Internet use in the UK annual estimates by age, sex, disability, ethnic group, economic activity and geographical location, including confidence intervals.

The U.S.-based telecommunications company Verizon has registered a significant increase in the usage of data on its networks in the United States on March 19 compared to March 12 due to restrictions in place triggered by the coronavirus (COVID-19) pandemic. VPN traffic for example was up by 25 percent during this small sample time period.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Fact and Figures page.

In 2024, 94 percent of young people aged 16 to 24 years in Finland had used a social networking site in the past three months and 81 percent had used social networks daily. However, only a quarter of the population aged 75 to 89 years had used social networking sites in the past three months.

The average daily in-home data usage in the United States has increased significantly during the coronavirus (COVID-19) outbreak in March 2020. Compared to the same time in March 2019 the daily average in-home data usage has increased by 38 percent to 16.6 gigabytes, up from 12 gigabytes in March 2019. The increase can be observed across almost all device categories with the data usage of gaming consoles and smartphones increasing the most.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Fact and Figures page.

The dataset is a set of network traffic traces in pcap/csv format captured from a single user. The traffic is classified in 5 different activities (Video, Bulk, Idle, Web, and Interactive) and the label is shown in the filename. There is also a file (mapping.csv) with the mapping of the host's IP address, the csv/pcap filename and the activity label.

Activities:

Interactive: applications that perform real-time interactions in order to provide a suitable user experience, such as editing a file in google docs and remote CLI's sessions by SSH. Bulk data transfer: applications that perform a transfer of large data volume files over the network. Some examples are SCP/FTP applications and direct downloads of large files from web servers like Mediafire, Dropbox or the university repository among others. Web browsing: contains all the generated traffic while searching and consuming different web pages. Examples of those pages are several blogs and new sites and the moodle of the university. Vídeo playback: contains traffic from applications that consume video in streaming or pseudo-streaming. The most known server used are Twitch and Youtube but the university online classroom has also been used. Idle behaviour: is composed by the background traffic generated by the user computer when the user is idle. This traffic has been captured with every application closed and with some opened pages like google docs, YouTube and several web pages, but always without user interaction.

The capture is performed in a network probe, attached to the router that forwards the user network traffic, using a SPAN port. The traffic is stored in pcap format with all the packet payload. In the csv file, every non TCP/UDP packet is filtered out, as well as every packet with no payload. The fields in the csv files are the following (one line per packet): Timestamp, protocol, payload size, IP address source and destination, UDP/TCP port source and destination. The fields are also included as a header in every csv file.

The amount of data is stated as follows:

Bulk : 19 traces, 3599 s of total duration, 8704 MBytes of pcap files Video : 23 traces, 4496 s, 1405 MBytes Web : 23 traces, 4203 s, 148 MBytes Interactive : 42 traces, 8934 s, 30.5 MBytes Idle : 52 traces, 6341 s, 0.69 MBytes

The code of our machine learning approach is also included. There is a README.txt file with the documentation of how to use the code.

Explore the percentage of individuals using the internet dataset, providing valuable insights into internet usage trends worldwide. Click to access the data now!

Internet, Usage

Afghanistan, Albania, Algeria, Andorra, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan, Bolivia, Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burundi, Côte d'Ivoire, Cabo Verde, Cambodia, Cameroon, Canada, Chad, Chile, China, Colombia, Comoros, Congo, Costa Rica, Croatia, Cuba, Cyprus, Denmark, Djibouti, Dominica, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Estonia, Eswatini, Ethiopia, Fiji, Finland, France, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Grenada, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hungary, Iceland, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kiribati, Kuwait, Kyrgyzstan, Latvia, Lebanon, Lesotho, Liberia, Libya, Liechtenstein, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Marshall Islands, Mauritania, Mauritius, Mexico, Micronesia, Moldova, Monaco, Mongolia, Montenegro, Morocco, Mozambique, Myanmar, Namibia, Nauru, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, North Macedonia, Norway, Oman, Pakistan, Palau, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Samoa, San Marino, Sao Tome and Principe, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovakia, Slovenia, Solomon Islands, Somalia, South Africa, South Sudan, Spain, Sri Lanka, Sudan, Suriname, Sweden, Switzerland, Syria, Tajikistan, Tanzania, Thailand, Timor-Leste, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkmenistan, Tuvalu, Uganda, Ukraine, United Arab Emirates, United Kingdom, Uruguay, Uzbekistan, Vanuatu, Venezuela, Yemen, Zambia, Zimbabwe, WorldFollow data.kapsarc.org for timely data to advance energy economics research..Please review the notes in the attachments.

Network Traffic Analysis Solutions Market Outlook

The global network traffic analysis solutions market size was estimated at USD 3.5 billion in 2023 and is projected to reach USD 9.8 billion by 2032, reflecting a compound annual growth rate (CAGR) of 12.1%. This substantial growth is largely driven by the increasing demand for robust cybersecurity measures across various sectors. With an ever-growing volume of network traffic due to the proliferation of connected devices and the adoption of digital transformation initiatives, organizations are compelled to deploy sophisticated traffic analysis tools to effectively monitor, manage, and secure their networks. The expansion of cloud services, coupled with the rise in cyber threats, further accentuates the need for advanced traffic analysis capabilities.

The surge in cyber threats, including sophisticated hacking techniques and ransomware attacks, has become a pivotal growth factor for the network traffic analysis solutions market. As organizations strive to protect sensitive data and ensure the integrity of their networks, there is a heightened demand for solutions that can provide real-time visibility and control over network traffic. This growing emphasis on cybersecurity is not limited to large enterprises but is increasingly becoming a priority for small and medium enterprises (SMEs) as well. Consequently, the increasing cyber threat landscape is stimulating the adoption of network traffic analysis solutions across different organizational sizes, driving market growth.

Moreover, the rise of Internet of Things (IoT) devices is significantly contributing to the increased need for network traffic analysis. IoT devices generate vast amounts of data that need to be managed effectively to prevent network congestion and potential security breaches. By leveraging traffic analysis solutions, organizations can optimize IoT device performance and ensure seamless data flow while maintaining robust security protocols. As the IoT ecosystem continues to expand, it is expected to further fuel the demand for network traffic analysis solutions, facilitating better management and security of network resources.

In addition to cybersecurity concerns and IoT proliferation, regulatory compliance is another critical growth driver for the network traffic analysis solutions market. Organizations across various industries, such as BFSI, healthcare, and government sectors, are under increasing pressure to comply with stringent data protection regulations. Network traffic analysis solutions help these organizations monitor compliance effectively by providing detailed insights into network activity and data flows. As regulations continue to evolve and become more complex, the role of network traffic analysis solutions in ensuring compliance and mitigating risks is expected to become increasingly important, further bolstering market growth.

Network Telemetry Solutions are becoming increasingly essential in the realm of network traffic analysis. These solutions provide real-time data collection and analysis, enabling organizations to gain deeper insights into their network operations. By leveraging network telemetry, businesses can proactively identify and address potential issues before they escalate into significant problems. This capability is particularly valuable in today's fast-paced digital environment, where network performance and security are critical to maintaining operational efficiency. As the demand for more granular visibility into network activities grows, network telemetry solutions are poised to play a pivotal role in enhancing the capabilities of traffic analysis tools, offering a more comprehensive approach to network management and security.

From a regional perspective, North America is anticipated to maintain a dominant position in the network traffic analysis solutions market. This can be attributed to the presence of major technology companies, a high adoption rate of advanced technologies, and stringent cybersecurity regulations. The region's established digital infrastructure and focus on innovation also contribute to market growth. Meanwhile, the Asia Pacific region is projected to witness the highest growth rate due to rapid digitalization, increasing internet penetration, and growing investments in IT infrastructure. As businesses in this region continue to adopt digital technologies and face rising cyber threats, the demand for network traffic analysis solutions is expected to surge significantly.

Component Analysis</h2

The above statistic gives information on the average duration of daily internet usage worldwide as of the first quarter of 2019, sorted by age group and device. During the survey period, it was found that the average duration of daily mobile internet usage among internet users aged 25 to 34 years amounted to 3 hours and 45 minutes.

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GapMinder collects data from a handful of sources, including the Institute for Health Metrics and Evaluation, the US Census Bureau’s International Database, the United Nations Statistics Division, and the World Bank.

Variable Name & Description of Indicator:

• country: Unique Identifier
• incomeperperson: Gross Domestic Product per capita in constant 2000 US$. The inflation but not the differences in the cost of living between countries has been taken into account.
• Internetuserate: Internet users (per 100 people) Internet users are people with access to the worldwide network.
• urbanrate: Urban population (% of total) Urban population refers to people living in urban areas as defined by national statistical offices (calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects)

More information is available at www.gapminder.org

Ecuador Internet Usage: Number of Companies: Other Internet Connection: Not in Use: Financial & Insurance Activities data was reported at 5.000 Unit in 2015. This records a decrease from the previous number of 45.000 Unit for 2014. Ecuador Internet Usage: Number of Companies: Other Internet Connection: Not in Use: Financial & Insurance Activities data is updated yearly, averaging 45.500 Unit from Dec 2012 (Median) to 2015, with 4 observations. The data reached an all-time high of 49.000 Unit in 2013 and a record low of 5.000 Unit in 2015. Ecuador Internet Usage: Number of Companies: Other Internet Connection: Not in Use: Financial & Insurance Activities data remains active status in CEIC and is reported by National Institute of Statistics and Census. The data is categorized under Global Database’s Ecuador – Table EC.TB005: Internet Usage: by Connection Type and by Economic Activity.

This dataset provides the monthly WiFi usage statistics since 2023 for all public libraries in East Baton Rouge Parish. The WiFi usage statistics are organized by branch, year, and month. Only connections made by patrons to the public-facing networks are included in these metrics, not staff connections made to the internal networks. WiFi use on the Outreach Bookmobiles is also not included in this count.

When asked about "Social network usage by frequency", 11 percent of Colombian respondents answer "Several times a week". This online survey was conducted in 2023, among 972 consumers.As an element of Statista Consumer Insights, our Consumer Insights Global survey offers you up-to-date market research data from over 50 countries and territories worldwide.

We recommend using the CESNET DataZoo python library, which facilitates the work with large network traffic datasets. More information about the DataZoo project can be found in the GitHub repository https://github.com/CESNET/cesnet-datazoo.

The modern approach for network traffic classification (TC), which is an important part of operating and securing networks, is to use machine learning (ML) models that are able to learn intricate relationships between traffic characteristics and communicating applications. A crucial prerequisite is having representative datasets. However, datasets collected from real production networks are not being published in sufficient numbers. Thus, this paper presents a novel dataset, CESNET-TLS-Year22, that captures the evolution of TLS traffic in an ISP network over a year. The dataset contains 180 web service labels and standard TC features, such as packet sequences. The unique year-long time span enables comprehensive evaluation of TC models and assessment of their robustness in the face of the ever-changing environment of production networks.

Data description The dataset consists of network flows describing encrypted TLS communications. Flows are extended with packet sequences, histograms, and fields extracted from the TLS ClientHello message, which is transmitted in the first packet of the TLS connection handshake. The most important extracted handshake field is the SNI domain, which is used for ground-truth labeling.

Packet Sequences Sequences of packet sizes, directions, and inter-packet times are standard data input for traffic analysis. For packet sizes, we consider the payload size after transport headers (TCP headers for the TLS case). We omit packets with no TCP payload, for example ACKs, because zero-payload packets are related to the transport layer internals rather than services’ behavior. Packet directions are encoded as ±1, where +1 means a packet sent from client to server, and -1 is a packet from server to client. Inter-packet times depend on the location of communicating hosts, their distance, and on the network conditions on the path. However, it is still possible to extract relevant information that correlates with user interactions and, for example, with the time required for an API/server/database to process the received data and generate a response. Packet sequences have a maximum length of 30, which is the default setting of the used flow exporter. We also derive three fields from each packet sequence: its length, time duration, and the number of roundtrips. The roundtrips are counted as the number of changes in the communication direction; in other words, each client request and server response pair counts as one roundtrip.

Flow statistics Each data record also includes standard flow statistics, representing aggregated information about the entire bidirectional connection. The fields are the number of transmitted bytes and packets in both directions, the duration of the flow, and packet histograms. The packet histograms include binned counts (not limited to the first 30 packets) of packet sizes and inter-packet times in both directions. There are eight bins with a logarithmic scale; the intervals are 0-15, 16-31, 32-63, 64-127, 128-255, 256-511, 512-1024, >1024 [ms or B]. The units are milliseconds for inter-packet times and bytes for packet sizes (More information in the PHISTS plugin documentation). Moreover, each flow has its end reason---either it ended with the TCP connection termination (FIN packets), was idle, reached the active timeout, or ended due to other reasons. This corresponds with the official IANA IPFIX-specified values. The FLOW_ENDREASON_OTHER field represents the forced end and lack of resources reasons.

Dataset structure The dataset is organized per weeks and individual days. The flows are delivered in compressed CSV files. CSV files contain one flow per row; data columns are summarized in the provided list below. For each flow data file, there is a JSON file with the total number of saved flows and the number of flows per service. There are also files aggregating flow counts for each week (stats-week.json) and for the entire dataset (stats-dataset.json). The following list describes flow data fields in CSV files:

• ID: Unique identifier
• SRC_IP: Source IP address
• DST_IP: Destination IP address
• DST_ASN: Destination Autonomous System number
• SRC_PORT: Source port
• DST_PORT: Destination port
• PROTOCOL: Transport protocol
• FLAG_CWR: Presence of the CWR flag
• FLAG_CWR_REV: Presence of the CWR flag in the reverse direction
• FLAG_ECE: Presence of the ECE flag
• FLAG_ECE_REV: Presence of the ECE flag in the reverse direction
• FLAG_URG: Presence of the URG flag
• FLAG_URG_REV: Presence of the URG flag in the reverse direction
• FLAG_ACK: Presence of the ACK flag
• FLAG_ACK_REV: Presence of the ACK flag in the reverse direction
• FLAG_PSH: Presence of the PSH flag
• FLAG_PSH_REV: Presence of the PSH flag in the reverse direction
• FLAG_RST: Presence of the RST flag
• FLAG_RST_REV: Presence of the RST flag in the reverse direction
• FLAG_SYN: Presence of the SYN flag
• FLAG_SYN_REV: Presence of the SYN flag in the reverse direction
• FLAG_FIN: Presence of the FIN flag
• FLAG_FIN_REV: Presence of the FIN flag in the reverse direction
• TLS_SNI: Server Name Indication domain
• TLS_JA3: JA3 fingerprint of TLS client
• TIME_FIRST: Timestamp of the first packet in format YYYY-MM-DDTHH-MM-SS.ffffff
• TIME_LAST: Timestamp of the last packet in format YYYY-MM-DDTHH-MM-SS.ffffff
• DURATION: Duration of the flow in seconds
• BYTES: Number of transmitted bytes from client to server
• BYTES_REV: Number of transmitted bytes from server to client
• PACKETS: Number of packets transmitted from client to server
• PACKETS_REV: Number of packets transmitted from server to client
• PPI: Packet sequence in the format: [[inter-packet times], [packet directions], [packet sizes], [push flags]]
• PPI_LEN: Number of packets in the PPI sequence
• PPI_DURATION: Duration of the PPI sequence in seconds
• PPI_ROUNDTRIPS: Number of roundtrips in the PPI sequence
• PHIST_SRC_SIZES: Histogram of packet sizes from client to server
• PHIST_DST_SIZES: Histogram of packet sizes from server to client
• PHIST_SRC_IPT: Histogram of inter-packet times from client to server
• PHIST_DST_IPT: Histogram of inter-packet times from server to client
• APP: Web service label
• CATEGORY: Service category
• FLOW_ENDREASON_IDLE: Flow was terminated because it was idle
• FLOW_ENDREASON_ACTIVE: Flow was terminated because it reached the active timeout
• FLOW_ENDREASON_END: Flow ended with the TCP connection termination
• FLOW_ENDREASON_OTHER: Flow was terminated for other reasons
  
  

Dataset created under the Connecting Europe Facility of the European Union programme, VARIOT project TENtec n. 28263632. Developed by the Intelligent Systems for Industrial Systems group supported by the Department of Education, Language policy and Culture of the Basque Government.

This dataset comprises Xiaomi Mi Home Security Basic Camera 1080P Iot device network traffic and different features under compromised operation mode.

• Device description: 1080p full HD resolution | 130° ultra-wide angle lens | 10m infrared range | night vision scope | zoning classification | intelligent detection | two-way voice communication
• Infection type: Control

East Baton Rouge Parish Library computer usage statistics are organized by branch, year, and month. This dataset only includes the count for library patrons who have logged in to the Library’s public computers, located at any of the 14 locations.

United Arab Emirates Internet Usage: Social Media Market Share: Desktop: Youku data was reported at 0.000 % in 10 Jul 2024. This stayed constant from the previous number of 0.000 % for 09 Jul 2024. United Arab Emirates Internet Usage: Social Media Market Share: Desktop: Youku data is updated daily, averaging 0.000 % from Jun 2023 (Median) to 10 Jul 2024, with 218 observations. The data reached an all-time high of 1.250 % in 26 Mar 2024 and a record low of 0.000 % in 10 Jul 2024. United Arab Emirates Internet Usage: Social Media Market Share: Desktop: Youku data remains active status in CEIC and is reported by Statcounter Global Stats. The data is categorized under Global Database’s United Arab Emirates – Table AE.SC.IU: Internet Usage: Social Media Market Share.

Internet Usage: Search Engine Market Share: Mobile: Start Page data was reported at 0.000 % in 04 Sep 2024. This stayed constant from the previous number of 0.000 % for 03 Sep 2024. Internet Usage: Search Engine Market Share: Mobile: Start Page data is updated daily, averaging 0.000 % from Feb 2024 (Median) to 04 Sep 2024, with 199 observations. The data reached an all-time high of 8.330 % in 28 May 2024 and a record low of 0.000 % in 04 Sep 2024. Internet Usage: Search Engine Market Share: Mobile: Start Page data remains active status in CEIC and is reported by Statcounter Global Stats. The data is categorized under Global Database’s Kiribati – Table KI.SC.IU: Internet Usage: Search Engine Market Share.

Iceland Internet Usage: Search Engine Market Share: All Platforms: info.com data was reported at 0.000 % in 08 Feb 2025. This stayed constant from the previous number of 0.000 % for 07 Feb 2025. Iceland Internet Usage: Search Engine Market Share: All Platforms: info.com data is updated daily, averaging 0.000 % from Jan 2025 (Median) to 08 Feb 2025, with 9 observations. The data reached an all-time high of 0.080 % in 04 Feb 2025 and a record low of 0.000 % in 08 Feb 2025. Iceland Internet Usage: Search Engine Market Share: All Platforms: info.com data remains active status in CEIC and is reported by Statcounter Global Stats. The data is categorized under Global Database’s Iceland – Table IS.SC.IU: Internet Usage: Search Engine Market Share.

France Internet Usage: Search Engine Market Share: Mobile: Haosou data was reported at 0.010 % in 02 Oct 2024. This stayed constant from the previous number of 0.010 % for 01 Oct 2024. France Internet Usage: Search Engine Market Share: Mobile: Haosou data is updated daily, averaging 0.010 % from Sep 2024 (Median) to 02 Oct 2024, with 18 observations. The data reached an all-time high of 0.020 % in 27 Sep 2024 and a record low of 0.010 % in 02 Oct 2024. France Internet Usage: Search Engine Market Share: Mobile: Haosou data remains active status in CEIC and is reported by Statcounter Global Stats. The data is categorized under Global Database’s France – Table FR.SC.IU: Internet Usage: Search Engine Market Share.

Snapshot img

Global network traffic analytics Industry Overview

Technavio’s analysts have identified the increasing use of network traffic analytics solutions to be one of major factors driving market growth. With the rapidly changing IT infrastructure, security hackers can steal valuable information through various modes. With the increasing dependence on web applications and websites for day-to-day activities and financial transactions, the instances of theft have increased globally. Also, the emergence of social networking websites has aided the malicious attackers to extract valuable information from vulnerable users. The increasing consumer dependence on web applications and websites for day-to-day activities and financial transactions are further increasing the risks of theft. This encourages the organizations to adopt network traffic analytics solutions.

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See the complete table of contents and list of exhibits, as well as selected illustrations and example pages from this report.

Companies covered

The network traffic analytics market is fairly concentrated due to the presence of few established companies offering innovative and differentiated software and services. By offering a complete analysis of the competitiveness of the players in the network monitoring tools market offering varied software and services, this network traffic analytics industry analysis report will aid clients identify new growth opportunities and design new growth strategies.

The report offers a complete analysis of a number of companies including:

Allot
Cisco Systems
IBM
Juniper Networks
Microsoft
Symantec

Network traffic analytics market growth based on geographic regions

Americas
APAC
EMEA

With a complete study of the growth opportunities for the companies across regions such as the Americas, APAC, and EMEA, our industry research analysts have estimated that countries in the Americas will contribute significantly to the growth of the network monitoring tools market throughout the predicted period.

Network traffic analytics market growth based on end-user

Telecom
BFSI
Healthcare
Media and entertainment

According to our market research experts, the telecom end-user industry will be the major end-user of the network monitoring tools market throughout the forecast period. Factors such as increasing use of network traffic analytics solutions and increasing use of mobile devices at workplaces will contribute to the growth of the market shares of the telecom industry in the network traffic analytics market.

Key highlights of the global network traffic analytics market for the forecast years 2018-2022:

CAGR of the market during the forecast period 2018-2022
Detailed information on factors that will accelerate the growth of the network traffic analytics market during the next five years
Precise estimation of the global network traffic analytics market size and its contribution to the parent market
Accurate predictions on upcoming trends and changes in consumer behavior
Growth of the network traffic analytics industry across various geographies such as the Americas, APAC, and EMEA
A thorough analysis of the market’s competitive landscape and detailed information on several vendors
Comprehensive information about factors that will challenge the growth of network traffic analytics companies

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This market research report analyzes the market outlook and provides a list of key trends, drivers, and challenges that are anticipated to impact the global network traffic analytics market and its stakeholders over the forecast years.

The global network traffic analytics market analysts at Technavio have also considered how the performance of other related markets in the vertical will impact the size of this market till 2022. Some of the markets most likely to influence the growth of the network traffic analytics market over the coming years are the Global Network as a Service Market and the Global Data Analytics Outsourcing Market.

Technavio’s collection of market research reports offer insights into the growth of markets across various industries. Additionally, we also provide customized reports based on the specific requirement of our clients.