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 Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-2, 4-5, 8-9, 11-12, 15, 17-18 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Lee (US 2022/0377107)
Regarding Claim 1,
Lee (US 2022/0377107) teaches a method comprising steps of:
receiving an original target domain and a lookalike domain (Paragraph [0092] teaches dataset comprising domains and their possible lookalikes was used);
converting the original target domain and the lookalike domain into pixelated images (Paragraph [0092] teaches “the entire dataset is provided to an image renderer”)(Fig. 7, 704);
calculating a similarity via a trained Convolutional Neural Network (CNN) based on the pixelated images of the original target domain and the lookalike domain (Paragraph [0096] teaches encoder may comprise a “Convolutional Neural Network (CNN))”);
and providing a similarity score based on the similarity (Paragraph [0101] teaches “a similarity comparison of the encoding of the queried domain is then carried out with the encodings in the database”)(Also see Fig. 7 and 8).
Regarding Claim 2,
Lee teaches the method of claim 1, wherein the steps comprise training the CNN prior to the receiving (Paragraph [0090-0091] teaches training a Phish-GAN such as a convolutional neural network)
Regarding Claim 4,
Lee teaches the method of claim 1, wherein the steps include generating a plurality of lookalike domains based on a plurality of legitimate domains of a customer
(Paragraph [0073, 0079, 0092] teaches generating lookalike phishing domains based on legitimate domains)
Regarding Claim 5,
Lee teaches the method of claim 4, wherein the generating includes systematically creating domain permutations by applying one or more domain modification techniques (Paragraphs [0073-0074]).
Regarding Claims 8-9, 11-12,
Claims 8-9, 11-12 are similar in scope to Claims 1-2, 4-5 and are rejected for a similar rationale.
Regarding Claims 15, 17-18,
Claims 15, 17-18 are similar in scope to Claims 1, 4-5 and are rejected for a similar rationale.
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) 3, 10, 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lee in view of Wang (US 2021/0150268)
Regarding Claim 3,
Lee teaches the method of claim 1. Lee teaches retrieving CNN weights from storage (Paragraph [0109] and Table 2 teaches CNN filters)
But Lee does not explicitly teach wherein the calculating comprises:
converting the pixelated images of the original target domain and the lookalike domain to greyscale; concatenating the pixelated images together; feeding the concatenated images into the CNN; and determining a similarity based thereon.
Wang (US 2021/0150268) teaches concatenating the pixelated images together; feeding the concatenated images into the CNN; and determining a similarity based thereon (Paragraph [0006, 0011] teaches concatenation of two input images and the result is sent to the convolutional neural network to calculate similarity)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Lee with the method of concatenating images together and feeding the images into a CNN as taught by Wang and the results would be predictable (i.e. images would be concatenated, the result fed into a CNN to determine similarity)
While Wang teaches converting the images to color, Wang does not explicitly teach
converting the pixelated images of the original target domain and the lookalike domain to greyscale;
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to convert images of the original and lookalike domain to greyscale and the results would be predictable (i.e. the images of the original and lookalike domain would be converted to greyscale)
Regarding Claims 10, 16
Claims 10, 16 are similar in scope to Claim 3 and are rejected for a similar rationale.
Claim(s) 6-7, 13-14, 19-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lee
Regarding Claim 6,
Lee teaches the method of claim 1. While Lee teaches a similarity score (Paragraph [0113] teaches “similarity score”), a phishing score (Paragraph [0082] teaches a probability score that the domain is phishing) and a context similarity score (Paragraph [0083] teaches rule-based filtering modules), Lee does not explicitly teach wherein the steps further compromise generating a comprehensive risk score based on the similarity score, a phishing score, and a context similarity score.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine the phishing, similarity and context score of Lee to generate a comprehensive risk score and the results would be predictable (i.e. a comprehensive risk score would be generated using phishing, similarity and context scores of Lee)
Regarding Claim 7,
Lee teaches the method of claim 6. While Lee teaches actionable items (Paragraph [0154-0155]) and user interface (Paragraph [0086] teaches “user interface”), Lee does not explicitly teach wherein the steps further comprise displaying the risk score along with recommended actionable items within a User Interface (UI).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Lee to include displaying the risk score and recommended actionable items within a UI and the results would be predictable
Regarding Claims 13-14, 19-20
Claims 13-14, 19-20 are similar in scope to Claims 6-7 and are rejected for a similar rationale.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HARRIS C WANG whose telephone number is (571)270-1462. The examiner can normally be reached M-F 9:00-5:30.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, LUU PHAM can be reached at 571-270-5002. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/HARRIS C WANG/Primary Examiner, Art Unit 2439
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