According to Cognitive Market Research, The Global Anti crawling Techniques market size is USD XX million in 2023 and will expand at a compound annual growth rate (CAGR) of 6.00% from 2023 to 2030.

North America Anti crawling Techniques held the major market of more than 40% of the global revenue and will grow at a compound annual growth rate (CAGR) of 4.2% from 2023 to 2030.
Europe Anti crawling Techniques accounted for a share of over 30% of the global market and are projected to expand at a compound annual growth rate (CAGR) of 4.5% from 2023 to 2030.
Asia Pacific Anti crawling Techniques held the market of more than 23% of the global revenue and will grow at a compound annual growth rate (CAGR) of 8.0% from 2023 to 2030.
South American Anti crawling Techniques market of more than 5% of the global revenue and will grow at a compound annual growth rate (CAGR) of 5.4% from 2023 to 2030.
Middle East and Africa Anti crawling Techniques held the major market of more than 2% of the global revenue and will grow at a compound annual growth rate (CAGR) of 5.7% from 2023 to 2030.
The market for anti-crawling techniques has grown dramatically as a result of the increasing number of data breaches and public awareness of the need to protect sensitive data. 
Demand for bot fingerprint databases remains higher in the anti crawling techniques market.
The content protection category held the highest anti crawling techniques market revenue share in 2023.

Increasing Demand for Protection and Security of Online Data to Provide Viable Market Output

The market for anti-crawling techniques is expanding due in large part to the growing requirement for online data security and protection. Due to an increase in digital activity, organizations are processing and storing enormous volumes of sensitive data online. Organizations are being forced to invest in strong anti-crawling techniques due to the growing threat of data breaches, illegal access, and web scraping occurrences. By protecting online data from harmful activity and guaranteeing its confidentiality and integrity, these technologies advance the industry. Moreover, the significance of protecting digital assets is increased by the widespread use of the Internet for e-commerce, financial transactions, and sensitive data transfers. Anti-crawling techniques are essential for reducing the hazards connected to online scraping, which is a tactic often used by hackers to obtain important data.

Increasing Incidence of Cyber Threats to Propel Market Growth

The growing prevalence of cyber risks, such as site scraping and data harvesting, is driving growth in the market for anti-crawling techniques. Organizations that rely significantly on digital platforms run a higher risk of having illicit data extracted. In order to safeguard sensitive data and preserve the integrity of digital assets, organizations have been forced to invest in sophisticated anti-crawling techniques that strengthen online defenses. Moreover, the market's growth is a reflection of growing awareness of cybersecurity issues and the need to put effective defenses in place against changing cyber threats. Moreover, cybersecurity is constantly challenged by the spread of advanced and automated crawling programs. The ever-changing threat landscape forces enterprises to implement anti-crawling techniques, which use a variety of tools like rate limitation, IP blocking, and CAPTCHAs to prevent fraudulent scraping efforts.

Market Restraints of the Anti crawling Techniques

Increasing Demand for Ethical Web Scraping to Restrict Market Growth

The growing desire for ethical web scraping presents a unique challenge to the anti-crawling techniques market. Ethical web scraping is the process of obtaining data from websites for lawful objectives, such as market research or data analysis, but without breaching the terms of service. Furthermore, the restraint arises because anti-crawling techniques must distinguish between criminal and ethical scraping operations, finding a balance between preventing websites from misuse and permitting authorized data harvest. This dynamic calls for more complex and adaptable anti-crawling techniques to distinguish between destructive and ethical scrapping actions.

Impact of COVID-19 on the Anti Crawling Techniques Market

The demand for online material has increased as a result of the COVID-19 pandemic, which has...

The global web crawler tool market is experiencing robust growth, driven by the increasing need for data extraction and analysis across diverse sectors. The market's expansion is fueled by the exponential growth of online data, the rise of big data analytics, and the increasing adoption of automation in business processes. Businesses leverage web crawlers for market research, competitive intelligence, price monitoring, and lead generation, leading to heightened demand. While cloud-based solutions dominate due to scalability and cost-effectiveness, on-premises deployments remain relevant for organizations prioritizing data security and control. The large enterprise segment currently leads in adoption, but SMEs are increasingly recognizing the value proposition of web crawling tools for improving business decisions and operations. Competition is intense, with established players like UiPath and Scrapy alongside a growing number of specialized solutions. Factors such as data privacy regulations and the complexity of managing web crawlers pose challenges to market growth, but ongoing innovation in areas such as AI-powered crawling and enhanced data processing capabilities are expected to mitigate these restraints. We estimate the market size in 2025 to be $1.5 billion, growing at a CAGR of 15% over the forecast period (2025-2033). The geographical distribution of the market reflects the global nature of internet usage, with North America and Europe currently holding the largest market share. However, the Asia-Pacific region is anticipated to witness significant growth driven by increasing internet penetration and digital transformation initiatives across countries like China and India. The ongoing development of more sophisticated and user-friendly web crawling tools, coupled with decreasing implementation costs, is projected to further stimulate market expansion. Future growth will depend heavily on the ability of vendors to adapt to evolving web technologies, address increasing data privacy concerns, and provide robust solutions that cater to the specific needs of various industry verticals. Further research and development into AI-driven crawling techniques will be pivotal in optimizing efficiency and accuracy, which in turn will encourage wider adoption.

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Repository: [More… See the full description on the dataset page: https://huggingface.co/datasets/mendoanjoe/crawl-data.

The Common Crawl corpus contains petabytes of data collected over 8 years of web crawling. The corpus contains raw web page data, metadata extracts and text extracts. Common Crawl data is stored on Amazon Web Services’ Public Data Sets and on multiple academic cloud platforms across the world.

The Turkish web corpus MaCoCu-tr 1.0 was built by crawling the ".tr" internet top-level domain in 2021, extending the crawl dynamically to other domains as well (https://github.com/macocu/MaCoCu-crawler).

Considerable efforts were devoted into cleaning the extracted text to provide a high-quality web corpus. This was achieved by removing boilerplate (https://corpus.tools/wiki/Justext) and near-duplicated paragraphs (https://corpus.tools/wiki/Onion), discarding very short texts as well as texts that are not in the target language. The dataset is characterized by extensive metadata which allows filtering the dataset based on text quality and other criteria (https://github.com/bitextor/monotextor), making the corpus highly useful for corpus linguistics studies, as well as for training language models and other language technologies.

Each document is accompanied by the following metadata: title, crawl date, url, domain, file type of the original document, distribution of languages inside the document, and a fluency score (based on a language model). The text of each document is divided into paragraphs that are accompanied by metadata on the information whether a paragraph is a heading or not, metadata on the paragraph quality and fluency, the automatically identified language of the text in the paragraph, and information whether the paragraph contains personal information.

This action has received funding from the European Union's Connecting Europe Facility 2014-2020 - CEF Telecom, under Grant Agreement No. INEA/CEF/ICT/A2020/2278341. This communication reflects only the author’s view. The Agency is not responsible for any use that may be made of the information it contains.

This project develop components of a polar cyberinfrastructure (CI) to support researchers and users for data discovery and access. The main goal is to provide tools that will enable a better access to polar data and information, hence allowing to spend more time on analysis and research, and significantly less time on discovery and searching. A large-scale web crawler, PolarHub, is developed to continuously mine the Internet to discover dispersed polar data. Beside identifying polar data in major data repositories, PolarHub is also able to bring individual hidden resources forward, hence increasing the discoverability of polar data. Quality and assessment of data resources are analyzed inside of PolarHub, providing a key tool for not only identifying issues but also to connect the research community with optimal data resources.

In the current PolarHub system, seven different types of geospatial data and processing services that are compliant with OGC (Open Geospatial Consortium) are supported in the system. They are: -- OGC Web Map Service (WMS): is a standard protocol for serving (over the Internet)georeferenced map images which a map server generates using data from a GIS database. -- OGC Web Feature Service (WFS): provides an interface allowing requests for geographical features across the web using platform-independent calls. -- OGC Web Coverage Service (WCS): Interface Standard defines Web-based retrieval of coverages; that is, digital geospatial information representing space/time-varying phenomena. -- OGC Web Map Tile Service (WMTS): is a standard protocol for serving pre-rendered georeferenced map tiles over the Internet. -- OGC Sensor Observation Service (SOS): is a web service to query real-time sensor data and sensor data time series and is part of theSensor Web. The offered sensor data comprises descriptions of sensors themselves, which are encoded in the Sensor Model Language (SensorML), and the measured values in the Observations and Measurements (O and M) encoding format. -- OGC Web Processing Service (WPS): Interface Standard provides rules for standardizing how inputs and outputs (requests and responses) for invoking geospatial processing services, such as polygon overlay, as a web service. -- OGC Catalog Service for the Web (CSW): is a standard for exposing a catalogue of geospatial records in XML on the Internet (over HTTP). The catalogue is made up of records that describe geospatial data (e.g. KML), geospatial services (e.g. WMS), and related resources.

PolarHub has three main functions: (1) visualization and metadata viewing of geospatial data services; (2) user-guided real-time data crawling; and (3) data filtering and search from PolarHub data repository.

Host-level Web Graph - This graph aggregates the page graph by subdomain/host where each node represents a specific subdomain/host and an edge exists between a pair of hosts/subdomains if at least one link was found between pages that belong to a pair of subdomains/hosts. The hyperlink graph was extracted from the Web corpus released by the Common Crawl Foundation in August 2012. The Web corpus was gathered using a web crawler employing a breadth-first-search selection strategy and embedding link discovery while crawling. The crawl was seeded with a large number of URLs from former crawls performed by the Common Crawl Foundation. Also, see web-cc12-firstlevel-subdomain and web-cc12-PayLevelDomain.

North America Anti crawling Techniques held the major market of more than 40% of the global revenue with a market size of USD XX million in 2023 and will grow at a compound annual growth rate (CAGR) of 4.2% from 2023 to 2030.

Context

Common Crawl project has fascinated me ever since I learned about it. It provides a large number of data formats and presents challenges across skill and interest areas. I am particularly interested in URL analysis for applications such as typosquatting, malicious URLs, and just about anything interesting that can be done with domain names.

Content

I have sampled 1% of the domains from the Common Crawl Index dataset that is available on AWS in Parquet format. You can read more about how I extracted this dataset @ https://harshsinghal.dev/create-a-url-dataset-for-nlp/

Acknowledgements

Thanks a ton to the folks at https://commoncrawl.org/ for making this immensely valuable resource available to the world for free. Please find their Terms of Use here.

Inspiration

My interests are in working with string similarity functions and I continue to find scalable ways of doing this. I wrote about using a Postgres extension to compute string distances and used Common Crawl URL domains as the input dataset (you can read more @ https://harshsinghal.dev/postgres-text-similarity-with-commoncrawl-domains/).

I am also interested in identifying fraudulent domains and understanding malicious URL patterns.

Market Overview and Growth Drivers: The global live crawling service market is projected to witness significant growth over the forecast period from 2025 to 2033. In 2025, the market is estimated to be valued at XXX million, and it is expected to expand at a CAGR of XX% during the forecast period. The primary drivers behind this growth include the increasing demand for data analytics, the growing adoption of data scraping tools, and the emergence of advanced crawling technologies. Moreover, the rising trend of e-commerce and the need for real-time data for business intelligence and competitive analysis are contributing to the market expansion. Market Segmentation and Regional Analysis: The live crawling service market is segmented based on application, type, and region. By application, the market is classified into SMEs and large enterprises. By type, the market is divided into web data crawling, PDF data crawling, and others. Geographically, the market is divided into North America, South America, Europe, the Middle East & Africa, and Asia Pacific. North America is expected to hold a dominant share in the market due to the presence of key players such as X-Byte Enterprise Crawling and Actowiz Solutions, as well as the high adoption of data analytics and data scraping tools in the region. Asia Pacific is anticipated to witness the fastest growth rate during the forecast period, attributed to the rapid growth of the e-commerce sector and the increasing demand for data for market research and competitive analysis.

Anti-Crawling Techniques Market Analysis The global anti-crawling techniques market is anticipated to reach a valuation of USD 231 million by 2033, expanding at a CAGR of 10.3% from 2025 to 2033. This growth is driven by the increasing prevalence of malicious web crawling activities, such as web scraping, that can harm businesses by extracting sensitive data, abusing resources, or manipulating online prices. The market is segmented into applications such as content protection, price protection, and advertisement protection, and types including bot fingerprint databases, JavaScript tags, and cloud APIs. Key trends in the anti-crawling techniques market include the emergence of advanced technologies like intent-based deep behavior analysis (IDBA) and the growing emphasis on preventing sophisticated bot attacks. The market is dominated by established players such as Ziwit Enterprise, Radware, Imperva, and Paloalto, while regional markets in North America, Europe, Asia Pacific, and the Middle East & Africa present significant growth opportunities. The rising adoption of e-commerce and the increasing value of online data are expected to fuel further demand for anti-crawling solutions in the years to come.

An automatic pipeline based on an algorithm that identifies new resources in publications every month to assist the efficiency of NIF curators. The pipeline is also able to find the last time the resource's webpage was updated and whether the URL is still valid. This can assist the curator in knowing which resources need attention. Additionally, the pipeline identifies publications that reference existing NIF Registry resources as this is also of interest. These mentions are available through the Data Federation version of the NIF Registry, http://neuinfo.org/nif/nifgwt.html?query=nlx_144509 The RDF is based on an algorithm on how related it is to neuroscience. (hits of neuroscience related terms). Each potential resource gets assigned a score (based on how related it is to neuroscience) and the resources are then ranked and a list is generated.

RealNews is a large corpus of news articles from Common Crawl. Data is scraped from Common Crawl, limited to the 5000 news domains indexed by Google News. The authors used the Newspaper Python library to extract the body and metadata from each article. News from Common Crawl dumps from December 2016 through March 2019 were used as training data; articles published in April 2019 from the April 2019 dump were used for evaluation. After deduplication, RealNews is 120 gigabytes without compression.

In the recent years, Transformer-based models have lead to significant advances in language modelling for natural language processing. However, they require a vast amount of data to be (pre-)trained and there is a lack of corpora in languages other than English. Recently, several initiatives have presented multilingual datasets obtained from automatic web crawling. However, the results in Spanish present important shortcomings, as they are either too small in comparison with other languages, or present a low quality derived from sub-optimal cleaning and deduplication. In this paper, we introduce esCorpius, a Spanish crawling corpus obtained from near 1 Pb of Common Crawl data. It is the most extensive corpus in Spanish with this level of quality in the extraction, purification and deduplication of web textual content. Our data curation process involves a novel highly parallel cleaning pipeline and encompasses a series of deduplication mechanisms that together ensure the integrity of both document and paragraph boundaries. Additionally, we maintain both the source web page URL and the WARC shard origin URL in order to complain with EU regulations. esCorpius has been released under CC BY-NC-ND 4.0 license.

Europe Anti crawling Techniques accounted for a share of over 30% of the global market size of USD XX million in 2023 and projected to expand at a compound annual growth rate (CAGR) of 4.5% from 2023 to 2030

Microformat, Microdata and RDFa data from the October 2016 Common Crawl web corpus. We found structured data within 1.24 billion HTML pages out of the 3.2 billion pages contained in the crawl (38%). These pages originate from 5.63 million different pay-level-domains out of the 34 million pay-level-domains covered by the crawl (16.5%). Altogether, the extracted data sets consist of 44.2 billion RDF quads.

This dataset is the result of a full-population crawl of the .gov.uk web domain, aiming to capture a full picture of the scope of public-facing government activity online and the links between different government bodies. Local governments have been developing online services, aiming to better serve the public and reduce administrative costs. However, the impact of this work, and the links between governments’ online and offline activities, remain uncertain. The overall research question for this research examines whether local e-government has met these expectations, of Digital Era Governance and of its practitioners. Aim was to directly analyse the structure and content of government online. It shows that recent digital-centric public administration theories, typified by the Digital Era Governance quasi-paradigm, are not empirically supported by the UK local government experience. The data consist of a file of individual Uniform Resource Locators (URLs) fetched during the crawl, and a further file containing pairs of URLs reflecting the Hypertext Markup Language (HTML) links between them. In addition, a GraphML format file is presented for a version of the data reduced to third-level-domains, with accompanying attribute data for the publishing government organisations and calculated webometric statistics based on the third-level-domain link network.This project engages with the Digital Era Governance (DEG) work of Dunleavy et. al. and draws upon new empirical methods to explore local government and its use of Internet-related technology. It challenges the existing literature, arguing that e-government benefits have been oversold, particularly for transactional services; it updates DEG with insights from local government. The distinctive methodological approach is to use full-population datasets and large-scale web data to provide an empirical foundation for theoretical development, and to test existing theorists’ claims. A new full-population web crawl of .gov.uk is used to analyse the shape and structure of online government using webometrics. Tools from computer science, such as automated classification, are used to enrich our understanding of the dataset. A new full-population panel dataset is constructed covering council performance, cost, web quality, and satisfaction. The local government web shows a wide scope of provision but only limited evidence in support of the existing rhetorics of Internet-enabled service delivery. In addition, no evidence is found of a link between web development and performance, cost, or satisfaction. DEG is challenged and developed in light of these findings. The project adds value by developing new methods for the use of big data in public administration, by empirically challenging long-held assumptions on the value of the web for government, and by building a foundation of knowledge about local government online to be built on by further research. This is an ESRC-funded DPhil research project. A web crawl was carried out with Heritrix, the Internet Archive's web crawler. A list of all registered domains in .gov.uk (and their www.x.gov.uk equivalents) was used as a set of start seeds. Sites outside .gov.uk were excluded; robots.txt files were respected, with the consequence that some .gov.uk sites (and some parts of other .gov.uk sites) were not fetched. Certain other areas were manually excluded, particularly crawling traps (e.g. calendars which will serve infinite numbers of pages in the past and future and those websites returning different URLs for each browser session) and the contents of certain large peripheral databases such as online local authority library catalogues. A full set of regular expressions used to filter the URLs fetched are included in the archive. On completion of the crawl, the page URLs and link data were extracted from the output WARC files. The page URLs were manually examined and re-filtered to handle various broken web servers and to reduce duplication of content where multiple views were presented onto the same content (for example, where a site was presented at both http://organisation.gov.uk/ and http://www.organisation.gov.uk/ without HTTP redirection between the two). Finally, The link list was filtered against the URL list to remove bogus links and both lists were map/reduced to a single set of files. Also included in this data release is a derived dataset more useful for high-level work. This is a GraphML file containing all the link and page information reduced to third-level domain level (so darlington.gov.uk is considered as a single node, not a large set of pages) and with the links binarised to present/not present between each node. Each graph node also has various attributes, including the name of the registering organisation and various webometric measures including PageRank, indegree and betweenness centrality.

Originally designed to carry the towering Saturn V moon rocket from the Vehicle Assembly Building to the seaside launch site, the enormous transporters now carry the space shuttles to the launch pads for liftoff. Polygons: 146050 Vertices: 141658

The Legal Georgian Crawling is a 3-million-token corpus of Georgian built from the web by targeting specific in-domain urls that belong to the legal sector such as legislation websites, governamental sites, and domains from the Court and the Parliament. It consists of 3,688,666 tokens, 189,506 sentences and 13,766 documents. Documents are separated by single new lines. The corpus has been developed in the framework of the CEF project MT4ALL (http://ixa2.si.ehu.eus/mt4all/project) We license the actual packaging of this data under a CC0 1.0 Universal License.

This object has been created as a part of the web harvesting project of the Eötvös Loránd University Department of Digital Humanities ELTE DH. Learn more about the workflow HERE about the software used HERE.The aim of the project is to make online news articles and their metadata suitable for research purposes. The archiving workflow is designed to prevent modification or manipulation of the downloaded content. The current version of the curated content with normalized formatting in standard TEI XML format with Schema.org encoded metadata is available HERE. The detailed description of the raw content is the following:

• The portal's archived content (from 2000-09-10 to 2021-10-16) in WARC format available HERE (crawled: 2021-09-02T19:51:04.673039 - 2021-10-16T16:25:30.654675).