable computer code that is capable of being served with other code provided by the third-party to client computing devices; receiving data from client computing devices that have been served the code by the third-party, the data including data that characterizes (a) the client computing devices and (b) user interaction with the client computing devices; classifying the client computing devices as controlled by actual users or instead by automated software based on analysis of the received data from the client computing devices; and providing to the third party one or more reports that characterize an overall level of automated software activity among client computing devices that have been served code by the third party.

The present teaching relates to a fraud detecting system and method for providing protection against fraudulent advertisement requests. Upon receiving a request for an advertisement, the system extracts an identifier, associated with a source from which the request originates, included in the request. The system determines whether the extracted identifier is included in a list of designated identifiers, and when the identifier is included in the list, the system denies the request for the advertisement. When the identifier is not included in the list of designated identifiers, the system provides the advertisement in response to the request, and extracts a set of features from the request and other requests that originate from the source to determine whether the identifier associated with the source is to be included in the list of designated identifiers based on the set of features in accordance with one or more models.

A session identification system classifies network sessions with a network application as either human-generated or generated by a non-human, such as by a bot. In an embodiment, the session identification system receives a set of unlabeled network sessions, and determines a label for a single class of the unlabeled network sessions. Based on the one-class labeling information, the session identification system determines multiple subsets of the unlabeled network sessions. Multiple classifiers included in the session identification system generate probabilities describing each of the unlabeled network sessions. The session identification system classifies each of the unlabeled network sessions based on a combination of the generated probabilities.

Detecting unauthorized access to a device is detected in embodiments of the disclosed technology. After downloading a webpage, code is executed in a browser to scan network ports and determine which ports are open. Further webpage content sent from a web server is determined and/or modified in embodiments of the disclosed technology based on which ports are open. In some embodiments, when a particular port or ports are already in use it is determined that a malfeasant actor has access to the end user device and as such, sensitive data or secure data which is intended for a specific user is no longer sent to the end user device.

In one embodiment, the present invention is a method and apparatus for detecting malware infection. One embodiment of a method for detecting a malware infection at a local host in a network, includes monitoring communications between the local host and one or more entities external to the network, generating a dialog warning if the communications include a transaction indicative of a malware infection, declaring a malware infection if, within a predefined period of time, the dialog warnings includes at least one dialog warning indicating a transaction initiated at the local host and at least one dialog warning indicating an additional transaction indicative of a malware infection, and outputting an infection profile for the local host.

A system and method for identifying botnets. The method includes determining a network event proximity based on collected network data, where the network data relates to at least one network device; determining time density of the network data; determining trend patterns of the network data; and determining, based on the network event proximity, time density, and trend patterns, when a botnet activity is present within the network data.

A method includes receiving a set of strings and applying one or more filters to generate a subset of strings that are determined to correspond to strings of interest. The method also includes retrieving domain name system (DNS) information associated with a first string of the subset. The method includes executing a rule-based engine to determine, based on application of one or more rules to the DNS information, whether to add the first string to a set of suspicious hostnames.

Identifying malicious network traffic based on distributed, collaborative sampling includes, at a computing device having connectivity to a network, obtaining a first set of data flows, based on sampling criteria, that represents network traffic between one or more nodes in the network and one or more domains outside of the network, each data flow in the first set of data flows including a plurality of data packets. The first set of data flows is forwarded for correlation with a plurality of other sets of data flows from other networks to generate global intelligence data. Adjusted sampling criteria is generated based on the global intelligence data and a second set of data flows is obtained based on the adjusted sampling criteria.

A method of reducing ad fraud for an Internet-based platform prevents advertising being shown to a user by any of the following steps: determining how many users of the plurality of users are associated with a particular IP address exceeding one or exceeding the number of authorized users; determining whether a screen of the user displaying the Internet-based platform is on, off or in screen saver mode; determining whether the Internet-based platform is currently being instantaneously displayed by the screen of the user; tracking a last time of a particular user input being a keyboard input, a mouse input or a touchscreen input which was made by the particular user; determining whether the user's electronic device has an accelerometer and whether a movement is occurring; determining whether the user's electronic device has a video camera and whether a movement is occurring in the electronic device from the video camera.