Systems, methods, and computer-readable media for data security
Systems and methods are provided for data security. A server system provides data security using one or more processor devices, one or more communication interfaces, and one or more memory devices including computer-executable instructions. Those instructions cause the one or more processor devices to: monitor one or more requests or activities of a computing device; compare the monitored one or more requests or activities with a database of predetermined characteristics to determine whether the monitored one or more requests or activities indicates that the computing device downloaded or attempted to download more than a threshold number of data files or objects; and determine that the one or more requests or activities is suspicious when the comparing determines that the one or more requests or activities indicates that the computing device downloaded or attempted to download more than the threshold number of data files or objects, which causes a response to hinder the monitored one or more requests or activities.
1. A method performed at a data computing system that includes one or more data processors, one or more communication devices, and one or more memories storing one or more machine learning programs, the method comprising the following steps:
detecting, by the data computing system, one or more commands or actions for a computing device;
executing, by the data computing system, the one or more machine learning programs to analyze the one or more commands or actions and generating a machine learning output;
determining, by the data computing system, the one or more commands or actions is atypical based on the machine learning output;
determining, by the data computing system, that the one or more commands or actions determined to be atypical is suspicious; and
initiating, by the data computing system, a response to prevent the commands or actions that are determined to be suspicious,
wherein the response includes deleting the one or more commands or actions from a first server and storing a copy of the one or more commands or actions in a secondary server.
2. The method of claim 1 , wherein the detecting step includes detecting one or more commands or actions for the computing device initiated by a user.
3. The method of claim 1 , wherein the detecting step includes detecting one or more commands or actions for the computing device initiated by executable software.
4. The method of claim 1 , further comprising:
determining, by the data computing system, a baseline of actions or commands, and
the one or more machine learning programs, when executed, using the baseline of actions or commands to analyze the one or more commands or actions by comparing of the one or more commands or actions to the baseline of commands or actions.
5. The method of claim 4 , wherein the baseline of actions or commands is a baseline of actions or commands of a particular user.
6. The method of claim 4 , wherein the baseline of actions or commands is a baseline of actions or commands of general actions of the data computing system.
7. The method of claim 1 , wherein the one or more commands or actions determined to be suspicious is based on one or more of the following conditions:
a query being executed which is recursive;
a command being initiated that has not been used before;
an action or command being executed at a time of day or a time of week that is not usual for that action or command;
an action or command relating to high value data files or data objects; and
an action or command that calls or initiates other actions or commands.
8. The method of claim 1 , wherein the one or more commands or actions determined to be suspicious is based on one or more of the following conditions:
a frequency of a command or an action;
a sequence of inputted commands or actions taken;
whether the one or more commands or the one or more actions are atypical of a certain user profile;
whether the one or more commands or the one or more actions are atypical of a certain employee type; and
whether an atypical group of different users or IP addresses or both, exceeds an atypical grouping threshold, and the atypical group of different users or IP addresses or both is conducting similar or the same actions.
9. The method of claim 1 , further comprising:
associating a marker to mark monitored one or more requests or activities determined to be suspicious, the marker indicating that a data security action for a marked request or activity should be taken.
10. The method of claim 1 , wherein the response includes terminating a communication channel with the computing device.
11. A server system, comprising:
one or more data processors;
one or more communication interfaces connected to the one or more data processors; and
one or more memory devices including computer-executable instructions including machine learning instructions, which when executed by the one or more data processors, cause the one or more data processors to:
detect one or more commands or actions for a computing device;
perform a machine learning analysis of the one or more commands or actions and generating a machine learning output;
determine the one or more commands or actions is atypical based on the machine learning output;
determine that the one or more commands or actions determined to be atypical is suspicious; and
initiate a response to prevent the commands or actions that are determined to be suspicious,
wherein the response includes deleting the one or more commands or actions from a first server and storing a copy of the one or more commands or actions in a secondary server.
12. The server system of claim 11 , further comprising computer-executable instructions, which when executed by the one or more data processors, cause the one or more data processors to detect one or more commands or actions for the computing device initiated by a user.
13. The server system of claim 11 , further comprising computer-executable instructions, which when executed by the one or more data processors, cause the one or more data processors to detect one or more commands or actions for the computing device initiated by executable software.
14. The server system of claim 11 , further comprising computer-executable instructions, which when executed by the one or more data processors, cause the one or more data processors to:
determine a baseline of actions or commands, and
use the baseline of actions or commands to analyze the one or more commands or actions by comparing of the one or more commands or actions to the baseline of commands or actions.
15. The server system of claim 14 , wherein the baseline of actions or commands is a baseline of actions or commands of a particular user.
16. The server system of claim 14 , wherein the baseline of actions or commands is a baseline of actions or commands of general actions of the server system.
17. The server system of claim 11 , wherein the one or more commands or actions determined to be suspicious is based on one or more of the following conditions:
a query being executed which is recursive;
a command being initiated that has not been used before;
an action or command being executed at a time of day or a time of week that is not usual for that action or command;
an action or command relating to high value data files or data objects; and
an action or command that calls or initiates other actions or commands.
18. The server system of claim 11 , wherein the one or more commands or actions determined to be suspicious is based on one or more of the following conditions:
a frequency of a command or an action;
a sequence of inputted commands or actions taken;
whether the one or more commands or the one or more actions are atypical of a certain user profile;
whether the one or more commands or the one or more actions are atypical of a certain employee type; and
whether an atypical group of different users or IP addresses or both, exceeds an atypical grouping threshold, and the atypical group of different users or IP addresses or both is conducting similar or the same actions.
19. The server system of claim 11 , further comprising computer-executable instructions, which when executed by the one or more data processors, cause the one or more data processors to associate a marker to mark monitored one or more requests or activities determined to be suspicious, the marker indicating that a data security action for a marked request or activity should be taken.
20. The server system of claim 11 , wherein the response includes terminating a communication channel with the computing device.
21. A non-transitory, computer-readable medium having instructions stored thereon which, when executed at a data computing system that includes one or more data processors, one or more communication devices, and one or more memories storing one or more machine learning programs, cause the data computing system to perform operations that include:
detecting, by the data computing system, one or more commands or actions for a computing device;
executing, by the data computing system, the one or more machine learning programs to analyze the one or more commands or actions and generating a machine learning output;
determining, by the data computing system, the one or more commands or actions is atypical based on the machine learning output;
determining, by the data computing system, that the one or more commands or actions determined to be atypical is suspicious; and
initiating, by the data computing system, a response to prevent the commands or actions that are determined to be suspicious,
wherein the response includes deleting the one or more commands or actions from a first server and storing a copy of the one or more commands or actions in a secondary server.