Data Dictionary

ID
id
Typ
int4
Etikett
index

ID
year
Typ
text
Etikett
Year

ID
state_name
Typ
text
Etikett
State Name

ID
state_code
Typ
text
Etikett
State Code

ID
district_name
Typ
text
Etikett
District Name

ID
district_code
Typ
text
Etikett
District Code

ID
registration_circles
Typ
text
Etikett
Registration Circles

ID
tampering_computer_source_documents
Typ
numeric
Etikett
Tampering Computer Source Documents

ID
ransom_ware
Typ
numeric
Etikett
Ransom Ware

ID
offences_other_than_ransom_ware
Typ
numeric
Etikett
Offences Other Than Ransom Ware

ID
dishonestly_recv_stolen_cmp_resrc_or_comm_device
Typ
numeric
Etikett
Dishonestly Receiving Stolen Computer Resource Or Communication Device

ID
identity_theft
Typ
numeric
Etikett
Identity Theft

ID
cheating_by_personation_by_using_computer_resource
Typ
numeric
Etikett
Cheating By Personation By Using Computer Resource

ID
violation_of_privacy
Typ
numeric
Etikett
Violation Of Privacy

ID
cyber_terrorism
Typ
numeric
Etikett
Cyber Terrorism

ID
pub_or_trans_obscene_material_in_electronic_form
Typ
numeric
Etikett
Publishing Or Transmitting Obscene Material In Electronic Form

ID
pub_or_trans_mtrl_cont_sxly_explct_act_elect_frm
Typ
numeric
Etikett
Publishing Or Transmitting Of Material Containing Sexually Explicit Act In Electronic Form

ID
pub_or_trans_mtrl_dpct_chl_sxly_explct_elect_frm
Typ
numeric
Etikett
Publishing Or Transmitting Of Material Depicting Children In Sexually Explicit Act In Electronic Form

ID
presrv_and_retention_of_info_by_intermediaries
Typ
numeric
Etikett
Preservation And Retention Of Information By Intermediaries

ID
other_sections_it_act
Typ
numeric
Etikett
Other Sections It Act

ID
interception_or_monitoring_or_decryption_of_info
Typ
numeric
Etikett
Interception Or Monitoring Or Decryption Of Information

ID
un_athryz_access_atmpt_access_prct_comp_sys
Typ
numeric
Etikett
Un Authorized Access Attempt To Access To Protected Computer System

ID
abetment_to_commit_offences
Typ
numeric
Etikett
Abetment To Commit Offences

ID
attempt_to_commit_offences
Typ
numeric
Etikett
Attempt To Commit Offences

ID
other_sections_of_it_act
Typ
numeric
Etikett
Other Sections Of It Act

ID
abetment_of_suicide_online
Typ
numeric
Etikett
Abetment Of Suicide Online

ID
cyber_stalking_bullying_of_women_children
Typ
numeric
Etikett
Cyber Stalking Bullying Of Women Children

ID
data_theft
Typ
numeric
Etikett
Data Theft

ID
credit_card_debit_card_fraud
Typ
numeric
Etikett
Credit Card Debit Card Fraud

ID
atms_fraud
Typ
numeric
Etikett
Atms Fraud

ID
online_banking_fraud
Typ
numeric
Etikett
Online Banking Fraud

ID
otp_frauds
Typ
numeric
Etikett
Otp Frauds

ID
other_frauds
Typ
numeric
Etikett
Other Frauds

ID
cheating
Typ
numeric
Etikett
Cheating

ID
forgery
Typ
numeric
Etikett
Forgery

ID
defamation_morphing
Typ
numeric
Etikett
Defamation Morphing

ID
fake_profile
Typ
numeric
Etikett
Fake Profile

ID
currency_counterfeiting
Typ
numeric
Etikett
Currency Counterfeiting

ID
stamps_counterfeiting
Typ
numeric
Etikett
Stamps Counterfeiting

ID
cyber_blackmailing_threatening
Typ
numeric
Etikett
Cyber Blackmailing Threatening

ID
fake_news_on_social_media
Typ
numeric
Etikett
Fake News On Social Media

ID
other_offences
Typ
numeric
Etikett
Other Offences

ID
total_offences_under_ip
Typ
numeric
Etikett
Total Offences Under Ip

ID
gambling_act
Typ
numeric
Etikett
Gambling Act

ID
lotteries_act
Typ
numeric
Etikett
Lotteries Act

ID
copy_right_act
Typ
numeric
Etikett
Copy Right Act

ID
trade_marks_act
Typ
numeric
Etikett
Trade Marks Act

ID
other_sll_crimes
Typ
numeric
Etikett
Other Sll Crimes

Mer information

Fält Värde
Data senast uppdaterad 20 november 2024
Metadata senast uppdaterad 19 december 2025
Skapad 4 september 2024
Format CSV
Licens Licens ej angiven
Additional infonan
Data extraction pagehttps://ncrb.gov.in/crime-in-india.html
Data insightsThe insights gleaned from cybercrime data are highly valuable. They help identify patterns and trends in cybercrimes, enabling law enforcement agencies to focus their efforts on areas with higher incidence rates. Moreover, this data aids in understanding the types of cybercrimes that are most prevalent, such as phishing, identity theft, or online fraud. Such insights are crucial for developing effective preventive measures, enhancing cybersecurity awareness, and strengthening legal frameworks. They also highlight the need for educational initiatives and resources to empower individuals and organizations to protect themselves from cyber threats, ultimately contributing to a safer digital environment.
Data last updated01-08-2024
Data retreival date2024-07-01 00:00:00
Datastore activeTrue
District no752
FrequencyYearly
Geo columns['state_code', 'district_code']
GranularityDistrict
Has viewsTrue
Id2353f85d-372a-4bb2-8617-32775891f39b
Idp readyTrue
Lgd mappingyes
MethodologyThe process of generating data for cybercrimes in each district is intricate. It starts with incident reporting by local authorities and individuals, followed by data collection and maintenance by law enforcement agencies. Legal involvement, including interviews and digital forensics, supplements the data. Each district maintains its records, and this information is periodically reported to a central agency. Data undergoes classification, analysis, and anonymization, shedding light on trends and areas with high cybercrime rates. Insights guide prevention strategies, awareness campaigns, and legislation. The public's role in reporting and practicing safe online behavior is emphasized, while resource allocation benefits from understanding local cybercrime trends.
Mimetypetext/csv
No indicators41
Package ide311a510-ce48-4f4c-baf6-0ec5f9278285
Position7
Size1,1 MiB
Skuncrb-cii_cyber_crimes-dt-yr-aaa
Stateactive
States uts no36
Tags['Cyber crimes', 'identity theft', 'cyber terrorism', 'gambling', 'frogery', 'fraud']
Url typeupload
Years covered2017-2022
Methodology The process of generating data for cybercrimes in each district is intricate. It starts with incident reporting by local authorities and individuals, followed by data collection and maintenance by law enforcement agencies. Legal involvement, including interviews and digital forensics, supplements the data. Each district maintains its records, and this information is periodically reported to a central agency. Data undergoes classification, analysis, and anonymization, shedding light on trends and areas with high cybercrime rates. Insights guide prevention strategies, awareness campaigns, and legislation. The public's role in reporting and practicing safe online behavior is emphasized, while resource allocation benefits from understanding local cybercrime trends.
Indicators
Similar Resources
Granularity Level District
Data Extraction Page https://ncrb.gov.in/crime-in-india.html
Data Retreival Date 2024-07-01 00:00:00
Data Last Updated 01-08-2024
Sku ncrb-cii_cyber_crimes-dt-yr-aaa
Dataset Frequency Yearly
Years Covered 2017-2022
No of States/UT(s) 36
No of Districts 752
No of Tehsils/blocks
No of Gram Panchayats
Mer information nan
Number of Indicators 41
Insights from the dataset The insights gleaned from cybercrime data are highly valuable. They help identify patterns and trends in cybercrimes, enabling law enforcement agencies to focus their efforts on areas with higher incidence rates. Moreover, this data aids in understanding the types of cybercrimes that are most prevalent, such as phishing, identity theft, or online fraud. Such insights are crucial for developing effective preventive measures, enhancing cybersecurity awareness, and strengthening legal frameworks. They also highlight the need for educational initiatives and resources to empower individuals and organizations to protect themselves from cyber threats, ultimately contributing to a safer digital environment.
IDP Ready Yes
LGD Mapping Yes
Mapping Status %
Geo Columns ['state_code', 'district_code']