Districtwise Cyber Crimes
The data for the count of cybercrimes in each district is collected from multiple sources, including law enforcement agencies, cybercrime units, and online reporting platforms. These sources document various cybercrimes, such as hacking, online fraud, identity theft, and cyberbullying. The data includes details about the nature of the crime, the location of the incident, the parties involved, and the outcomes of investigations. It is essential for law enforcement, policymakers, and cybersecurity experts to monitor and analyze this data to develop strategies for preventing and addressing cybercrimes effectively. Additionally, public awareness campaigns and educational programs are often based on these statistics to promote online safety.
Data Dictionary
| Column | Type | Label | Description |
|---|---|---|---|
| id | int4 | index | |
| year | date | Year | |
| state_name | text | State Name | |
| state_code | text | State Code | |
| district_name | text | District Name | |
| district_code | text | District Code | |
| registeration_circles | text | Case registered in circle | |
| tampering_computer_source_documents | numeric | Tampering computer source documents under Sec 65 | |
| computer_related_offences | numeric | Computer Related Offences, Dishonestly receiving stolen computer resource or communication device, Identity Theft, Cheating by personation by using computer resource, Violation of Privacy Under Sec 66 | |
| cyber_terrorism | numeric | Cyber Terrorism Under Sec 66F | |
| pub_of_sexually_exp_act_elec_form | numeric | Publication/ transmission of obscene / sexually explicit act in electronic form | |
| intrcptn_montr_decryp_info | numeric | Inter-ception or Monitoring or decryption of Information Under Sec 69 | |
| unauthorized_access_to_protected_computer_system | numeric | Un-authorized access/attempt to access to protected computer system Under Sec.70 | |
| abetment_to_commit_offences | numeric | Abetment to Commit Offences Under Sec 84 B | |
| attempt_to_commit_offences | numeric | Attempt to Commit Offences Under Sec 84C | |
| other_sections_of_it_act | numeric | Other Sections of IT Act | |
| abetment_of_suicide_online | numeric | Abetment of Suicide (Online) Under Sec 305/306 IPC | |
| cyber_stalking_bullying_of_women_or_children | numeric | Cyber Stalking/ Bullying of Women/ Children Sec 354D IPC | |
| data_theft | numeric | Data theft Under Sec 379 to 381 | |
| fraud | numeric | Total Fraud including Credit/Debit card, ATMs, Oline banking, OTP other frauds Under Sec 420 r/w Sec 465,468-471 IPC | |
| cheating | numeric | Cheating Under Sec 420 | |
| forgery | numeric | Forgery Under Sec 465, 468 & 471 | |
| defamation_or_morphing | numeric | Defamation/ Morphing Under Sec 469 IPC r/w IPC and Indecent representation of women Act | |
| fake_profile | numeric | Fake Profile r/w IPC/SLL | |
| counterfeiting | numeric | Total Counter-feiting | |
| cyber_blackmailing_threatening | numeric | Cyber Blackmailing/Threatening Under Sec 506,503,384 IPC r/w IPC/SLL | |
| fake_news_on_social_media | numeric | Fake News on Social Media Under Sec 505 | |
| other_offences | numeric | Other Offences r/w IT Act | |
| gambling_act | numeric | Gambling Act includes Online Gambling | |
| lotteries_act | numeric | Lotteries Act includes Online Lotteries | |
| copy_right_act | numeric | Copy Right Act, 1957 | |
| trade_marks_act | numeric | Trade Marks Act, 1999 | |
| other_sll_crimes | numeric | Other SLL Crimes | |
| total_cyber_crimes | numeric | Total Cyber Crimes |
Additional Information
| Field | Value |
|---|---|
| Data last updated | June 24, 2024 |
| Metadata last updated | June 25, 2024 |
| Created | June 24, 2024 |
| Format | CSV |
| License | Open Data Commons Attribution License |
| Additional info | nan |
| Data extraction page | https://ncrb.gov.in/crime-in-india.html |
| Data insights | 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. |
| Data last updated | 2,021 |
| Data retreival date | 2023-10-01 00:00:00 |
| Datastore active | True |
| District no | 12 |
| Frequency | Yearly |
| Granularity | District |
| Has views | True |
| Id | 7c78e2a7-a667-485e-bdb0-a460a6466179 |
| Idp ready | True |
| 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. |
| No indicators | 27 |
| Package id | db72aca9-7907-456c-a7f5-407ecd3d0fc6 |
| Position | 4 |
| Size | 13.6 KiB |
| Sku | ncrb-cii_cyber_crimes-dt-yr-him |
| State | active |
| States uts no | 1 |
| Url type | upload |
| Years covered | 2017-2021 |
| 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. |
| Similar Resources | |
| Granularity Level | District |
| Data Extraction Page | https://ncrb.gov.in/crime-in-india.html |
| Data Retreival Date | 2023-10-01 00:00:00 |
| Data Last Updated | 2021 |
| Sku | ncrb-cii_cyber_crimes-dt-yr-him |
| Dataset Frequency | Yearly |
| Years Covered | 2017-2021 |
| No of States/UT(s) | 1 |
| No of Districts | 12 |
| No of Tehsils/blocks | |
| No of Gram Panchayats | |
| Additional Information | nan |
| Number of Indicators | 27 |
| 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 |