Conceptualising Cyber-Crime Against Women: Beyond Numbers And “Online Misbehaviour”

Mahera Imam

Introduction

The rapid expansion of digital technologies in India has opened up unprecedented opportunities for women in education, employment, financial inclusion and political participation. Yet these same technologies have also created new sites for control, humiliation and violence. Smartphones and social media platforms can easily become tools for stalking, blackmail, non consensual image sharing and coordinated harassment. In this context, “cyber-crime against women” is not merely a technical or legal category; it is a window into how gendered power reorganises itself in digital spaces.

India is one of the few countries that publishes detailed, annual crime statistics through the National Crime Records Bureau (NCRB). Recent Crime in India reports show both a rise in overall cyber-crime cases and persistently high levels of crimes against women. For example, the 2023 report records 86,420 cyber-crime cases, an increase of over 30% from 2022, with the cyber-crime rate rising from 4.8 to 6.2 cases per lakh population. In the same year, crimes against women crossed 4.48 lakh, with a crime rate of 66.2 per lakh female population, slightly higher than in 2022. These figures underscore that both offline and online harms remain pressing concerns.

However, to conceptualise “cyber-crime against women” in a robust way, we must move beyond raw numbers. We need to situate cyber-violence within feminist theory, global policy frameworks, typologies of digital harms, and the methodological limitations of existing data.

Scholarly and Policy Debates: From “Online Misbehaviour” to TF-VAW

Early public debates often trivialised online abuse as “misbehaviour” or a side-effect of anonymity, with women advised to “ignore” or “log off”. Feminist scholars and international organisations have firmly challenged this view.

UN Women and allied experts use the concept of technology-facilitated violence against women (TF-VAW) to describe any act of gender-based violence that is committed, assisted, or aggravated by digital technologies ranging from cyberstalking and doxxing to image-based

abuse and online death or rape threats. TF-VAW is understood as part of a continuum of gender based violence, not as a separate, purely “virtual” phenomenon: the same patriarchal norms that sanction domestic abuse or street harassment are expressed through new tools, at greater scale and speed.

In the scholarly literature, Nicole Henry and Anastasia Powell have analysed technology facilitated sexual violence, highlighting how acts such as “revenge porn” and non-consensual sharing of intimate images combine sexual, psychological and social harm in ways that law and policy have struggled to recognise. They emphasise that digital technologies intensify violence by making it persistent (content is hard to remove), portable (it follows the victim everywhere via their phone), and networked (it can be shared and amplified by many actors).

At the same time, feminist data scholars remind us that how we conceptualise cyber-crime is tied to how we measure it. In Data Feminism, Catherine D’Ignazio and Lauren Klein argue that data are never neutral; they reflect power relations whose experiences are recorded, who is believed, and which harms the system is designed to see. Safiya Noble’s work in Algorithms of Oppression shows that supposedly “neutral” search engines and algorithms often reproduce racist and sexist stereotypes, shaping the information environments where abuse occurs. Together, these scholars push us to think of cyber-crime against women not just as a set of incidents, but as a phenomenon embedded in platform architectures, legal categories, and social hierarchies.

Typologies: Understanding Different Forms of Cyber-Crime Against Women

Conceptual clarity requires distinguishing between different types of cyber-crime that affect women, even when they appear under broad headings in NCRB data.

One central category is cyberstalking and online harassment. Here, perpetrators repeatedly contact, monitor, or threaten women through messages, calls or posts, often across multiple platforms. The harm lies not only in explicit threats but in the relentlessness of the behaviour, which can push women to withdraw from social media, political expression or professional networking to feel safer.

A second, highly consequential form is image-based abuse or non-consensual sharing of intimate images and videos. Perpetrators may leak such content after breakups, steal it through hacking, or create doctored or “deepfake” images. The threat of exposure can be enough to extort sexual, emotional or financial compliance. In many Indian contexts, where honour and

reputation are tightly policed, the social consequences for women can be catastrophic even if the images never leave a small circle.

Impersonation and identity abuse represent another cluster, where offenders create fake profiles using a woman’s photos or details, or misuse her identifiers for fraud. These acts can invite unwanted sexual attention, damage reputations, or entangle women in financial scams they did not initiate.

Sextortion and digital blackmail sit at the intersection of sexual and financial violence, leveraging the threat of exposure of real or fabricated intimate content. Doxxing and targeted hate the publication of personal information alongside incitement often affects women who are visible in public life: journalists, activists, students, politicians. These campaigns can combine thousands of small actions (comments, messages, shares) that are hard to capture through incident-based legal categories.

Finally, there are emerging harms such as AI-generated deepfake pornography, covert spyware on personal devices, and misogynistic online communities dedicated to demeaning women that remain poorly captured in current classificatory systems. UN Women and others have noted that existing legal and statistical frameworks lag behind these developments, leaving large areas of TF-VAW effectively invisible.

For conceptualisation, this typology matters because it shows that “cyber-crime against women” is not homogeneous. Each type involves different actors, technological affordances, and required remedies; a single aggregated figure cannot convey these distinctions.

Reports and Data: NCRB, NFHS-5 and the Global Gender Gap

To move from concept to evidence, we rely on a small set of key datasets and reports. At the national level, NCRB’s Crime in India series is the primary administrative source. The 2023 report records 86,420 cyber-crime cases and documents that cyber-crime rates have risen steadily over recent years. It also shows that crimes against women overall climbed to over 4.48 lakh cases, suggesting that online harms are unfolding within a broader context of persistent offline violence. Within the cyber-crime chapter, NCRB provides breakdowns by motive and category for example, fraud, sexual exploitation, obscene content, and stalking though the granularity for “cyber-crimes against women” specifically is still limited and sometimes spread across sections.

To interpret these numbers, we must understand who is online in the first place. NFHS-5 (2019– 21) shows that only about 33.3% of Indian women aged 15–49 report having ever used the internet, with stark urban–rural divides: approximately 51.8% of urban women versus 24.6% of rural women. This means that the population at risk of online victimisation and capable of filing online complaints is a subset of all women, shaped by class, geography, age and education.

Globally, the GSMA Mobile Gender Gap Report 2023 provides important context: in low- and middle-income countries, women are 19% less likely than men to use mobile internet, and almost 900 million women still do not use it at all, with a large concentration in South Asia and Sub-Saharan Africa. Subsequent GSMA analyses highlight that South Asia continues to have one of the widest gender gaps in mobile internet use. These figures remind us that under

reporting is structurally baked in: vast numbers of women either lack access or lack the conditions (privacy, literacy, safety) needed to report cyber-violence.

Finally, we must factor in reporting infrastructure. India’s National Cybercrime Reporting Portal and the 1930 helpline provide national channels for lodging cybercrime complaints, including those involving women. Their rollout and increasing public visibility likely contribute to rising reported numbers by lowering the barriers to lodging complaints.

Taken together, these reports suggest that rising NCRB figures should be understood as the product of at least four interacting processes: underlying risk, digital access, reporting mechanisms, and changing legal-statistical categories.

Conceptual and Practical Challenges

Conceptualising cyber-crime against women through this data landscape presents several challenges.

First, there is the problem of under-reporting and misclassification. Many women, especially from marginalised communities, may never report abuse because of stigma, fear of disbelief, or lack of trust in institutions. When they do report, their complaints may be recorded under general headings (such as “obscenity” or “insult”) rather than as gendered, technology

facilitated violence.

Second, there are category and definition issues. NCRB’s categories have evolved over time: new sub-headings like cyberstalking have been introduced, some labels have changed, and

some emerging harms (such as deepfake pornography) still lack clear classification. This makes long-term trend analysis difficult and risks underestimating novel forms of abuse.

Third, there is the access gap. As NFHS-5 and GSMA show, large numbers of women remain offline or under-connected, particularly in rural and low-income contexts. Their experiences of digital harm often mediated through shared phones, cybercafés, or third-party devices are least likely to be captured in administrative data. Any conceptual model that equates reported NCRB cyber-crime volumes with true prevalence will therefore systematically underestimate harm among the most disadvantaged.

Fourth, the platform dimension is inadequately addressed in crime statistics. Many abuses occur in the grey zone between platform policies and national law: harmful content may not cross the legal threshold for prosecution but can still cause serious cumulative harm. Platform moderation practices, algorithmic amplification of misogynistic content, and opaque takedown processes rarely appear in national crime data, yet they shape the environment in which cyber

crimes against women occur.

Finally, there is the risk of policy misinterpretation. Rising NCRB numbers may be used either to fuel moral panic and calls for overbroad censorship, or to dismiss online violence as “only” a reflection of better reporting. Both reactions miss the point: the numbers are a signal that safety and justice systems are struggling to keep pace with digital transformation, especially for women.

Ways Forward: Towards a Feminist, Data-Informed Approach

A constructive way forward requires combining conceptual clarity with pragmatic reforms.

First, adopting the TF-VAW framing more explicitly in Indian policy and research would help connect cyber-crime to the broader continuum of gender-based violence. This includes recognising that harms span emotional, social, economic and political dimensions, and that online and offline violations reinforce each other.

Second, there is a need to improve data systems. NCRB could stabilise and refine categories that are especially relevant for women such as image-based abuse, cyberstalking, and impersonation while publishing more disaggregated, machine-readable data. This would enable researchers to trace offence-specific trends and geographical patterns more accurately. Aligning administrative categories with international guidance on TF-VAW from bodies like UN Women would further enhance comparability.

Third, analyses of cyber-crime against women should systematically triangulate NCRB data with other sources: household surveys (NFHS-5), digital access and gender gap reports (GSMA), platform transparency reports, and qualitative research with survivors and practitioners. No single dataset can capture the full complexity of digital harm.

Fourth, policy responses must address both access and safety. Expanding women’s digital inclusion through affordable devices, connectivity and digital literacy must go hand in hand with gender-sensitive cyber-policing, survivor-centred support services, faster content takedowns, and clear liability frameworks for platforms. Otherwise, as UN Women and GSMA warn, closing the digital gender gap without addressing safety simply exposes more women to unmitigated risk.

Finally, conceptual work should inform legal and institutional reforms. Feminist legal scholars and practitioners can help ensure that laws recognise the specificities of digital harm (such as persistence, replicability, and networked abuse) without relying on paternalistic or moralistic restrictions on women’s own expression and mobility.

Conclusion

Conceptualising cyber-crime against women is not merely a technical exercise in defining new offences; it is a broader project of understanding how gendered power operates in digital environments and how states, platforms and communities respond. The Indian case, with its combination of rapid digitalisation, persistent gender inequalities and relatively rich administrative data through NCRB, offers both opportunities and cautions.

On the one hand, rising cyber-crime and crimes-against-women figures undeniably signal that women’s safety online and offline remains under threat. On the other hand, as feminist theorists and data scholars remind us, these numbers are shaped by access, reporting infrastructures, and evolving categories. They must therefore be read as partial but important signals, not as full measures of prevalence.

A rigorous, critical, and feminist conceptualisation of cyber-crime against women insists on holding these tensions together. It uses data, but does not worship them; it names new forms of harm, but does not treat them as detached from older structures of inequality; and it insists that digital justice must be built not only through new laws and portals, but through deeper transformations in whose voices are heard, whose harms are believed, and whose safety is treated as non-negotiable in the digital age.

References

Bailey, J., Flynn, A., & Henry, N. (Eds.). (2021). Technology-Facilitated Violence and Abuse: International Perspectives and Experiences. Emerald Publishing.
D’Ignazio, C., & Klein, L. F. (2020). Data Feminism. MIT Press.
Gámez-Guadix, M., et al. (2023). The prevalence of technology-facilitated sexual violence: A meta-analysis and systematic review. Trauma, Violence, & Abuse.
GSMA. (2023). The Mobile Gender Gap Report 2023. GSMA. Retrieved from the GSMA website.
Henry, N., & Powell, A. (2018). Technology-facilitated sexual violence: A literature review of empirical research. Trauma, Violence, & Abuse, 19(2), 195–208.
Ministry of Health and Family Welfare (MoHFW), Government of India, & IIPS. (2021). National Family Health Survey (NFHS-5), 2019–21: India Report (FR375). International Institute for Population Sciences.
National Crime Records Bureau (NCRB). (2025). Crime in India 2023: Statistics. Ministry of Home Affairs, Government of India. (Key highlights summarised in Drishti IAS and other secondary analyses.)
National Cyber Crime Reporting Portal (NCRP). (n.d.). National Cyber Crime Reporting Portal & Helpline 1930. Indian Cyber Crime Coordination Centre (I4C), Ministry of Home Affairs, Government of India. Retrieved from cybercrime.gov.in and i4c.mha.gov.in.
Noble, S. U. (2018). Algorithms of Oppression: How Search Engines Reinforce Racism. New York University Press.
UN Women. (2023a). Technology-Facilitated Violence Against Women: Taking Stock of Evidence and Data Collection. UN Women.
UN Women. (2023b). Expert Group Meeting Report: Technology-Facilitated Violence Against Women. UN Women.
UN Women. (2025). Repository of UN Women’s Work on Technology-Facilitated Violence Against Women and Girls. UN Women