Donald J Mcqueen

US Patent:

20220335099, Oct 20, 2022

Filed:

Jul 1, 2022

Appl. No.:

17/810375

Inventors:

- Basking Ridge NJ, US
Donald J. MCQUEEN - Leesburg VA, US

International Classification:

G06F 16/9535
H04L 51/04
H04W 4/21
H04L 51/52

Abstract:

Systems, methods, and computer-readable media are provided for pairing users for electronic communications over a network. In accordance with one implementation, a method is provided for pairing users that request a chat encounter or other form of electronic communication. The operations of the method include receiving a request from a first user and calculating a plurality of pairing scores, each pairing score based on a collaborative filtering score. The method further includes selecting a second user based on the plurality of pairing scores and pairing the first user with the second user to enable electronic communications.

US Patent:

20220210175, Jun 30, 2022

Filed:

Mar 21, 2022

Appl. No.:

17/655640

Inventors:

- New York NY, US
Donald J. MCQUEEN - Leesburg VA, US

International Classification:

H04L 9/40
H04W 12/63

Abstract:

Systems and methods are disclosed for identifying malicious traffic associated with a website. One method includes receiving website traffic metadata comprising a plurality of variables, the website traffic metadata being associated with a plurality of website visitors to the website; determining a total number of occurrences associated with at least two of the plurality of variables of the website traffic metadata; generating a plurality of pairs comprising combinations of the plurality of variables of the website traffic metadata; determining a total number of occurrences associated with each pair of the plurality of pairs of combinations of the plurality of variables of the website traffic metadata; determining a plurality of visitor actions associated with the plurality of variables of the website traffic metadata; clustering each of the plurality of pairs and the plurality of visitor actions associated with the plurality of variables of the website traffic metadata into groups; and determining, based on the clustering of the plurality of pairs and the plurality of visitor actions, whether each of the plurality of website visitors are malicious visitors.

US Patent:

20230029211, Jan 26, 2023

Filed:

Oct 3, 2022

Appl. No.:

17/937563

Inventors:

- Dulles VA, US
Donald J. MCQUEEN - Leesburg VA, US
Paul S. Rock - Leesburg VA, US

International Classification:

H04L 9/40
G06F 7/08
G06N 20/00

Abstract:

Systems and methods are disclosed for utilizing sender-recipient pair data to establish sender-level trust in future communication. One method comprises receiving raw communication data over a network and testing the received raw communication data against trained machine learning data to predict whether the raw communication data is associated with expected communication data. The raw communication data is sorted for expected communication data, which is further analyzed for sender-recipient pair data and assigned an expected communication pair data score. Senders associated with an expected communication pair data score that meets or exceeds a threshold are labeled and stored in a database as trusted. As a result of the sender-recipient pair analysis, recipients at-risk for being scammed can be identified, senders misidentified as spammers can be properly classified, and machine learning techniques utilized for analyzing raw communication data can be fine-tuned.

US Patent:

20200382542, Dec 3, 2020

Filed:

Aug 17, 2020

Appl. No.:

16/995347

Inventors:

- Dulles VA, US
Donald J. McQueen - Leesburg VA, US

International Classification:

H04L 29/06
H04W 12/00

Abstract:

Systems and methods are disclosed for identifying malicious traffic associated with a website. One method includes receiving website traffic metadata comprising a plurality of variables, the website traffic metadata being associated with a plurality of website visitors to the website; determining a total number of occurrences associated with at least two of the plurality of variables of the website traffic metadata; generating a plurality of pairs comprising combinations of the plurality of variables of the website traffic metadata; determining a total number of occurrences associated with each pair of the plurality of pairs of combinations of the plurality of variables of the website traffic metadata; determining a plurality of visitor actions associated with the plurality of variables of the website traffic metadata; clustering each of the plurality of pairs and the plurality of visitor actions associated with the plurality of variables of the website traffic metadata into groups; and determining, based on the clustering of the plurality of pairs and the plurality of visitor actions, whether each of the plurality of website visitors are malicious visitors.

US Patent:

20200145452, May 7, 2020

Filed:

Jan 6, 2020

Appl. No.:

16/734630

Inventors:

- New York NY, US
Donald J. McQueen - Leesburg VA, US

International Classification:

H04L 29/06
G06F 21/46

Abstract:

Systems and methods are disclosed for analyzing a plurality of failed login records that correspond to failed login attempts detected by a computing system, to identify suspicious patterns of activity that can facilitate the supplementation of password blacklists for improving account security. To accomplish the foregoing, failed login records that include information associated with failed login attempts are obtained for analysis. The failed login records are analyzed to identify a set of failed login records that show initial characteristics of a suspicious pattern of activity. The information included in the set of failed login records are further analyzed to determine whether a suspicious pattern of activity is actually present. When a suspicious pattern of activity is identified in the set of failed login records, the passwords used in the failed login attempts are stored in password blacklists associated with the account identifier(s) with which the passwords were used.

US Patent:

20190253451, Aug 15, 2019

Filed:

Apr 23, 2019

Appl. No.:

16/392367

Inventors:

- New York NY, US
Donald J. McQueen - Leesburg VA, US

International Classification:

H04L 29/06
G06F 21/46

Abstract:

Systems and methods are disclosed for analyzing a plurality of failed login records that correspond to failed login attempts detected by a computing system, to identify suspicious patterns of activity that can facilitate the supplementation of password blacklists for improving account security. To accomplish the foregoing, failed login records that include information associated with failed login attempts are obtained for analysis. The failed login records are analyzed to identify a set of failed login records that show initial characteristics of a suspicious pattern of activity. The information included in the set of failed login records are further analyzed to determine whether a suspicious pattern of activity is actually present. When a suspicious pattern of activity is identified in the set of failed login records, the passwords used in the failed login attempts are stored in password blacklists associated with the account identifier(s) with which the passwords were used.

US Patent:

20190104145, Apr 4, 2019

Filed:

Nov 30, 2018

Appl. No.:

16/205919

Inventors:

- Dulles VA, US
Donald J. MCQUEEN - Leesburg VA, US

International Classification:

H04L 29/06

Abstract:

Systems and methods are disclosed for identifying malicious traffic associated with a website. One method includes receiving website traffic metadata comprising a plurality of variables, the website traffic metadata being associated with a plurality of website visitors to the website; determining a total number of occurrences associated with at least two of the plurality of variables of the website traffic metadata; generating a plurality of pairs comprising combinations of the plurality of variables of the website traffic metadata; determining a total number of occurrences associated with each pair of the plurality of pairs of combinations of the plurality of variables of the website traffic metadata; determining a plurality of visitor actions associated with the plurality of variables of the website traffic metadata; clustering each of the plurality of pairs and the plurality of visitor actions associated with the plurality of variables of the website traffic metadata into groups; and determining, based on the clustering of the plurality of pairs and the plurality of visitor actions, whether each of the plurality of website visitors are malicious visitors.

US Patent:

20180332058, Nov 15, 2018

Filed:

May 9, 2017

Appl. No.:

15/590303

Inventors:

- Dulles VA, US
Donald J. McQueen - Leesburg VA, US

International Classification:

H04L 29/06

Abstract:

Systems and methods are disclosed for identifying malicious traffic associated with a website. One method includes receiving website traffic metadata comprising a plurality of variables, the website traffic metadata being associated with a plurality of website visitors to the website; determining a total number of occurrences associated with at least two of the plurality of variables of the website traffic metadata; generating a plurality of pairs comprising combinations of the plurality of variables of the website traffic metadata; determining a total number of occurrences associated with each pair of the plurality of pairs of combinations of the plurality of variables of the website traffic metadata; determining a plurality of visitor actions associated with the plurality of variables of the website traffic metadata; clustering each of the plurality of pairs and the plurality of visitor actions associated with the plurality of variables of the website traffic metadata into groups; and determining, based on the clustering of the plurality of pairs and the plurality of visitor actions, whether each of the plurality of website visitors are malicious visitors.