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 .
Claim Objections
Claim 4 is objected to because of the following informalities: claim 4 has a double period. Appropriate correction is required.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-15 of U.S. Patent No. 11,388,142. Although the claims at issue are not identical, they are not patentably distinct from each other because the claim limitations are similar in wording and concepts.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-15 of U.S. Patent No. 11,909,722. Although the claims at issue are not identical, they are not patentably distinct from each other because the claim limitations are similar in wording and concepts.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-18 of U.S. Patent No. 12,309,120. Although the claims at issue are not identical, they are not patentably distinct from each other because the claim limitations are similar in wording and concepts.
19/184,242
11,388,142
11,909,722
12,309,120
1. A system, comprising:
a processor configured to:
generate training and test data sets for images of characters for domain names;
train a homograph classifier using the training and test data sets to recognize Unicode characters that are visually similar to one or more ASCII characters; and
execute the homograph classifier over a set of Unicode characters to generate an ASCII to Unicode map,
wherein the homograph classifier is executed over the set of Unicode characters to map an ASCII character to each Unicode character in the set of Unicode characters based on visual similarity to obtain the ASCII to Unicode map; and
a memory coupled to the processor and configured to provide the processor with instructions.
1. A system, comprising:
a processor configured to:
receive a DNS data stream, wherein the DNS data stream includes a DNS query and a DNS response for resolution of the DNS query;
apply a homograph detector for a domain in the DNS data stream, comprising to:
decode the domain to Unicode;
map each character of the Unicode to an ASCII character using an ASCII to Unicode map,
wherein the ASCII to Unicode map is generated using a convolutional neural network and trained using training data; and
perform one or more of the following:
A) perform a lookup on a target list; and identify matches based on the lookup;
B) apply similarity score metrics; and
identify nearby/close matches based on threshold similarity scores; and/or
C) implement a k-nearest neighbor; and identify matches based on k-NN threshold distance results; and
detect a homograph of a domain name in the DNS data stream using the homograph detector; and
a memory coupled to the processor and configured to provide the processor with instructions.
1. A system, comprising:
a processor configured to:
generate training and test data sets for images of characters for domain names;
train a homograph classifier using the training and test data sets to recognize Unicode characters that are visually similar to one or more ASCII characters,
wherein a convolutional neural network (CNN) architecture is used to train the homograph classifier,
wherein the CNN architecture learns a filter to detect a pattern for a prediction, and
wherein a presence of the pattern or a lack of the pattern is used by the CNN architecture to make the prediction; and
execute the homograph classifier over a set of Unicode characters to generate an ASCII to Unicode map; and
a memory coupled to the processor and configured to provide the processor with instructions.
1. A system, comprising:
a processor configured to:
receive a DNS data stream, wherein the DNS data stream includes a DNS query and a DNS response for resolution of the DNS query;
apply a homograph detector for each domain in the DNS data stream; and
detect a homograph of a domain name in the DNS data stream using the homograph detector,
wherein the homograph detector is generated using a deep neural network technique and training data, and
wherein the deep neural network technique includes a recurrent neural network (RNN) technique, a K-Means clustering technique,
a support vector machine (SVM) technique or any combination thereof; and
a memory coupled to the processor and configured to provide the processor with instructions.
Claim Rejections - 35 USC § 103
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) 1-5, 8-12, 15-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Maylor et al., (US Publication No. 2017/0078321), hereinafter “Maylor”, and further in view of Brown et al., (US Patent No. 10,943,067), hereinafter “Brown”.
Regarding claims 1, 8, 15 Maylor discloses
a processor [Maylor, paragraph 79] configured to:
execute the homograph classifier over a set of Unicode characters to generate an ASCII to Unicode map, wherein the homograph classifier is executed over the set of Unicode characters to map an ASCII character to each Unicode character in the set of Unicode characters based on visual similarity to obtain the ASCII to Unicode map [Maylor, paragraph 111, mapping Unicode to ascii]; and
a memory coupled to the processor and configured to provide the processor with instructions [Maylor, paragraph 78-79].
Maylor does not specifically disclose, however Brown teaches
generate training and test data sets for images of characters for domain names [Brown, column 1, lines 5-14, column 2, lines 46-67, column 9, lines 47-58];
train a homograph classifier using the training and test data sets to recognize Unicode characters that are visually similar to one or more ASCII characters [Brown, column 1, lines 5-14, column 2, lines 46-67, column 9, lines 47-58].
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include training using machine learning the data related to homograph data of Maylor in order to provide for tracking possible malicious domain names for security. It would have been obvious to combine Brown with Maylor as each art relates to a similar concept.
Regarding claims 2, 9, 16 Maylor-Brown further discloses
wherein the processor is further configured to update the homograph classifier to obtain an updated ASCII to Unicode map [Brown, column 1, lines 5-14, column 2, lines 46-67, column 9, lines 47-58].
Regarding claims 3, 10, 17 Maylor-Brown further discloses
wherein the processor is further configured to update the homograph classifier to obtain an updated ASCII to Unicode map, and wherein the updated ASCII to Unicode map includes a new Unicode character [Brown, column 1, lines 5-14, column 2, lines 5-16, column 9, lines 47-58].
Regarding claims 4, 11, 18 Maylor-Brown further discloses
wherein the homograph classifier is trained using a machine learning technique [Brown, column 1, lines 5-14, column 2, lines 46-67, column 9, lines 47-58].
Regarding claims 5, 12, 19 Maylor-Brown further discloses
wherein the processor is further configured to deploy the homograph classifier to provide an inline homograph detection model for automatically detecting homographs of domain names on a DNS data stream [Brown, column 1, lines 5-14, column 2, lines 46-67, column 9, lines 47-58].
Claim(s) 6-7, 13-14, 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Maylor-Brown as applied to claims 1, 8, 15 above, and further in view of Senior et al., (US Publication No. 2017/0011738), hereinafter “Senior”.
Regarding claims 6, 13, 20 Maylor-Brown does not specifically disclose, however Senior teaches
wherein a convolutional neural network (CNN) architecture is used to train the homograph classifier [Senior, paragraphs 38-39].
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include training using machine learning neural networks including CNN and RNN in order to provide the most efficient neural network model for security of the system. It would have been obvious to combine Brown-Senior with Maylor as each art relates to a similar concept.
Regarding claims 7, 14 Maylor-Brown-Senior further discloses
wherein a recurrent neural network (RNN) architecture is used to train the homograph classifier [Senior, paragraphs 38-39].
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WILLIAM J GOODCHILD whose telephone number is (571)270-1589. The examiner can normally be reached M-F 8am-4:30pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jeff Pwu can be reached at 571-272-6798. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/William J. Goodchild/Primary Examiner, Art Unit 2433
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