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Fabulous also offers premium services such as a built-in sales network, parking program, and full reporting features. The company's domain management system is designed to help domainers maximize performance and financial return, with features such as bulk management tools, click tracking, and statistics reporting. With Fabulous, domain owners can register, manage, and monetize their domains effectively, making it an ideal choice for those in the domain industry.

Jeu de données reprenant l'ensemble des infos sur les jeux de données de la plateforme

National Domain Name (DN) Registration Quantity Statistics Table

An incomplete collection of open data domains throughout the U.S. (intended for comparison with King County open data)

As of August 2024, the most popular new generic top-level domain (gTLD) was .xyz with approximately 4.16 million domains, accounting for16.71 percent of gTLDs. The second-most popular gTLD was .online with 3.63 million registrations. Domains that do not have a country or geographic designation are often referred to by the term generic TLDs.

Introduction

Web Hosting Statistics: If you're starting or growing your online business, picking the right web hosting provider should be your top priority. Many people need to think more about choosing a web host. Still, it's actually very important because it affects things like how fast your pages load, your Google ranking, and your website's security.

That's why we've put together a list of key statistics to show how web hosting impacts businesses. Let's take a look at some of these important Web Hosting Statistics in this article.

Business Software Alliance is a trade association that represents the world's leading software companies, including Autodesk, IBM, and Symantec. The organization's members are committed to promoting the use of legitimate software and ensuring the integrity of their intellectual property.

As a result, the data housed on BSA's website is rich in information related to the software industry, including software licensing, anti-piracy efforts, and digital piracy statistics. The data includes information on software usage, software development, and the impact of piracy on the technology industry. With its focus on promoting legitimate software use, the data on BSA's website provides valuable insights into the global software industry.

The dataset contains DNS records, IP-related features, WHOIS/RDAP information, information from TLS certificate fields, and GeoIP information for 432,572 verified benign domains from Cisco Umbrella and 36,993 verified phishing domains from PhishTank and OpenPhish services. The dataset is useful for statistical analysis of domain data or feature extraction for training machine learning-based classifiers, e.g. for phishing detection. The data was collected between March and July 2023.The final assessment of the data was conducted in July 2023 (this is why the names are suffixed with _2307).

The upload contains: a) data files, b) the description of the data structure, and c) the veature vector we used for ML-based phishing domain detection.

Data Files

The data is located in two individual files:

• benign_2307.json - data about 432,572 benign domains, and
• phishing_2307.json - data about 36,993 phishing domains.

Data Structure

Both files are in the JSON Array format. The structure is as follows:

[
{
  "_id" : "A unique ID of the data record",
  "domain_name" : "Name of the domain (e.g., zenodo.com)",
  "dns" : { "//": "Data obtained from DNS records" },
  "evaluated_on" : "// ISO Timestamp of data collection ",
  "ip_data" : [  "// Data for each related IP adddress ",
    {
      "//": "IP-related data, including RTT from ICMP echo attempts (from Brno, Czechia)",
      "//": "WHOIS/RDAP data for the given IP address",
      "//": "GeoIP data for the given IP address",
      "//": "NERD system reputation score (if available)",
      "//": "ASN info",
      "//": "remarks: ISO timestamps of collection of the individual data pieces"
    },
  ],
  "label" : "benign_2307 for benign OR misp_2307 for phishing",
  "rdap" : { "//": "WHOIS/RDAP information for the domain name" },
  "remarks" : {
    "dns_evaluated_on" : "ISO Timestamp of DNS data collection",
    "rdap_evaluated_on" : "ISO Timestamp of WHOIS/RDAP data collection",
    "tls_evaluated_on" : "ISO Timestamp of TLS certificate information collection",
    "dns_had_no_ips" : "true if no IPs were found in DNS records"
  },
  "sourced_on" : "ISO Timestamp of the moment the domain was found",
  "tls" : {
    "cipher" : "Identifier of the TLS cipher suite",
    "count" : "Number of certificates in chain",
    "protocol" : "Version of the TLS protocol",
    "certificates" : [
      "//": "Information from TLS certificate fields: issuer, extensions, etc."
    ]
  },
  "category" : "Category of the record (could be ignored)",
  "source" : "Name of the file that we used to save the domain list"
}
]

Feature Vector

This section describes the veature vector used in the "Unmasking the Phishermen: Phishing Domain Detection with Machine Learning and Multi-Source Intelligence" paper that was accepted to the IEEE NOMS 2024 conference.

Lexical Features

The following features were extracted from the sole domain name:

• lex_name_len - length of the domain name,
• lex_begins_with_digit - true if the domain name begins with a digit,
• lex_www_flag - true if the domain name begins with "www.",
• lex_phishing_keyword_count - occurence count of 47 phishing-related keywords,
• lex_consecutive_chars - length of the longest consecutive character sequence,
• lex_tld_len - length of the top-level domain (TLD),
• lex_tld_hash - hash of the TLD,
• lex_sld_len - length of the second-level domain (SLD),
• lex_sld_norm_entropy - normalized entropy of the SLD,
• lex_stld_unique_char_count - number of unique characters in the TLD and the SLD,
• lex_sub_count - number of subdomains,
• lex_sub_digit_ratio - ratio of digits in subdomains,
• lex_sub_hex_ratio - ratio of hex symbols in subdomains,
• lex_sub_non_alpanum_ratio - ratio of non-alphanumeric symbols in subdomains,
• lex_sub_vowel_ratio - ratio of vowels in subdomains,
• lex_sub_consonant_ratio - ratio of consonants in subdomains,
• lex_sub_max_consonant_len - length of the longest consonant sequence in subdomains,
• lex_sub_norm_entropy - normalized entropy of a string made from all subdomains,
• lex_phishing_bigram_matches - occurrence count of the top 300 phishing domain bigrams,
• lex_phishing_trigram_matches - occurrence count of the top 2000 phishing domain trigrams,
• lex_phishing_tetragram_matches - occurrence count of the top 5000 phishing domain tetragrams,
• lex_phishing_pentagram_matches - occurrence count of the top 10000 phishing domain pentagrams.

DNS-based Features

The following features were extracted from DNS responses when querying about the domain:

• dns_A_count - number of A records for the domain,
• dns_AAAA_count - number of AAAA records for the domain,
• dns_CNAME_count - number of CNAME records for the domain,
• dns_MX_count - number of MX records for the domain,
• dns_NS_count - number of nameserver (NS) records for the domain,
• dns_TXT_count - number of TXT records for the domain,
• dns_soa_primary_ns_len - number of characters in the primary NS's domain name,
• dns_soa_primary_ns_level - number of subdomain in the primary NS's domain name,
• dns_soa_primary_ns_digit_count - number of digits in the primary NS's domain name,
• dns_soa_primary_ns_entropy - normalized entropy of the primary NS's domain name,
• dns_soa_email_len - number of characters in the admin's email domain name part,
• dns_soa_email_level - number of subdomains in the admin's email domain name part,
• dns_soa_email_digit_count - number of digits in the admin's email domain name part,
• dns_soa_email_entropy - normalized entropy of the admin's email domain name part,
• dns_soa_refresh - SOA refresh parameter,
• dns_soa_retry - SOA retry parameter,
• dns_soa_expire - SOA expire parameter,
• dns_mx_avg_len - average number of characters of the domain names in MX records,
• dns_mx_avg_entropy - average normalized entropy of the domain names in MX records,
• dns_domain_name_in_mx - true if the domain name is contained in the MX record's domains,
• dns_txt_spf_exists - true if an SPF record is in the TXT RRs,
• dns_txt_avg_entropy - average normalized entropy of the TXT records
• dns_ttl_low - number of RRsets with TTL in [0,100],
• dns_ttl_mid - number of RRsets with TTL in [101,500],
• dns_zone_entropy - normalized entropy of the zone's domain name.

IP-based Features

These features were derived from IP addresses and ICMP echo replies:

• ip_mean_average_rtt - average RTT of all ICMP echo attempts,
• ip_entropy - total entropy of all /16 (/64 for v6) IP prefixes,
• ip_count - total number of IP addresses for the domain,
• ip_v4_count - total number of IPv4 addresses for the domain,
• ip_v6_count - total number of IPv6 addresses for the domain,

TLS-based Features

The following features were extracted from TLS certificate chains and TLS handshakes:

• tls_chain_len - length of the TLS certificate chain,
• tls_broken_chain - true if there is a certificate that has never been valid,
• tls_expired_chain - true if there is an expired certificate in the chain,
• tls_total_extension_count - total extensions in all certificates in the chain,
• tls_critical_extensions - total extensions flagged as "critical" in all certificates,
• tls_with_policies_crt_count - number of certificates that include the "policies" extension,
• tls_percentage_crt_with_policies - percentage of certificates that include the "policies" extension,
• tls_x509_anypolicy_crt_count - number of certificates not enforcing any security policy,
• tls_iso_policy_crt_count - total discovered policies from the 1.* OID space,
• tls_joint_isoitu_policy_crt_count - total discovered policies from from the 2.* OID space,
• tls_subject_count - number of subject alternative names (SANs) in the leaf certificate,
• tls_server_auth_crt_count - number of certificates with the "Web Server Authentication",
• tls_client_auth_crt_count - number of certificates with the "Web Client Authentication",
• tls_CA_certs_in_chain_ratio - ratio of CA certificates in the chain,
• tls_unique_SLD_count -number of unique second-level domains

Get an organized archive of WHOIS data by countries, covering 261+ nations and territories.

The statistic shows the trend in the global number of internet hosts in the domain name system from 1993 to 2019. In January 2019, approximately 1.01 billion internet hosts were available on the DNS.

Hilco Streambank is a trusted marketplace leader dedicated to reliable and transparent service. As the world's largest IPv4 address broker, Hilco Streambank has successfully completed more transfers than any other organization, worldwide, with over $0 billion generated for clients since 2014. The company's team has extensive experience in region internet registry transfer regulations and provides buyers and sellers with expert advice to help reach a deal that meets even the most complex of needs.

Hilco Streambank's online marketplace provides a streamlined and transparent process to transfer the rights to IPv4 assets, including buyer and seller checklists, private brokered solutions, and LEASE IPv4 options. The company also offers the IPv4 Analyzer widget and its ReView digital IP address audit tool, a free tool working with 6connect. With operating presence in all five internet registries, including ARIN, APNIC, RIPE, LACNIC, and AFRINIC, Hilco Streambank is well-positioned to facilitate IPv4 transactions worldwide.

About this Dataset

For sale are domain names with WHO IS information that were registered between Mar 16, 2018 and Mar 31, 2018 by registrants in United States. Domains which obfuscate registrant, administrative, and other WHO IS contact details have been omitted from this dataset. The following information is availble for download in this dataset: - Domain name, Created Date, Updated Date, Expiration Date, Registrar Name- Registrant Company, Name, Address, City, State/Province/Other, Postal Code, Country, Email, Phone #, Fax #- Administrative Company, Name, Address, City, State/Province/Other, Postal Code, Country, Email, Phone #, Fax #- Technical Company, Name, Address, City, State/Province/Other, Postal Code, Country, Email, Phone #, Fax #- Billing Company, Name, Address, City, State/Province/Other, Postal Code, Country, Email, Phone #, Fax #- NameServer1, NameServer2, NameServer3, NameServer4, - DomainStatus1, DomainStatus2, DomainStatus3, DomainStatus4 Still unsure about purchasing this dataset? View and Download a free sample dataset of global domain name registrations in the Lead Generation category Are you interested in a more targeted domain name registration dataset? Select the "Ask Seller a Question" link, send me a message, and I'll get back to you as soon as I can.

Category

Lead Generation

Keywords

usa,united-states,newly-registered-domains,who-is-data

Row Count

220910

Price

$20.00

This dataset results from 13 data description sessions conducted at U. Porto. In each session researchers have created metadata in the Dendro, research data management platform. A project for each session was created beforehand in Dendro and all the sessions were kept under the same account. All projects were kept private. This was explained to the researchers and they could have changed any information if they wanted to. When scheduling the sessions researchers were asked to choose a dataset to describe. The sessions started by introducing researchers to Dendro with a brief demonstration of its features. The researchers were then asked to create a folder and upload their datasets. During the session the selection of descriptors was mostly up to them. Exceptionally, they were asked if a given descriptor was suitable to contextualize their data. Sessions audio was recorded with the researchers’ consent and were deleted after the transcription of relevant events and comments during each session to complement the analysis of the metadata produced. The audio was also used to mark the moment the researchers started and finished the description, in order to ascertain the session duration.

PredictLeads Key Customers Data provides essential business intelligence by analyzing company relationships, uncovering vendor partnerships, client connections, and strategic affiliations through advanced web scraping and logo recognition. This dataset captures business interactions directly from company websites, offering valuable insights into market positioning, competitive landscapes, and growth opportunities.

Use Cases:

✅ Account Profiling – Gain a 360-degree customer view by mapping company relationships and partnerships. ✅ Competitive Intelligence – Track vendor-client connections and business affiliations to identify key industry players. ✅ B2B Lead Targeting – Prioritize leads based on their business relationships, improving sales and marketing efficiency. ✅ CRM Data Enrichment – Enhance company records with detailed key customer data, ensuring data accuracy. ✅ Market Research – Identify emerging trends and industry networks to optimize strategic planning.

Key API Attributes:

• id (string, UUID) – Unique identifier for the company connection.
• category (string) – Type of relationship (e.g., vendor, client, partner).
• source_category (string) – Where the connection was detected (e.g., partner page, case study).
• source_url (string, URL) – Website where the relationship was found.
• individual_source_url (string, URL) – Specific page confirming the connection.
• context (string) – Extracted description of the business relationship (e.g., "Company X - partners with Company Y to enhance payment processing").
• first_seen_at (ISO 8601 date-time) – Date the connection was first detected.
• last_seen_at (ISO 8601 date-time) – Most recent confirmation of the relationship.
• company1 & company2 (objects) – Details of the two connected companies, including:
• - domain (string) – Company website domain.
• - company_name (string) – Official company name.
• - ticker (string, nullable) – Stock ticker, if available.

📌 PredictLeads Key Customers Data is an indispensable tool for B2B sales, marketing, and market intelligence teams, providing actionable relationship insights to drive targeted outreach, competitor tracking, and strategic decision-making.

PredictLeads Docs: https://docs.predictleads.com/v3/guide/connections_dataset

About this Dataset

For sale are domain names that were registered between Feb 24, 2018 and Feb 28, 2018 by registrants in United States. Domains which obfuscate registrant, administrative, and other WHO IS contact details have been omitted from this dataset. The following information is availble for download in this dataset: - Domain name, Created Date, Updated Date, Expiration Date, Registrar Name- Registrant Company, Name, Address, City, State/Province/Other, Postal Code, Country, Email, Phone #, Fax #- Administrative Company, Name, Address, City, State/Province/Other, Postal Code, Country, Email, Phone #, Fax #- Technical Company, Name, Address, City, State/Province/Other, Postal Code, Country, Email, Phone #, Fax #- Billing Company, Name, Address, City, State/Province/Other, Postal Code, Country, Email, Phone #, Fax #- NameServer1, NameServer2, NameServer3, NameServer4, - DomainStatus1, DomainStatus2, DomainStatus3, DomainStatus4 Still unsure about purchasing this dataset? View and Download a free sample dataset of global domain name registrations - https://www.dataandsons.com/categories/lead_generation/domain-names-registered-between-feb-12-2018-to-feb-18-2018. Are you interested in a more targeted domain name registration dataset? Select the "Ask Seller a Question" link, send me a message, and I'll get back to you as soon as I can.

Category

Lead Generation

Keywords

USA,United-States,newly-registered-domain-names,recently-registered-domain-names,who-is-data

Row Count

84127

Price

$10.00

Korea Number of .kr Domains data was reported at 1,047,432.000 Unit in Jun 2018. This records a decrease from the previous number of 1,047,761.000 Unit for May 2018. Korea Number of .kr Domains data is updated monthly, averaging 625,439.000 Unit from Apr 1993 (Median) to Jun 2018, with 303 observations. The data reached an all-time high of 1,324,075.000 Unit in Jun 2012 and a record low of 24.000 Unit in Apr 1993. Korea Number of .kr Domains data remains active status in CEIC and is reported by Korea Internet & Security Agency. The data is categorized under Global Database’s Korea – Table KR.TB002: Internet Statistics.

As of 2023, the strategy domain is the one with the largest number of companies claiming to be either a pacesetter or a chaser in terms of artificial intelligence (AI) readiness. The data domain held the largest number of laggards in the technology.

This dataset consists in data from 13 multi-domain data description sessions follow-up questionnaires. Researchers from the University of Porto participated in a data description session and filled in a follow-up questionnaire to assess their interest in research data management, the usefulness of data description, among others. The questionnaire was conducted on Google Forms and the data copied to a spreadsheet, because the questionnaires were made individually taking into account the specificity of one of the questions.

WP-Script is a company that provides WordPress themes and plugins for creating adult sites. They offer a range of products, including seven customizable adult WordPress themes and thirteen powerful adult WordPress plugins. Their products are designed to be easy to use and can help entrepreneurs create professional-looking adult sites with minimal technical expertise.

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Korea Number of .kr Domains: .co data was reported at 651,627.000 Unit in Jun 2018. This records a decrease from the previous number of 652,819.000 Unit for May 2018. Korea Number of .kr Domains: .co data is updated monthly, averaging 537,922.500 Unit from Jan 1997 (Median) to Jun 2018, with 258 observations. The data reached an all-time high of 653,298.000 Unit in Jan 2018 and a record low of 2,245.000 Unit in Jan 1997. Korea Number of .kr Domains: .co data remains active status in CEIC and is reported by Korea Internet & Security Agency. The data is categorized under Global Database’s Korea – Table KR.TB002: Internet Statistics.