Richard Hallock Awarded Patent in Cybercrime Industry

Cybercrime is a growing threat not only in the United States but around the world. Experts claim that the inability to quickly, efficiently, and accurately identify individuals online is at the very center of this epidemic. Researchers report over 43,000 cybercrimes in 2017 were facilitated by leveraged credentials. Hallock’s patented methodology announced today can significantly impact and reduce the incidence of cybercrimes leveraged by the use of hijacked or spoofed credentials.

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Current Processes

Cybercrime is at an all-time high, and the collective reliance on flawed credentials-based identification is behind it. As it stands, these methods do little more than “assume” an individual’s identity based on the credential information an unknown person in a remote location provides. Credentials are statically stored of necessity of the process and subject to harvesting. Proofs of identity such as passwords, phrases, PINs, SSN’s and even biometrics are easily hijacked or spoofed, and the same is true even where multi-factor verification is employed.

In order to reduce the occurrence of cybercrime and make it more difficult for bad actors to leverage the credentials of others, Hallock has invented a method to use human traits to identify people. It is based on the notion that a smartphone – a device that almost everyone carries – would learn the owner’s human traits over time by use of sensors and AI. Then, when verifying another’s identity, all that is needed is the individual’s phone number to obtain their smartphone possession status. A process within, employing the same AI and sensors, evaluates the human traits of the person in possession as an active process. Positive results establish the individual in possession is whom he or she claims to be, the owner. Fulltime adaptive learning of owner human traits ensures longevity and accuracy.

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The Impact of Hallock’s Patent

Today’s methods of identity verification depend on very personal information and credentials such as passwords, phrases, biometrics, last four, SSN, and PINs. When cybercriminals gain access to this information, they can use it to access the victim’s personal and business networks and online accounts, computers, facilities, vehicles and much, much more. The goal of Hallock’s patent involves using data that means very little to a criminal – information such as a person’s name and phone number – to effectively “read” someone’s identity from a device in their possession using incredibly smart and sophisticated machine learning and prediction processes. These processes project identity of the person in possession of their human traits.

Consumers and users benefit in numerous ways. While enjoying assured security, they can self-identify easily, and without the need to create passwords, scan fingerprints, or take selfies to do so. The process is frictionless, requiring no periodic updates. There are no credentials for criminals to harvest or spoof, and above all else, there is no practical way for a cybercriminal to “hack”, “spoof” or defeat the system.

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