Paul E. Black, a scientist at the National Institute of Standards and Technology (NIST) has developed an algorithm that may guide applicants in proposing new 鈥渢op-level domains鈥?such as .com, that people type in navigating the Web.
The algorithm has been made at the request Internet Corporation for Assigned Names and Numbers (ICANN), which checks whether the newly proposed name is confusingly similar to existing ones by looking for visual likenesses in its appearance.
Having visually distinct top-level domain names may help avoid confusion in navigating the ever-expanding Internet and combat fraud, by reducing the potential to create malicious look-alikes: .C0M with a zero instead of .COM, for instance.
ICANN is planning to launch the process for proposing a new round of 鈥済eneric鈥?top-level domains (gTLDs), strings such as .net, .gov and .org meant to indicate organizations or interests. In preparing for newly proposed gTLDs, ICANN reached out to various algorithm developers, including this one, as among those engaged to 鈥減rovide an open, objective, and predictable mechanism for assessing the degree of visual confusion鈥?in gTLDs.
Black鈥檚 algorithm which can be found here compares a proposed gTLD with other TLDs and generates a score based on their visual similarities. For example, the domain .C0M scores an 88 percent visual similarity with the familiar .COM. The resulting scores may help indicate whether the newly proposed domain name looks too much like existing ones.
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The algorithm has been made at the request Internet Corporation for Assigned Names and Numbers (ICANN), which checks whether the newly proposed name is confusingly similar to existing ones by looking for visual likenesses in its appearance.
Having visually distinct top-level domain names may help avoid confusion in navigating the ever-expanding Internet and combat fraud, by reducing the potential to create malicious look-alikes: .C0M with a zero instead of .COM, for instance.
ICANN is planning to launch the process for proposing a new round of 鈥済eneric鈥?top-level domains (gTLDs), strings such as .net, .gov and .org meant to indicate organizations or interests. In preparing for newly proposed gTLDs, ICANN reached out to various algorithm developers, including this one, as among those engaged to 鈥減rovide an open, objective, and predictable mechanism for assessing the degree of visual confusion鈥?in gTLDs.
Black鈥檚 algorithm which can be found here compares a proposed gTLD with other TLDs and generates a score based on their visual similarities. For example, the domain .C0M scores an 88 percent visual similarity with the familiar .COM. The resulting scores may help indicate whether the newly proposed domain name looks too much like existing ones.
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