DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
Claims 1-20 are pending in this Office Action.
Response to Arguments
Applicant’s arguments filed in the amendment on 05/06/2026, have been fully considered but are moot in view of new grounds of rejection. The reasons set forth below.
Drawings
The formal drawings received on 07/25/2024 have been entered.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Independent Claim(s):
Step 1: Statutory Category. Claim(s) 1-20 is/are directed to statutory category of subject matter. The claim(s) does/do fall within at least one of the four categories of patent eligible subject matter because the claim(s) is/are directed to either a process, machine, manufacture, or composition of matter.
Step 2A: Prong One. Judicial Exception. Claim(s) 1-20 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. The claim(s) are directed to abstract idea of generating a whitelist using the filtered DNS related event data, wherein the whitelist includes a subset of network domains included in the DNS related event data based on a data driven model of the DNS related event data and the DNS related threat data, as explained in detail below. The claim(s) do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional computer elements, which are recited at a high level of generality, provide conventional computer functions that do not add meaningful limits to practicing the abstract idea.
The independent claim(s) recites, in part, receive a set of network related event data, wherein the set of network related event data includes Domain Name System (DNS) related event data; receive a set of network related threat data, wherein the set of network related threat data includes DNS related threat data; filter the DNS related event data using the set of network related threat data to obtain filtered DNS related event data; and generate a whitelist using the filtered DNS related event data, wherein the whitelist includes a subset of network domains included in the DNS related event data based on a data driven model of the DNS related event data and the DNS related threat data, wherein the generating of the whitelist comprises to: determine a top N domains based on the filtered DNS related event data; and filter the top N domains to obtain the whitelist, wherein the filtering of the top N domains comprises to: remove domains that are known threats from the top N domains to obtain an updated top N domains; and output domains in the updated top N domains to the whitelist; output the whitelist to a network device for filtering DNS requests using the whitelist; and identify a network domain for further evaluation to determine whether the network domain is properly included on a blacklist; and a memory coupled to the processor and configured to provide the processor with instructions. These steps describe the concept of generating a whitelist using the filtered DNS related event data, wherein the whitelist includes a subset of network domains included in the DNS related event data based on a data driven model of the DNS related event data and the DNS related threat data, which corresponds to concepts identified as abstract ideas by the courts, such as filtering content, BASCOM Global Internet v. AT&T Mobility, LLC, 827 F.3d 1341, 1345-46, 119 USPQ2d 1236, 1239 (Fed. Cir. 2016). All of these concepts relate to “Certain Methods of Organizing Human Activity” in which “Concepts relating to interpersonal and intrapersonal activities, such as managing relationships or transactions between people, social activities, and human behavior; satisfying or avoiding a legal obligation; advertising, marketing, and sales activities or behaviors; and managing human mental activity.” The concept described in the claim(s) is/are not meaningfully different than “Certain Methods of Organizing Human Activity” found by the courts to be abstract ideas. As such, the description in the claim(s) of generating a whitelist using the filtered DNS related event data, wherein the whitelist includes a subset of network domains included in the DNS related event data based on a data driven model of the DNS related event data and the DNS related threat data is an abstract idea. Enfish, LLC v. Microsoft Corp. 822 F.3d 1327, 1335-36 (Fed. Cir. 2016) (“[T]he first step in the Alice inquiry in this case asks whether the focus of the claims [was] on the specific asserted improvement in computer capabilities … or, instead, on a process that qualifies as an ‘abstract idea’ for which computers are invoked merely as a tool.”) No such evidence exists on this record. Unlike Enfish, where the claims were focused on a specific improvement in how the computer functioned, the claim here merely uses the computer as a tool to perform the abstract concepts, and the claims are not rooted in technology and simply employs conventional techniques used by humans for generating a whitelist using the filtered DNS related event data, wherein the whitelist includes a subset of network domains included in the DNS related event data based on a data driven model of the DNS related event data and the DNS related threat data. The claim here is not similar to claimed patent’s innovative logical model for a computer database (p. 2-3), nor does the claim here have similar specific asserted improvement in computer capabilities (p. 7) as in the Enfish patent. Rather here, the claim is directed to automating the human behavior or task. (See Enfish Memo and Enfish v. Microsoft, May 2016). In addition, simply limiting the invention to a technological environment does “not make an abstract concept any less abstract under step one.” Intellectual Ventures I, 850 F.3d at 1340. Therefore, based on the similarity of the concept described in this claim to abstract ideas identified by the courts in the claim is directed to an abstract idea. For these reasons, afford are ineligible.
Step 2A: Prong Two. Practical Application. Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f). Adding insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g). Generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h).
Step 2B: Additional Elements Significantly More Then the Judicial Exception. The independent claim(s) do/does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. The claim recites the additional limitations of a “processor” configured to: receive a set of network related event data, wherein the set of network related event data includes Domain Name System (DNS) related event data; receive a set of network related threat data, wherein the set of network related threat data includes DNS related threat data; filter the DNS related event data using the set of network related threat data to obtain filtered DNS related event data; and generate a whitelist using the filtered DNS related event data, wherein the whitelist includes a subset of network domains included in the DNS related event data based on a data driven model of the DNS related event data and the DNS related threat data, wherein the generating of the whitelist comprises to: determine a top N domains based on the filtered DNS related event data; and filter the top N domains to obtain the whitelist, wherein the filtering of the top N domains comprises to: remove domains that are known threats from the top N domains to obtain an updated top N domains; and output domains in the updated top N domains to the whitelist; output the whitelist to a network device for filtering DNS requests using the whitelist; and identify a network domain for further evaluation to determine whether the network domain is properly included on a blacklist; and a “memory” coupled to the “processor” and configured to provide the processor with instructions. The “memory” and “processor” are recited at a high level of generality and are recited as performing generic computer functions routinely used in computer applications. Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system. Next, “generating a whitelist using the filtered DNS related event data, wherein the whitelist includes a subset of network domains included in the DNS related event data based on a data driven model of the DNS related event data and the DNS related threat data” is stated at a high level of generality without tying it to an algorithm that would improve the functionality of the technology and its broadest reasonable interpretation comprises only generating a whitelist using the filtered DNS related event data, wherein the whitelist includes a subset of network domains included in the DNS related event data based on a data driven model of the DNS related event data and the DNS related threat data through the use of some unspecified generic computers and interface. The use of generic computer components for generating a whitelist using the filtered DNS related event data, wherein the whitelist includes a subset of network domains included in the DNS related event data based on a data driven model of the DNS related event data and the DNS related threat data through an unspecified interface does not impose any meaningful limit on the computer implementation of the abstract idea. These independent claims include insignificant pre-solution limitation(s) [a processor configured to: receive a set of network related event data, wherein the set of network related event data includes Domain Name System (DNS) related event data; receive a set of network related threat data, wherein the set of network related threat data includes DNS related threat data; filter the DNS related event data using the set of network related threat data to obtain filtered DNS related event data;] and post-solution limitation(s) [output the whitelist to a network device for filtering DNS requests using the whitelist; and identify a network domain for further evaluation to determine whether the network domain is properly included on a blacklist; and a memory coupled to the processor and configured to provide the processor with instructions] that do not transform the patent-ineligible concept of an abstract idea to a patent-eligible concept even if they are performed using general purpose computer, as these pre-solution limitation(s) and post-solution limitation(s) add insignificant extrasolution activity to the judicial exception. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. Additionally, adding the words ‘‘apply it’’ (or an equivalent) with the judicial exception (i.e., applying the judicial exception to the Domain Name System network services), or mere instructions to implement an abstract idea on a computer or generally linking the use of the judicial exception to a particular technological environment or field of use (i.e., the Domain Name System network services) is also found to not be enough to qualify as significantly more.
Dependent Claim(s):
Step 1: Statutory Category. Claim(s) 2-10, 12-15, and 17-20 is/are directed to statutory category of subject matter. The claim(s) does/do fall within at least one of the four categories of patent eligible subject matter because the claim(s) is/are directed to either a process, machine, manufacture, or composition of matter.
Step 2A: Judicial Exception. Claim(s) 2-10, 12-15, and 17-20 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. The claim(s) are directed to abstract idea of generating a whitelist using the filtered DNS related event data, wherein the whitelist includes a subset of network domains included in the DNS related event data based on a data driven model of the DNS related event data and the DNS related threat data, without any significant extrasolution activities, as explained in detail below. The claim(s) do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional computer elements, which are recited at a high level of generality, provide conventional computer functions that do not add meaningful limits to practicing the abstract idea.
The dependent claim(s) recites, in part, 2. The system recited in claim 1, wherein the DNS related event data includes a set of popular network domains. 3. The system recited in claim 1, wherein the DNS related threat data includes a DNS threat feed. 4. The system recited in claim 1, wherein the DNS related threat data includes a DNS threat feed that is associated with a first enterprise network. 5. The system recited in claim 1, wherein the DNS related threat data includes a DNS threat feed that is automatically filtered to determine a popularity of network domains associated with malware. 6. The system recited in claim 1, wherein the subset of network domains included in the whitelist are selected using a classifier. 7. The system recited in claim 1, wherein the subset of network domains included in the whitelist are selected using a statistical classifier. 8. The system recited in claim 1, wherein: the DNS related event data is automatically filtered using a classifier to exclude one or more network domains associated with malware; and the processor is further configured to: output the whitelist to a network device for filtering DNS requests using the whitelist. 9. The system recited in claim 1, wherein: the DNS related event data is automatically filtered using a classifier to exclude one or more network domains associated with malware; and the processor is further configured to: periodically update the whitelist based on another set of network related event data and another set of network related threat data, wherein the whitelist is automatically and dynamically adjusted to changes in a production data environment associated with a first enterprise network. 10. The system recited in claim 1, wherein the processor is further configured to: identify a network domain for further evaluation to determine whether the network domain is properly included on a blacklist. These steps describe the concept of generating a whitelist using the filtered DNS related event data, wherein the whitelist includes a subset of network domains included in the DNS related event data based on a data driven model of the DNS related event data and the DNS related threat data, without any significant extrasolution activities, which corresponds to concepts identified as abstract ideas by the courts, such as filtering content, BASCOM Global Internet v. AT&T Mobility, LLC, 827 F.3d 1341, 1345-46, 119 USPQ2d 1236, 1239 (Fed. Cir. 2016). All of these concepts relate to “Certain Methods of Organizing Human Activity” in which “Concepts relating to interpersonal and intrapersonal activities, such as managing relationships or transactions between people, social activities, and human behavior; satisfying or avoiding a legal obligation; advertising, marketing, and sales activities or behaviors; and managing human mental activity.” The concept described in the claim(s) is/are not meaningfully different than “Certain Methods of Organizing Human Activity” found by the courts to be abstract ideas. As such, the description in the claim(s) of generating a whitelist using the filtered DNS related event data, wherein the whitelist includes a subset of network domains included in the DNS related event data based on a data driven model of the DNS related event data and the DNS related threat data, without any significant extrasolution activities, is an abstract idea. Enfish, LLC v. Microsoft Corp. 822 F.3d 1327, 1335-36 (Fed. Cir. 2016) (“[T]he first step in the Alice inquiry in this case asks whether the focus of the claims [was] on the specific asserted improvement in computer capabilities … or, instead, on a process that qualifies as an ‘abstract idea’ for which computers are invoked merely as a tool.”) No such evidence exists on this record. Unlike Enfish, where the claims were focused on a specific improvement in how the computer functioned, the claim here merely uses the computer as a tool to perform the abstract concepts, and the claims are not rooted in technology and simply employs conventional techniques used by humans for generating a whitelist using the filtered DNS related event data, wherein the whitelist includes a subset of network domains included in the DNS related event data based on a data driven model of the DNS related event data and the DNS related threat data, without any significant extrasolution activities. The claim here is not similar to claimed patent’s innovative logical model for a computer database (p. 2-3), nor does the claim here have similar specific asserted improvement in computer capabilities (p. 7) as in the Enfish patent. Rather here, the claim is directed to automating the human behavior or task. (See Enfish Memo and Enfish v. Microsoft, May 2016). In addition, simply limiting the invention to a technological environment does “not make an abstract concept any less abstract under step one.” Intellectual Ventures I, 850 F.3d at 1340. Therefore, based on the similarity of the concept described in this claim to abstract ideas identified by the courts in the claim is directed to an abstract idea. For these reasons, afford are ineligible.
Step 2B: Additional Elements Significantly More Then the Judicial Exception. The dependent claim(s) do/does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. The claim recites the additional limitations of a “memory” and “processor” for 2. The system recited in claim 1, wherein the DNS related event data includes a set of popular network domains. 3. The system recited in claim 1, wherein the DNS related threat data includes a DNS threat feed. 4. The system recited in claim 1, wherein the DNS related threat data includes a DNS threat feed that is associated with a first enterprise network. 5. The system recited in claim 1, wherein the DNS related threat data includes a DNS threat feed that is automatically filtered to determine a popularity of network domains associated with malware. 6. The system recited in claim 1, wherein the subset of network domains included in the whitelist are selected using a classifier. 7. The system recited in claim 1, wherein the subset of network domains included in the whitelist are selected using a statistical classifier. 8. The system recited in claim 1, wherein: the DNS related event data is automatically filtered using a classifier to exclude one or more network domains associated with malware; and the processor is further configured to: output the whitelist to a network device for filtering DNS requests using the whitelist. 9. The system recited in claim 1, wherein: the DNS related event data is automatically filtered using a classifier to exclude one or more network domains associated with malware; and the processor is further configured to: periodically update the whitelist based on another set of network related event data and another set of network related threat data, wherein the whitelist is automatically and dynamically adjusted to changes in a production data environment associated with a first enterprise network. 10. The system recited in claim 1, wherein the processor is further configured to: identify a network domain for further evaluation to determine whether the network domain is properly included on a blacklist. The “memory” and “processor” are recited at a high level of generality and are recited as performing generic computer functions routinely used in computer applications. Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system. Next, “generating a whitelist using the filtered DNS related event data, wherein the whitelist includes a subset of network domains included in the DNS related event data based on a data driven model of the DNS related event data and the DNS related threat data, without any significant extrasolution activities” is stated at a high level of generality without tying it to an algorithm that would improve the functionality of the technology and its broadest reasonable interpretation comprises only generating a whitelist using the filtered DNS related event data, wherein the whitelist includes a subset of network domains included in the DNS related event data based on a data driven model of the DNS related event data and the DNS related threat data, without any significant extrasolution activities through the use of some unspecified generic computers and interface. The use of generic computer components for generating a whitelist using the filtered DNS related event data, wherein the whitelist includes a subset of network domains included in the DNS related event data based on a data driven model of the DNS related event data and the DNS related threat data, without any significant extrasolution activities through an unspecified interface does not impose any meaningful limit on the computer implementation of the abstract idea. These dependent claims include insignificant pre-solution limitation(s) and post-solution limitation(s) that do not transform the patent-ineligible concept of an abstract idea to a patent-eligible concept even if they are performed using general purpose computer, as these pre-solution limitation(s) and post-solution limitation(s) add insignificant extrasolution activity to the judicial exception. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. Additionally, adding the words ‘‘apply it’’ (or an equivalent) with the judicial exception (i.e., applying the judicial exception to the Domain Name System network services), or mere instructions to implement an abstract idea on a computer or generally linking the use of the judicial exception to a particular technological environment or field of use (i.e., the Domain Name System network services) is also found to not be enough to qualify as significantly more.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim 10 is rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. Claim 10 recites limitation that is already in the independent claims. Clam 10 recites wherein the processor is further configured to: identify a network domain for further evaluation to determine whether the network domain is properly included on a blacklist. Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-3, 10-13, 16-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kislitsin (US 20190222589) in view of Cooley (US 9832209), and further in view of Lin (US 10853431).
1, 11, 16. Kislitsin teaches:
A system, comprising: – in paragraphs [0041]-[0153] (System 10 can be used to detect malicious domain names in a network traffic.)
a processor configured to: – in paragraphs [0041]-[0153] (A computer-readable medium for long-term storage of data is provided, the medium for storing computer-readable instructions that, when executed by a processor by a computing device, cause the steps of the method described in this document to be performed.)
receive a set of network related event data, – in paragraphs [0041]-[0152] (The computing device 1, in particular its analyzing module 1.3, may periodically, after a specified period of time establish a connection with at least one of the above rating sites or access them using the connection module 1.6 in order to extract from the so-accessed rating sites at least one list of popular sites for updating data associated with the known domain names that is stored in the local storage 1.5 data.)
wherein the set of network related event data includes Domain Name System (DNS) related event data; – in paragraphs [0041]-[0152] (The updating can be executed on the basis of the list of popular sites from a given one of these rating sites (or lists from multiple rating sites), as well as a summary list of popular sites compiled by the analyzing module 1.3 on the basis of separate lists of popular domain names obtained from each of these rating sites, by, for example, a comparative assessment of popularity indicators assigned to sites in these separate lists, in accordance with a given set of evaluation rules to identify a given number of the most popular sites.)
a memory coupled to the processor and configured to provide the processor with instructions. – in paragraphs [0041]-[0153] (A computer-readable medium for long-term storage of data is provided, the medium for storing computer-readable instructions that, when executed by a processor by a computing device, cause the steps of the method described in this document to be performed.)
Kislitsin does not explicitly teach:
receive a set of network related threat data, wherein the set of network related threat data includes DNS related threat data; filter the DNS related event data using the set of network related threat data to obtain filtered DNS related event data; and generate a whitelist using the filtered DNS related event data, wherein the whitelist includes a subset of network domains included in the DNS related event data based on a data driven model of the DNS related event data and the DNS related threat data, wherein the generating of the whitelist comprises to: determine a top N domains based on the filtered DNS related event data; and filter the top N domains to obtain the whitelist, wherein the filtering of the top N domains comprises to: remove domains that are known threats from the top N domains to obtain an updated top N domains; and output domains in the updated top N domains to the whitelist; output the whitelist to a network device for filtering DNS requests using the whitelist.
However, Cooley teaches:
receive a set of network related threat data, – on lines 1-67 in columns 2-18 (Domain reputation information may be obtained from and/or stored within any suitable service or system. Obtaining knowledge about threats from and/or reputations of Internet domains, along with knowledge of Internet domain traffic patterns.)
wherein the set of network related threat data includes DNS related threat data; – on lines 1-67 in columns 2-18 (Obtaining knowledge about threats from and/or reputations of Internet domains, along with knowledge of Internet domain traffic patterns.)
filter the DNS related event data using the set of network related threat data to obtain filtered DNS related event data; and – on lines 1-67 in columns 2-18 (Select all Internet domains with reputations above a predetermined threshold and traffic volume higher than a predetermined threshold.)
generate a whitelist using the filtered DNS related event data, – on lines 1-67 in columns 2-18 (Selection module 108 may select the subset of Internet domains for use in default whitelists and/or whitelists that are customized for particular users and/or gateways systems.)
wherein the whitelist includes a subset of network domains included in the DNS related event data based on a data driven model of the DNS related event data and the DNS related threat data, – on lines 1-67 in columns 2-18 (Selection module 108 may select all Internet domains with reputations above a predetermined threshold and traffic volume higher than a predetermined threshold. In addition to evaluating reputation and traffic volume information, selection module 108 may consider a variety of other types of information in determining which Internet domains are to be selected for inclusion in a domain whitelist. Selection module 108 may consider the types of data typically provided by an Internet domain to determine whether the Internet domain should be selected for inclusion in a whitelist.)
wherein the generating of the whitelist comprises to: determine a top N domains based on the filtered DNS related event data; and – on lines 1-67 in columns 2-18 (Selection module 108 may select all Internet domains with reputations above a predetermined threshold and traffic volume higher than a predetermined threshold. In addition to evaluating reputation and traffic volume information, selection module 108 may consider a variety of other types of information in determining which Internet domains are to be selected for inclusion in a domain whitelist. Selection module 108 may consider the types of data typically provided by an Internet domain to determine whether the Internet domain should be selected for inclusion in a whitelist.)
filter the top N domains to obtain the whitelist, – on lines 1-67 in columns 2-18 (Selection module 108 may select all Internet domains with reputations above a predetermined threshold and traffic volume higher than a predetermined threshold.)
wherein the filtering of the top N domains comprises to: remove domains that are known threats from the top N domains to obtain an updated top N domains; and – on lines 1-67 in columns 2-18 (Whitelist module 110 may include a high-level domain in Internet domain whitelist 126 while excluding one or more sub-domains of the high-level domain. Selection module 108 may select all Internet domains with reputations above a predetermined threshold and traffic volume higher than a predetermined threshold. By obtaining knowledge about threats from and/or reputations of Internet domains, along with knowledge of Internet domain traffic patterns, embodiments of the instant disclosure may generate and deliver a database of trusted domains that may be small enough to be effectively delivered and leveraged on resource-constrained gateways while being large enough to cover the most popular high-traffic websites.)
output domains in the updated top N domains to the whitelist; – on lines 1-67 in columns 2-18 (Selection module 108 may select the subset of Internet domains for use in default whitelists and/or whitelists that are customized for particular users and/or gateways systems, as discussed in greater detail below.)
output the whitelist to a network device for filtering DNS requests using the whitelist; and – on lines 1-67 in columns 2-18 (Selection module 108 may select the subset of Internet domains for use in default whitelists and/or whitelists that are customized for particular users and/or gateways systems, as discussed in greater detail below.)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Kislitsin with Cooley to include receive a set of network related threat data, wherein the set of network related threat data includes DNS related threat data; filter the DNS related event data using the set of network related threat data to obtain filtered DNS related event data; and generate a whitelist using the filtered DNS related event data, wherein the whitelist includes a subset of network domains included in the DNS related event data based on a data driven model of the DNS related event data and the DNS related threat data, wherein the generating of the whitelist comprises to: determine a top N domains based on the filtered DNS related event data; and filter the top N domains to obtain the whitelist, wherein the filtering of the top N domains comprises to: remove domains that are known threats from the top N domains to obtain an updated top N domains; and output domains in the updated top N domains to the whitelist; output the whitelist to a network device for filtering DNS requests using the whitelist, as taught by Cooley, on lines 1-67 in columns 1-4, to perform security scans on incoming traffic to identify and block malicious Internet content.
Combination of Kislitsin and Cooley does not explicitly teach:
identify a network domain for further evaluation to determine whether the network domain is properly included on a blacklist.
However, Lin teaches:
identify a network domain for further evaluation to determine whether the network domain is properly included on a blacklist; and – on lines 1-67 in columns 2-9 (The placement of a URL on a blacklist may not immediately result in its exclusion from distribution to users of the online system, but may instead flag it as suspicious and requiring further administrative review by the online system.)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Kislitsin and Cooley with Lin to include identify a network domain for further evaluation to determine whether the network domain is properly included on a blacklist, as taught by Lin, on lines 1-67 in columns 1-2, to identify webpages with a high likelihood of providing a low quality user experience and prevent them from being presented to users of the online system.
2, 12, 17. The system recited in claim 1,
Kislitsin teaches:
wherein the DNS related event data includes a set of popular network domains. – in paragraphs [0041]-[0152] (The updating can be executed on the basis of the list of popular sites from a given one of these rating sites (or lists from multiple rating sites), as well as a summary list of popular sites compiled by the analyzing module 1.3 on the basis of separate lists of popular domain names obtained from each of these rating sites, by, for example, a comparative assessment of popularity indicators assigned to sites in these separate lists, in accordance with a given set of evaluation rules to identify a given number of the most popular sites.)
3, 13, 18. The system recited in claim 1,
Cooley teaches:
wherein the DNS related threat data includes a DNS threat feed. – on lines 1-67 in columns 2-18 (Domain reputation information may be obtained from and/or stored within any suitable service or system. Obtaining knowledge about threats from and/or reputations of Internet domains, along with knowledge of Internet domain traffic patterns.)
10. The system recited in claim 1,
Lin teaches:
wherein the processor is further configured to: identify a network domain for further evaluation to determine whether the network domain is properly included on a blacklist. – on lines 1-67 in columns 2-9 (The placement of a URL on a blacklist may not immediately result in its exclusion from distribution to users of the online system, but may instead flag it as suspicious and requiring further administrative review by the online system.)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Kislitsin and Cooley with Lin to include wherein the processor is further configured to: identify a network domain for further evaluation to determine whether the network domain is properly included on a blacklist, as taught by Lin, on lines 1-67 in columns 1-2, to identify webpages with a high likelihood of providing a low quality user experience and prevent them from being presented to users of the online system.
Claim(s) 4, 14, 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kislitsin (US 20190222589) in view of Cooley (US 9832209), and further in view of Lin (US 10853431) and Harris (US 20160173510).
4, 14, 19. The system recited in claim 1,
Combination of Kislitsin, Cooley, and Lin does not explicitly teach:
wherein the DNS related threat data includes a DNS threat feed that is associated with a first enterprise network.
However, Harris teaches:
wherein the DNS related threat data includes a DNS threat feed that is associated with a first enterprise network. – in paragraphs [0004]-[0172] (A remote threat management facility configured to manage threats to an enterprise; and a plurality of devices associated with the enterprise, where each of the plurality of devices has a memory and a processor, the memory storing a URL cache including a reputation score and a time to live for each of a plurality of URLs, and the processor configured to update the URL cache on each of the plurality of devices using reputation scores from the remote threat management facility to add new entries for new URL traffic to the URL cache and using the time to live to expire existing entries from the URL cache.)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Kislitsin, Cooley, and Lin with Harris to include wherein the DNS related threat data includes a DNS threat feed that is associated with a first enterprise network, as taught by Harris, in paragraphs [0002]-[0034], to provide techniques for threat detection in an enterprise network.
Claim(s) 5, 15, 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kislitsin (US 20190222589) in view of Cooley (US 9832209), and further in view of Lin (US 10853431) and Xu (US 20170163603).
5, 15, 20. The system recited in claim 1,
Combination of Kislitsin, Cooley, and Lin does not explicitly teach:
wherein the DNS related threat data includes a DNS threat feed that is automatically filtered to determine a popularity of network domains associated with malware.
However, Xu teaches:
wherein the DNS related threat data includes a DNS threat feed that is automatically filtered to determine a popularity of network domains associated with malware. – in paragraphs [0018]-[0109] (An additional filtering operation can be performed using a DGA-domain prediction to filter out time-sensitive DGA domains (DGA-generated domain names) from the ranked listing of popular NX domains, because such NX domains would typically only be used for at most one day by such C&C malware.)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Kislitsin, Cooley, and Lin with Xu to include wherein the DNS related threat data includes a DNS threat feed that is automatically filtered to determine a popularity of network domains associated with malware, as taught by Xu, in paragraphs [0002]-[0051], to identify and prevent the further spread of malware in a network.
Claim(s) 6-9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kislitsin (US 20190222589) in view of Cooley (US 9832209), and further in view of Lin (US 10853431) and Balduzzi (US 10057279).
6. The system recited in claim 1,
Combination of Kislitsin, Cooley, and Lin does not explicitly teach:
wherein the subset of network domains included in the whitelist are selected using a classifier.
However, Balduzzi teaches:
wherein the subset of network domains included in the whitelist are selected using a classifier. – on lines 1-67 in columns 2-14 (The URL classifier 152 may be configured to distinguish between malicious and benign URLs.)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Kislitsin, Cooley, and Lin with Balduzzi to include wherein the subset of network domains included in the whitelist are selected using a classifier, as taught by Balduzzi, on lines 1-67 in columns 1-2, to provide a technique for protecting computers against remote malware downloads includes a malware download detection system and participating client computers that provide download event information to the malware download detection system.
7. The system recited in claim 1,
Combination of Kislitsin, Cooley, and Lin does not explicitly teach:
wherein the subset of network domains included in the whitelist are selected using a statistical classifier.
However, Balduzzi teaches:
wherein the subset of network domains included in the whitelist are selected using a statistical classifier. – on lines 1-67 in columns 2-14 (The URL classifier 152 may be configured to distinguish between malicious and benign URLs. The URL classifier 152 may comprise a statistical classifier that is configured to classify the source URL of the downloaded file.)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Kislitsin, Cooley, and Lin with Balduzzi to include wherein the subset of network domains included in the whitelist are selected using a statistical classifier, as taught by Balduzzi, on lines 1-67 in columns 1-2, to provide a technique for protecting computers against remote malware downloads includes a malware download detection system and participating client computers that provide download event information to the malware download detection system.
8. The system recited in claim 1,
Cooley teaches:
the processor is further configured to: output the whitelist to a network device for filtering DNS requests using the whitelist. – on lines 1-67 in columns 2-18 (Selection module 108 may select the subset of Internet domains for use in default whitelists and/or whitelists that are customized for particular users and/or gateways systems.)
Combination of Kislitsin, Cooley, and Lin does not explicitly teach:
wherein: the DNS related event data is automatically filtered using a classifier to exclude one or more network domains associated with malware.
However, Balduzzi teaches:
wherein: the DNS related event data is automatically filtered using a classifier to exclude one or more network domains associated with malware; and – on lines 1-67 in columns 2-14 (Consider u is an unknown URL and that all of its neighbors are unknown nodes, so they cannot contribute meaningfully to classifying u. Nonetheless, if u shares the same URL path with a group of malicious URLs (because, for example, they were generated by the same malware kit), and if there are some known malware files or infected client machines connected to this group of malicious URLs in the download graph 153, the group of malicious URLs will have an impact on accurately labeling u as malicious, because the badness reputation score custom character of the group of malicious URLs will be used to compute some features of u.)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Kislitsin, Cooley, and Lin with Balduzzi to include wherein: the DNS related event data is automatically filtered using a classifier to exclude one or more network domains associated with malware, as taught by Balduzzi, on lines 1-67 in columns 1-2, to provide a technique for protecting computers against remote malware downloads includes a malware download detection system and participating client computers that provide download event information to the malware download detection system.
9. The system recited in claim 1,
Cooley teaches:
the processor is further configured to: periodically update the whitelist based on another set of network related event data and another set of network related threat data, – on lines 1-67 in columns 2-18 (Network gateway system 230 may use Internet domain whitelist 126 as an initial whitelist, may use Internet domain whitelist 126 to update an existing whitelist (e.g., whitelist 232), and/or may use Internet domain whitelist 126 to replace an existing whitelist.)
wherein the whitelist is automatically and dynamically adjusted to changes in a production data environment associated with a first enterprise network. – on lines 1-67 in columns 2-18 (Network gateway system 230 may use Internet domain whitelist 126 as an initial whitelist, may use Internet domain whitelist 126 to update an existing whitelist (e.g., whitelist 232), and/or may use Internet domain whitelist 126 to replace an existing whitelist.)
Combination of Kislitsin, Cooley, and Lin does not explicitly teach:
wherein: the DNS related event data is automatically filtered using a classifier to exclude one or more network domains associated with malware.
However, Balduzzi teaches:
wherein: the DNS related event data is automatically filtered using a classifier to exclude one or more network domains associated with malware; and – on lines 1-67 in columns 2-14 (Consider u is an unknown URL and that all of its neighbors are unknown nodes, so they cannot contribute meaningfully to classifying u. Nonetheless, if u shares the same URL path with a group of malicious URLs (because, for example, they were generated by the same malware kit), and if there are some known malware files or infected client machines connected to this group of malicious URLs in the download graph 153, the group of malicious URLs will have an impact on accurately labeling u as malicious, because the badness reputation score custom character of the group of malicious URLs will be used to compute some features of u.)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Kislitsin, Cooley, and Lin with Balduzzi to include wherein: the DNS related event data is automatically filtered using a classifier to exclude one or more network domains associated with malware, as taught by Balduzzi, on lines 1-67 in columns 1-2, to provide a technique for protecting computers against remote malware downloads includes a malware download detection system and participating client computers that provide download event information to the malware download detection system.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/MUHAMMAD RAZA/Primary Examiner, Art Unit 2449
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