A system and method for file type identification involving extraction of a file-print of a file, the file-print being a unique or practically-unique representation of statistical characteristics associated with the distribution of bits in the binary contents of the file, similar to a fingerprint. The file-print is then passed to a machine learning algorithm that has been trained to recognize file types from their file-prints. The machine learning algorithm returns a predicted file type and, in some cases, a probability of correctness of the prediction. The file may then be encoded using an encoding algorithm chosen based on the predicted file type.

Assistance method for managing a cyber attack, and device and system thereof. The assistance method is implemented by a device managing resources of a computing domain, these resources being protected by a plurality of cyber attack protection services. The method includes: determining an incapability of a first protection service from among the plurality of protection services to handle a cyber attack targeting at least one resource of the computing domain; developing a mitigation plan for mitigating the attack based on a mitigation plan obtained from a second protection service from among the plurality of protection services or using assistance provided by at least the second protection service; and transmitting the developed mitigation plan to the first protection service to handle the attack.

A system and method for out-of-path detection of cyber-attacks are provided. The method includes receiving, by a detector, a plurality of data feeds from a plurality of data sources, wherein the detector is communicatively connected to the plurality of data sources; processing, by the detector, the plurality of received data feeds to generate enriched Flow data sets; analyzing the enriched Flow data sets to detect a potential cyber-attack; and upon detection of a potential cyber-attack, providing indication to each network entity of the network entities that is under attack.

An access point (AP) in a deployment may be attacked by a rogue AP. The rogue AP may transmit fake beacons that include a fake/incorrect basic service set (BSS) color that does not match the BSS color assigned to/used by the AP under attack. Due to this BSS color mismatch, stations associated to the AP under attack may switch to the fake/incorrect BSS color, and communications between the AP under attack and the stations may be disrupted, and can eventually lead to service denial. Systems and methods are provided for leveraging the BSS color feature to identify when a rogue AP is attacking another AP. Upon detecting an attack, the BSS color feature may be disabled to mitigate the level of service disruption to the AP under attack and the stations associated to that AP.

Malicious attacks by certain devices against a radio access network (RAN) can be detected and mitigated, while allowing communication of priority messages. A security management component (SMC) can determine whether a malicious attack against the RAN is occurring based on a defined baseline that indicates whether a malicious attack is occurring. The defined baseline is determined based on respective characteristics associated with respective devices that are determined based on analysis of information relating to the devices. In response to determining there is a malicious attack, SMC determines whether to block connections of devices to the RAN based on respective priority levels associated with respective messages being communicated by the devices. SMC blocks connections of devices communicating messages associated with priority levels that do not satisfy a defined threshold priority level, while managing communication connections to allow messages satisfying the defined threshold priority level to be communicated via the RAN.

A method for detecting patterns using statistical analysis is provided. The method includes receiving a subset of structured data having a plurality of fields. A plurality of value combinations is generated for the plurality of fields using a statistical combination function. Each combination of the generated plurality of value combinations is stored as a separate entry in a results table. The entry in the results table includes a counter associated with the stored combination. A value of the counter is incremented for every occurrence of the stored combination in the generated plurality of value combinations. The results table is sorted based on the counters' values and based on a number of fields in each combination. One or more entries having highest counter values are identified in the results table.

A method for managing communications in accordance with a given transport protocol. The method is implemented by a first device and includes, following detection of a cyber attack, activating, in the first device, collaboration with at least one entity of the network in order to mitigate the cyber attack, this collaboration including execution, by the first device, of at least one determined action, called collaboration action, during at least one the communication of the first device in accordance with the given transport protocol, via the network.

Techniques for securing control and user plane separation in mobile networks (e.g., service provider networks for mobile subscribers, such as for 4G/5G networks) are disclosed. In some embodiments, a system/process/computer program product for securing control and user plane separation in mobile networks in accordance with some embodiments includes monitoring network traffic on a mobile network at a security platform to identify an Packet Forwarding Control Protocol (PFCP) message associated with a new session, in which the mobile network includes a 4G network or a 5G network; extracting a plurality of parameters from the PFCP message at the security platform; and enforcing a security policy at the security platform on the new session based on one or more of the plurality of parameters to secure control and user plane separation in the mobile network.

The disclosed computer-implemented method includes applying transport protocol heuristics to selective acknowledgement (SACK) messages received at a network adapter from a network node. The transport protocol heuristics identify threshold values for operational functions that are performed when processing the SACK messages. The method further includes determining, by applying the transport protocol heuristics to the SACK messages received from the network node, that the threshold values for the transport protocol heuristics have been reached. In response to determining that the threshold values have been reached, the method includes identifying the network node as a security threat and taking remedial actions to mitigate the security threat. Various other methods, systems, and computer-readable media are also disclosed.

A method and system for characterizing application layer denial-of-service (DDoS) attacks are provided. The method includes generating a dynamic applicative signature by analyzing requests received during an on-going DDoS attack, wherein the dynamic applicative signature characterizes based on frequent applicative attributes appeared from the received; characterizing each incoming request based on the generated dynamic applicative signature, wherein the characterization provides an indication for each incoming request whether an incoming request is generated by an attack tool executing the on-going DDoS attributes; and causing a mitigation action on the incoming request generated by the attack tool based on the generated dynamic applicative signature.