Abstract: Actuators for rotating an optical-path-folding-element with two, first and second, degrees of freedom in an extended rotation range around two respective rotation axes, folded cameras including such actuators and dual-cameras including a folded camera as above together with an upright camera.

Abstract: Actuators for rotating an optical-path-folding-element with two, first and second, degrees of freedom in an extended rotation range around two respective rotation axes, folded cameras including such actuators and dual-cameras including a folded camera as above together with an upright camera.

Abstract: A computerized method for logical identification of malicious threats across a plurality of end-point devices (EPD) communicatively connected by a network, comprising collecting over the network an identifier associated with each file of a plurality of files, wherein each file of the plurality of files is installed on at least one of the plurality of EPDs and wherein the identifier is the same for each like file of the plurality of file. Information associated with an identified subset of files is collected, wherein the information indicates at least a time at which the at least one file was installed on one or more of the plurality of EPDs and the way the at least one file spread within the network. The collected information is analyzed according to a set of predetermined computerized investigation rules. The analysis is used to determine whether at least a file of the identified subset files is a suspicious file.

Abstract: A computerized method for logical identification of malicious threats across a plurality of end-point devices (EPD) communicatively connected by a network, comprising collecting over the network an identifier associated with each file of a plurality of files, wherein each file of the plurality of files is installed on at least one of the plurality of EPDs and wherein the identifier is the same for each like file of the plurality of file. Information associated with an identified subset of files is collected, wherein the information indicates at least a time at which the at least one file was installed on one or more of the plurality of EPDs and the way the at least one file spread within the network. The collected information is analyzed according to a set of predetermined computerized investigation rules. The analysis is used to determine whether at least a file of the identified subset files is a suspicious file.

Abstract: To prevent ransomware from encrypting data elements stored in a memory of a computer-based system, the system identifies at least one identifier associated with a data element. The identifiers indicate an attribute(s) of the corresponding data element within the memory. The system then determines an optimal number of virtual traps for the data elements respective of at least one identifier. The system then determines an optimal position for each virtual trap corresponding to the at least one identifier. The system then positions the virtual traps at the determined position within the memory. The system monitors the data elements stored in the memory in order to identify whether changes have occurred, and determines respectively updated optimal number and positions of virtual traps.

Abstract: To prevent ransomware from encrypting data elements stored in a memory of a computer-based system, the system identifies at least one identifier associated with a data element. The identifiers indicate an attribute(s) of the corresponding data element within the memory. The system then determines an optimal number of virtual traps for the data elements respective of at least one identifier. The system then determines an optimal position for each virtual trap corresponding to the at least one identifier. The system then positions the virtual traps at the determined position within the memory. The system monitors the data elements stored in the memory in order to identify whether changes have occurred, and determines respectively updated optimal number and positions of virtual traps.

Abstract: A system is connected to a plurality of user devices coupled to an enterprise's network. The system continuously collects, stores, and analyzes forensic data related to the enterprise's network. Based on the analysis, the system is able to determine normal behavior of the network and portions thereof and thereby identify abnormal behaviors within the network. Upon identification of an abnormal behavior, the system determines whether the abnormal behavior relates to a security incident. Upon determining a security incident in any portion of the enterprise's network, the system extracts forensic data respective of the security incident and enables further assessment of the security incident as well as identification of the source of the security incident. The system provides real-time damage assessment respective of the security incident as well as the security incident's attributions.

Abstract: For remediation of security incidents occurring in a network, forensic data which is collected from devices connected to a network is analyzed. A security incident is detected based on the analysis of the forensic data. Based on detecting the security incident, a source which is affected by the security data is identified based, at least in part, on attributes of the forensic data. The affected source is isolated from the network. Information about the affected source in association with an indication of the security incident and an indication of the isolating is stored.

Abstract: Processes in a network which cause and are attributable to security incidents are identified. Processes which are initiated on devices in an enterprise network at boot of the devices are identified. The enterprise network is continuously monitored to collect data about processes which were initiated or spawned on devices in the enterprise network after the boot of the devices. Each process is determined to be a major system process, a minor system process, or a non-system process based, at least in part, on the collected data which indicates associations among the processes. Based on matching a security incident alert to a first of the processes, it is determined whether the first process is a non-system process to validate the security incident alert.

Abstract: A computerized method for preventing ransomware from encrypting data elements stored in a memory of a computer-based system, the method comprising identifying at least one identifier for a data element, wherein the at least one identifier indicates at least a position of the data element within the memory. An optimal number of virtual traps is determined for the data element corresponding to the at least one identifier. An optimal position for each of the virtual traps is determined corresponding to the at least one identifier. The virtual traps are send to the determined optimal position within the memory.

Abstract: A computerized method for identification of suspicious processes executing on an end-point device communicatively connected to network, the network communicatively connected to a server, the method comprising receiving, by the server, a record of at least one process, initiated by and executing on by the end-point device. One or more parameters associated with the at least one process are identified. A first time pointer is identified corresponding to the identified one or more parameters, a first time pointer. A second time pointer at which a user associated with the end-point device initiated a user dependent process is identified. Whether the second time pointer occurred before the first time pointer is identified. It is determined whether the at least one process was initiated by the user based on identification of user dependent processes and corresponding attribution. An action is performed based on the above determination.

Abstract: A system is connected to a plurality of user devices coupled to an enterprise's network. The system continuously collects, stores, and analyzes forensic data related to the enterprise's network. Based on the analysis, the system is able to determine normal behavior of the network and portions thereof and thereby identify abnormal behaviors within the network. Upon identification of an abnormal behavior, the system determines whether the abnormal behavior relates to a security incident. Upon determining a security incident in any portion of the enterprise's network, the system extracts forensic data respective of the security incident and enables further assessment of the security incident as well as identification of the source of the security incident. The system provides real-time damage assessment respective of the security incident as well as the security incident's attributions.

Abstract: A system is used for detection of advanced persistent and non-persistent threats in a computerized environment. The system collects data about at least a first event associated with a process of an operating system of one of a plurality of devices connected to a network. The system identifies threads which attribute to the first event. The system generates a causality chain for the first event, where the causality chain comprises the threads which attribute to the first event in chronological order of spawning. The system determines whether a main thread corresponding to the first process can be identified based, at least in part, on the causality chain. Based on determining that the main thread corresponding to the first process cannot be identified, the system determines that the process is malicious.

Abstract: A system is connected to a plurality of user devices coupled to an enterprise's network. The system continuously collects, stores, and analyzes forensic data related to the enterprise's network. Based on the analysis, the system is able to determine normal behavior of the network and portions thereof and thereby identify abnormal behaviors within the network. Upon identification of an abnormal behavior, the system determines whether the abnormal behavior relates to a security incident. Upon determining a security incident in any portion of the enterprise's network, the system extracts forensic data respective of the security incident and enables further assessment of the security incident as well as identification of the source of the security incident. The system provides real-time damage assessment respective of the security incident as well as the security incident's attributions.

Abstract: A computerized method for logical identification of malicious threats across a plurality of end-point devices (EPD) communicatively connected by a network, comprising collecting over the network an identifier associated with each file of a plurality of files, wherein each file of the plurality of files is installed on at least one of the plurality of EPDs and wherein the identifier is the same for each like file of the plurality of file. Information associated with an identified subset of files is collected, wherein the information indicates at least a time at which the at least one file was installed on one or more of the plurality of EPDs and the way the at least one file spread within the network. The collected information is analyzed according to a set of predetermined computerized investigation rules. The analysis is used to determine whether at least a file of the identified subset files is a suspicious file.

Abstract: A system is connected to a plurality of user devices coupled to an enterprise's network. The system continuously collects, stores, and analyzes forensic data related to the enterprise's network. Based on the analysis, the system is able to determine normal behavior of the network and portions thereof and thereby identify abnormal behaviors within the network. Upon identification of an abnormal behavior, the system determines whether the abnormal behavior relates to a security incident. Upon determining a security incident in any portion of the enterprise's network, the system extracts forensic data respective of the security incident and enables further assessment of the security incident as well as identification of the source of the security incident. The system provides real-time damage assessment respective of the security incident as well as the security incident's attributions.

Abstract: A system is connected to a plurality of user devices coupled to an enterprise's network. The system continuously collects, stores, and analyzes forensic data related to the enterprise's network. Based on the analysis, the system is able to determine normal behavior of the network and portions thereof and thereby identify abnormal behaviors within the network. Upon identification of an abnormal behavior, the system determines whether the abnormal behavior relates to a security incident. Upon determining a security incident in any portion of the enterprise's network, the system extracts forensic data respective of the security incident and enables further assessment of the security incident as well as identification of the source of the security incident. The system provides real-time damage assessment respective of the security incident as well as the security incident's attributions.

Abstract: A computerized method for preventing ransomware from encrypting data elements stored in a memory of a computer-based system, the method comprising identifying at least one identifier for a data element, wherein the at least one identifier indicates at least a position of the data element within the memory. An optimal number of virtual traps is determined for the data element corresponding to the at least one identifier. An optimal position for each of the virtual traps is determined corresponding to the at least one identifier. The virtual traps are send to the determined optimal position within the memory.

Abstract: A computerized method for identification of suspicious processes executing on an end-point device communicatively connected to network, the network communicatively connected to a server, the method comprising receiving, by the server, a record of at least one process, initiated by and executing on by the end-point device. One or more parameters associated with the at least one process are identified. A first time pointer is identified corresponding to the identified one or more parameters, a first time pointer. A second time pointer at which a user associated with the end-point device initiated a user dependent process is identified. Whether the second time pointer occurred before the first time pointer is identified. It is determined whether the at least one process was initiated by the user based on identification of user dependent processes and corresponding attribution. An action is performed based on the above determination.

Abstract: A system is used for detection of advanced persistent and non-persistent threats in a computerized environment. The system is connected to a plurality of user devices coupled to an enterprise's network. The system receives via an interface an electronic notification of at least one event in the operating system of the computer. The system then analyzes the at least one event. The system then generates a causality chain for the at least one event respective of the analysis. The causality chain comprises all the threads that attributed to the at least one event in a chronological order. The system then identifies a main thread that started the causality chain that led to the at least one event. Then, the system determines whether the main thread is associated with malicious software. Upon determination that the main thread is associated with malicious software, the causality chain is marked as infected.