SYSTEM AND METHOD FOR DETECTING COMPUTER ATTACKS
20170279820 · 2017-09-28
Inventors
Cpc classification
H04L63/16
ELECTRICITY
H04L63/00
ELECTRICITY
H04L63/20
ELECTRICITY
International classification
Abstract
One embodiment of the invention is a system that stores a characteristic “modus operandi” for each type of computer attack that has historically been encountered or that could potentially be encountered on a computer network. In this embodiment, the system uses criteria derived from a modus operandi to query an event data store, identifying entities (host computers, user credentials, or malicious software objects) on the network that meet those criteria. The system also queries a flow data store to identify network connections among the identified entities that meet the criteria for the modus operandi. The identified entities and network connections are then analyzed to determine whether an attack matching the modus operandi is underway. If so, the system transmits a notification to permit the attack to be thwarted before it is completed (i.e., before exfiltration of sensitive stolen data occurs).
Claims
1. A system for detecting a computer attack, comprising: at least one processor; at least one memory; at least one communication interface for communicating over a network; and a plurality of program instructions stored in the at least one memory that, when executed by the at least one processor, cause the at least one processor to: load into the at least one memory criteria for at least one modus operandi, each modus operandi corresponding to a particular attack scenario; query an event data store to identify entities on the network that meet the criteria for the at least one modus operandi; query a flow data store to identify network connections among the identified entities that meet the criteria for the at least one modus operandi; analyze the identified entities and the identified network connections to determine whether an attack matching the at least one modus operandi is underway; and transmit a notification over the network, if it is determined that an attack matching the at least one modus operandi is underway.
2. The system for detecting a computer attack of claim 1, wherein each identified entity is one of a host computer, a user credential, and a malicious software object.
3. The system for detecting a computer attack of claim 1, wherein the notification is transmitted to one or more computers on the network for the displaying of an alert in a Web browser.
4. The system for detecting a computer attack of claim 1, wherein the notification is transmitted to a network firewall.
5. The system for detecting a computer attack of claim 1, wherein the at least one processor, the at least one memory, the at least one communication interface, and the plurality of program instructions reside in a single server.
6. The system for detecting a computer attack of claim 1, wherein the at least one processor, the at least one memory, the at least one communication interface, and the plurality of program instructions are distributed among a plurality of servers that are remotely located with respect to one another.
7. A computer-implemented method for detecting a computer attack, comprising: loading into a computer memory criteria for at least one modus operandi, each modus operandi corresponding to a particular attack scenario; querying an event data store over a network to identify entities on the network that meet the criteria for the at least one modus operandi; querying a flow data store over the network to identify network connections among the identified entities that meet the criteria for the at least one modus operandi; analyzing the identified entities and the identified network connections to determine whether an attack matching the at least one modus operandi is underway; and transmitting a notification over the network, if it is determined that an attack matching the at least one modus operandi is underway.
8. The computer-implemented method of claim 7, wherein each identified entity is one of a host computer, a user credential, and a malicious software object.
9. The computer-implemented method of claim 7, wherein the notification is transmitted to one or more computers on the network for the displaying of an alert in a Web browser.
10. The computer-implemented method of claim 7, wherein the notification is transmitted to a network firewall.
Description
BRIEF DESCRIPTION OF THE DRAWINGS
[0009]
[0010]
[0011]
DETAILED DESCRIPTION OF THE INVENTION
[0012] The following Detailed Description is of the best currently contemplated modes of carrying out illustrative embodiments of the invention. The description is not to be taken in a limiting sense but is made merely for the purpose of illustrating the general principles of the invention, since the scope of the invention is best defined by the appended claims.
[0013] One embodiment of the invention is a system that stores a characteristic “modus operandi” for each type of computer attack that has historically been encountered or that could potentially be encountered over a computer network. In this embodiment, the system uses criteria derived from a modus operandi to query an event data store, identifying entities (host computers, user credentials, or malicious software objects) on the network that meet those criteria. The system also queries a flow data store to identify network connections among the identified entities that meet the criteria for the modus operandi. The identified entities and network connections are then analyzed to determine whether an attack matching the modus operandi is underway. If so, the system transmits a notification to permit the attack to be thwarted before it is completed (i.e., before exfiltration of sensitive stolen data occurs). In some embodiments, the notification is sent to a user's (e.g., network administrator's) Web browser. In other embodiments, the notification is sent to a network firewall.
[0014] Referring next to the drawings,
[0015] Nodes 16 and 18 are staging hosts (computers inside the enterprise's network) that collect data from other computers on the network. Phase 2 in
[0016] Node 20 is an exfiltration host, a server on the enterprise's network to which the staging hosts transmit the stolen data collected during Phase 2. Phase 3 in
[0017] Node 22 is the exfiltration target, a computer controlled by the attacker that receives the data exfiltrated from the enterprise's network via exfiltration host 20. Phase 4 in
[0018] An attack such as that illustrated in
[0019] For a given MO, criteria can be derived that permit a “scraper” service on the enterprise network to categorize entities (host computers, user credentials, or files) into appropriate sets matching the MO in question. For example, a scraper might query an event data store for events involving infestations by a particular malicious software object (e.g., “Virus X”) and designate all affected host computers on the network as being members of a particular set. In other words, the MO criteria permit the scraper to identify the members of a set (e.g., “the set of all hosts on the network infected by Virus X”).
[0020] A scraper can then query a flow data store on the network (a source of information about communications that have taken place over the network, such as a network-communications log file obtained from a router or other network node) to define sets of network connections among the already-identified entities that match the MO. Analysis of the resulting sets of entities and network connections enables the system to determine that an attack matching the MO is currently underway. At that point, appropriate corrective action can be taken to thwart the attack.
[0021] In various embodiments, the system stores MOs corresponding to various attack scenarios in advance and provides criteria defining the sets of entities and connections for each MO to the scraper services. The MOs can be of a wide variety of types, including, without limitation, well-known industry-researched and published MOs, other historically-observed MOs, and hypothetical MOs (MOs of attacks not yet actually observed in practice).
[0022]
[0023] Web API 125 conveys the connections criteria for the MO from data store 180 to flow scraper 145. Flow scraper 145 queries flow data store 135, via a suitable API 140, for network connections involving the identified entities that match the connections criteria of the MO. Connections matching the MO criteria are assigned to sets in accordance with the MO and are communicated to middle tier 175 via Web API 125.
[0024] Middle tier 175 analyzes the sets of entities and network connections identified by event scraper 115 and flow scraper 145 to determine whether an attack matching the MO is currently underway. If so, middle tier 175 transmits a notification via Web API 125 to user interface 165 or, in other embodiments, to a firewall appliance on the network.
[0025] In some embodiments, all of the functional blocks shown in
[0026]
[0027] The systems and methods described herein offer distinct advantages over prior-art computer-attack-detection systems. The inventive embodiments reduce the number of investigations that need to be performed because many separate events are related to one another combined into a single “incident.” Those embodiments also reduces the amount of time needed to perform the investigation because more relevant information is contained in the incident. The cumulative impact to an organization using the inventive approach is reduced number of investigations, reduced time per investigative cycle, and reduced risk caused by missing an intrusion attempt.
[0028] It should be understood that the foregoing relates to illustrative embodiments of the invention and that modifications may be made without departing from the spirit and scope of the invention as set forth in the following claims.