Abstract: Systems and methods for determining a source of anomaly in a cyber-physical system (CPS). A forecasting tool can obtain a plurality of CPS feature values during an input window and forecast the plurality of CPS feature values for a forecast window. An anomaly identification tool can determine a total forecast error for the plurality of CPS features in the forecast window, identify an anomaly in the cyber-physical system when the total forecast error exceeds a total error threshold, and identify at least one CPS feature as the source of the anomaly.

Abstract: Disclosed are systems and methods of adding tags for use in detecting computer attacks. In one aspect, the system comprises a computer protection module configured to: receive a security notification, extract an object from the security notification, search for the extracted object in a threat database, add a first tag corresponding to the extracted object in the threat database only when the extracted object is found in the threat database, search for signs of suspicious activity in a database of suspicious activities based on the received security notification and the added first tag, and when at least one sign of suspicious activity is found, extract a second tag from the database of suspicious activities and add the second tag to an object database, wherein the object database is used for identifying signature of targeted attacks based on security notifications, objects, first tags and second tags.

Abstract: The present disclosure provides for systems and methods for generating an image of a web resource to detect a modification of the web resource. An exemplary method includes selecting one or more objects of the web resource based on one or more object attributes; identifying a plurality of tokens for each selected object based on contents of the selected object; calculating a hash signature for each selected object of the web resource using the identified plurality of tokens; identifying potentially malicious calls within the identified plurality of tokens; generating an image of the web resource based on the plurality of hash signatures and based on the identified potentially malicious calls, wherein the image of the web resource comprises a vector representation of the contents of the web resource; and detecting whether the web resource is modified based on the image of the web resource.

Abstract: Systems and methods are presented for selection of compatible components for an observed system. An exemplary method comprises collecting parameters of one or more components of the system, assessing conformity of the one or more components of the system with a required state of the system, identifying one or more anomalies based on the assessment of conformity, analyzing the one or more anomalies to identify a class and parameters of the system corresponding to the one or more anomalies, determining one or more models of methods of restoration of the system, selecting one or more components that meets requirements of the one or more models of methods of restoration and implementing the one or more components in the system that are compatible with the system to eliminate the one or more anomalies.

Abstract: Disclosed herein are systems and methods for forming a log during an execution of a file with vulnerabilities. In one aspect, an exemplary method comprises, discovering an activation of a trigger during an execution of a thread of a process created upon opening the file, wherein the trigger describes conditions accompanying an event which relates to an attempt to exploit a vulnerability of the file, analyzing a stack of the process created upon opening the file, and discovering a chain of function calls preceding the event in a form of a sequence of call and return addresses, analyzing the discovered chain of function calls for fulfillment of conditions of the trigger which relate to the attempt to exploit the vulnerability, and when the conditions of the trigger are fulfilled, saving information about the chain of function calls in a log.

Abstract: A method for protecting electronics systems of a vehicle from cyberattacks includes intercepting messages transmitted on a first communications bus between a plurality of Electronic Control Units (ECUs) of a vehicle. The ECUs are communicatively coupled to the first communications bus. At least one recipient ECU that is a recipient of the intercepted messages is determined. The intercepted messages and information indicating the determined at least one recipient ECU are stored in a log. The method further includes detecting a computer attack of the vehicle based on satisfaction of at least one condition of a rule by the stored messages and information in the log and blocking the computer attack of the vehicle by performing an action associated with the rule. The rule may depend on whether one or more intercepted messages are malicious messages and a recipient ECU of the malicious messages.

Abstract: Systems and methods for configuring a gateway for an automated system (AS) including an assembly tool to obtain a security configuration including a set of requirements for applications operating with AS devices, analyze assembly components for compliance with the security configuration, the assembly components for building one of applications, assemble an application package using a subset of the assembly components based on compliance with the security configuration, and a control tool to install the application package on the gateway such that execution of an individual application derived from the application package ensures a required level of information security for the AS.

Abstract: Disclosed herein are systems and methods for connecting a Domain Name System (DNS) secure resolution protocol. In one aspect, an exemplary method comprises, by a protection module, determining a DNS query from a client, determining a fulfillment of at least one condition for connecting the DNS secure resolution protocol, wherein the at least one condition is obtained from a database, and connecting the DNS secure resolution protocol for the client when the at least one condition for connecting the DNS secure resolution protocol is fulfilled.

Abstract: Disclosed herein are systems and methods for detecting anomalies in a technological system. In one aspect, an exemplary method comprises, intercepting, by a duplicator running on an upper-level element of the technological system at least one outgoing data packet addressed to a middle-level element of the technological system, sending, by the duplicator, information about the intercepted at least one outgoing data packet to a monitor using a secure connection, the monitor running on the middle-level element, intercepting, by the monitor, at least one incoming data packet, comparing, by the monitor, the information received from the duplicator with the intercepted at least one incoming data packet, and detecting, by the monitor, an anomaly in the technological system when the intercepted at least one incoming data packet does not conform to the information received from the duplicator.

Abstract: A method for detecting unmanned aerial vehicles (UAV) includes detecting an unknown flying object in a monitored zone of air space. An image of the detected unknown flying object is captured. The captured image is analyzed to classify the detected unknown flying object. A determination is made, based on the analyzed image, whether the detected unknown flying object comprises a UAV. In response to determining that the detected unknown flying object comprises a UAV, one or more radio signals exchanged between the UAV and a user of the UAV are suppressed until the UAV departs from the monitored zone of air space.

Abstract: The present disclosure provides a system and method for allocating computer resources for detection of malicious files. In one aspect, the system comprises: a hardware processor configured to: form at least one behavior pattern grouping selected commands with shared parameters, apply a hash function on the at least one of the formed behavior pattern to obtain computed parameters, calculate a degree of harmfulness based on the obtained computed parameters using the hash function and a model for detection of malicious files, wherein the degree of harmfulness is a number value characterizing a probability that a malicious activity will be manifested by a time of computing said degree of harmfulness and wherein the model is a machine learning model trained using computed parameters of previous behavior patterns on which the hash function was applied to output degrees of harmfulness, and allocate the computing resources based on the calculated degree of harmfulness.

Abstract: Disclosed herein are methods and systems for detecting a source of malicious activity in a computer system. An exemplary method comprises gathering information related to the objects of the computer system, forming a graph based on the information gathered on the objects, selecting at least two induced subgraphs (hereinafter, subgraph) from the resulting graph, determining the coefficient of harmfulness for each selected subgraph, the coefficient of harmfulness representing a numerical characteristic describing the strength of the relations between the vertices of that subgraph, determining, from the selected subgraphs, a subgraph whose coefficient of harmfulness is a minimum among the determined coefficients of harmfulness of the subgraphs, and the total coefficient of harmfulness of the subgraphs related to that subgraph is a maximum, identifying the object correlated with at least one vertex of the determined subgraph as a source of the malicious activity in the computer system.

Abstract: Disclosed herein are systems and method for correlating events to detect an information security incident, a correlation module may receive a plurality of network events indicating potential security violations, wherein each network event of the plurality of network events has a respective timestamp. The correlation module may identify, from the plurality of network events, a subset of network events that have occurred within a period of time, based on each respective timestamp. The correlation module may determine a plurality of potential orders of occurrence for the subset of network events. The correlation module may apply at least one correlation rule to each respective potential order of the plurality of potential orders. In response to determining that the at least one correlation rule is fulfilled, the correlation module may detect the information security incident.

Abstract: Systems and methods for anonymous collection of malware-related data from client devices. The system comprising a network node configured to (i) receive a first data structure from a client device, wherein the first data structure contain an identifier of the client device and an encrypted data that includes an identifier of a user of the client device and/or personal data of the user, and wherein the encrypted data was encrypted by the client device with a public key of the client device, wherein the public key was provided to the client device by an independent certification authority, (ii) transform the received first data structure by replacing the identifier of the client device with an anonymized identifier, and (iii) transmit the transformed first data structure containing the anonymized identifier and the encrypted data to a server.

Abstract: Disclosed herein are systems and methods of categorizing a .NET application. In one aspect, an exemplary method comprises, by a hardware processor of a security module, launching a CLR profiler upon launching of the .NET application, forming an execution log of the .NET application and adding information about events occurring during the execution of the .NET application via the launched CLR profiler, assigning to the .NET application, a category of a predetermined list of categories based on an analysis of the execution log of the .NET application, and determining whether the .NET application is categorized as being a malicious application.

Abstract: Systems and methods for anonymously transmitting data in a network are provided, in which a request data structure is received by a network node from a client device. A first substructure containing personal data (PD) and a second substructure not containing PD are identified in the request data structure, by the network node. The first substructure is encrypted, by the network node, and is transmitted along with the second substructure to a server. A response data structure is received, by the network node, from the server. The first encrypted substructure and a third encrypted substructure are identified, by the network node, in the response data structure. The first encrypted substructure is decrypted, by the network node, and is transmitted along with the third encrypted substructure to the client device. The third encrypted substructure can be decrypted and viewed by the client device.

Abstract: Disclosed herein are systems and methods for anonymous sending of data from a source device to a recipient device. In one aspect, an exemplary method comprises, by the source device: receiving a request to send data to the recipient device, processing the data such that an identifier of the user and identification data are not linked to the data to be sent to the recipient, and determining whether the identifier of the user is absent in the source device, when the identifier of the user is absent, generating the identifier of the user, sending the identifier of the user to a token generator, wherein the sent identifier comprises either the generated identifier or an existing identifier found during the determination of whether the identifier is absent in the source device, and sending, to the recipient device, a combination of a random token received from the token generator and the data.

Abstract: Systems and methods for assessing an impact of software on components of an industrial automation and control systems (IACS) are disclosed. In one aspect, an exemplary method comprises, selecting samples of software to be analyzed for capability to cause harm to the IACS. In one aspect, the method further comprises, for each particular configuration of the IACS being tested, performing analysis to identify effects of the selected samples on the particular configuration, wherein the identified effects include at least causes and events resulting in disruption of operations of the particular configuration of the IACS, and where the particular configuration including at least components of the industrial system being simulated on a testing device. In one aspect, the method further comprises, analyzing identified causes and events, and based on the analysis, assessing the impact of the selected sample by determining a degree of influence of the software on the particular configuration.

Abstract: Disclosed herein are systems and methods for handling unwanted telephone calls. In one aspect, an exemplary method comprises, intercepting a call request for a call from a terminal device of a calling party to a terminal device of a called party, generating a call recording containing media data transmitted within a connection established by the intercepted call request, determining attributes of the generated call recording, classifying the call as an unwanted call based on the determined attributes, wherein the classification is performed by a classifier trained on previously collected unwanted calls, and wherein the call is classified as unwanted when the attributes belong to an unwanted call class that is known, and handling the call in accordance with the classification of the call, the handling including at least securing information of the call.

Abstract: A method for analyzing relationships between clusters of devices includes selecting a first device from a first cluster of devices and selecting a second device from a second cluster of devices. Information related to a first communication link associated with the first device and information related to a second communication link associated with the second device is obtained. A similarity metric is computed based on the obtained information. The similarity metric represents a similarity between the first communication link and the second communication link associated with the second device. A relationship between the first and second clusters is determined using the computed similarity metric. When a cyberattack is detected on the devices in the first cluster or the second cluster, protection of all devices in the first cluster and the second cluster is modified based on the determined relationship in order to defend the respective clusters from the cyberattack.