Techniques are described for delayed serving of protected content. A request has been made by a client computing device for a requested resource comprising a first portion and a second portion that is initially withheld from the client computing device. First content comprising the first portion of the requested resource and reconnaissance code is served for execution on the client computing device. When executed at the client computing device, the reconnaissance code gathers data at the client computing device that indicates whether the client computing device is human-controlled or bot-controlled. The data gathered by the reconnaissance code is received. Based on the data, it is determined that the client computing device is not bot-controlled. In response to determining that the client computing device is not bot-controlled, the second portion of the requested resource is served to the client computing device.

An emergency answering center and a method of handling a distributed denial of service attack on an emergency answering center are provided. The emergency answering center receives an emergency call from a current caller. The emergency answering center determines websites visited by the current caller prior to calling the emergency answering center. If the number of calls received at the emergency answering center within a predetermined time period exceeds a predetermined threshold, the emergency answering center compares the websites visited by the current caller prior to calling the emergency answering center to a list of websites visited by other callers within the predetermined time period. If the websites visited by the current caller match at least a subset of the list of websites visited by other callers within the predetermined time period, the emergency answering center processes the emergency call in an alternate manner that is different from the regular manner of processing emergency calls.

Methods, systems, and computer program products for performing passive and active identity verification in association with online communications. For example, a computer-implemented method may include receiving one or more electronic messages associated with a user account, analyzing the electronic messages based on a plurality of identity verification profiles associated with the user account, generating an identity trust score associated with the electronic messages based on the analyzing, determining whether to issue a security challenge in response to the electronic messages based on the generated identity trust score, and issuing the security challenge in response to the electronic messages based on the determining.

The present disclosure relates to techniques for automated and adaptive cloud security management. Embodiments provide for, at an electronic device configured to interface with a cloud computing environment, initiating one or more transactions in the cloud computing environment using a first identifier to cause a first service of the cloud computing environment to generate a first set of data including the first identifier and a second identifier, and a second service of the cloud computing environment to generate a second set of data including a third identifier and a fourth identifier. Embodiments also provide for automatically determining whether the first identifier corresponds to the third identifier, and, in accordance with a determination that the first identifier corresponds to the third identifier, associating the second identifier and the fourth identifier to generate a linkage between the first and second services.

The disclosure provides a method for evaluating domain name and a server using the same method. The method includes: retrieving a raw domain name and dividing the raw domain name into a plurality of parts; retrieving a specific part of the parts, wherein the specific part include characters; encoding the characters into encoded data; padding the encoded data to a specific length; projecting the encoded data being padded as embedded vectors; sequentially inputting the embedded vectors to a plurality cells of a long short term memory model to generate a result vector; and converting the result vector to a prediction probability via a fully-connected layer and a specific function.

The present disclosure is related to a computer-implemented method and system for distinguishing human-driven Doman Name System (DNS) queries from Machine-to-Machine (M2M) DNS queries. The method includes receiving a DNS query, which includes a domain name, generating a probability score for the domain name based on one or more predetermined rules, and categorizing the DNS query as a human-driven DNS query or a M2M DNS query based on the probability score.

A method and system for runtime detection of botnets in containerized environments. The method includes creating a domain name system (DNS) policy for a software container, wherein the DNS policy defines at least a plurality of allowed domain names for the software container, wherein the DNS policy is created based on historical DNS queries by the software container; detecting a botnet based on traffic to and from the software container, wherein the botnet is detected when at least a portion of the traffic does not comply with the DNS policy, wherein the botnet is implemented via communication with a bot executed in the software container; and blocking at least one DNS query in the at least a portion of traffic, wherein each blocked DNS query is to a domain having a domain name that does not match any of the plurality of allowed domain names for the software container.

Methods, systems, and media for detecting anomalous network activity are provided. In some embodiments, a method for detecting anomalous network activity is provided, the method comprising: receiving information indicating network activity, wherein the information includes IP addresses corresponding to devices participating in the network activity; generating a graph representing the network activity, wherein each node of the graph indicates an IP address of a device; generating a representation of the graph, wherein the representation of the graph reduces a dimensionality of information indicated in the graph; identifying a plurality of clusters of network activity based on the representation of the graph; determining that at least one cluster corresponds to anomalous network activity; and in response to determining that the at least one cluster corresponds to anomalous network activity, causing a network connection of at least one device included in the at least one cluster to be blocked.

A system and method for blockchain-based access authorization to a protected entity. The method includes: receiving, by the protected entity, an access request to a protected entity, wherein the access request is received from a client device; extracting a unique client identifier from the received access request; causing the client device to perform an admission process; monitoring a blockchain network to identify at least one admission transaction, wherein the at least one admission transaction designates admission criteria; determining if the admission criteria satisfy a set of conditions for accessing the protected entity; and granting access to the client device when the admission criteria satisfies the set of conditions, wherein the access is access to the protected entity.

A system monitors network activity of an end-user device that communicates with servers over a communications network. The performs analysis of packets of data that are transported via the network. The system detects a first set of communications in which a first server infects the end-user device with a cryptocurrency mining malware; a second set of communications, in which a second server activates the end-user device as an activated cryptocurrency mining bot; and a third set of communications, in which the second server allocates a cryptocurrency mining task to the end-user device and later receives a cryptocurrency mining output from the end-user device. The system determines that the first server is a malicious infecting web-server; that the second server is a malicious Command and Control server of a distributed bot-net of cryptocurrency mining bots; and that the end-user device is an infected and activated and operational cryptocurrency mining bot.