Lessons from the social Dilemma: BSSN's social cybersecurity strategy addressing information disorders
DOI:
https://doi.org/10.12928/commicast.v6i2.13673Keywords:
Communication strategy, Disorder of information, Disinformation, Social cybersecurity, Social dilemmaAbstract
The proliferation of misinformation, disinformation, and Malinformation on social media poses a serious threat to public trust and national security. Social media algorithms, as illustrated in The Social Dilemma, inadvertently amplify false and sensational content, fostering polarization and societal vulnerability. This study aims to analyze the strategy of Indonesia’s National Cyber and Crypto Agency (Badan Siber dan Sandi Negara/BSSN) in addressing information disorder through a participatory digital literacy approach. Its main contribution lies in providing both academic insights and policy recommendations for an ethical, adaptive, and evidence-based model of social cybersecurity governance. This research employed a descriptive qualitative method, combining documentary analysis of The Social Dilemma, a review of official BSSN documents, and an in-depth interview with a BSSN official. The data were processed using thematic coding and triangulated across multiple sources to ensure credibility and validity. The findings reveal that BSSN implements the EMILIE framework, Encouragement, Measurement, Involvement, Literacy, and Empowerment, which strengthens digital literacy, promotes stakeholder engagement, and develops ethical monitoring systems while safeguarding civil rights. This framework has proven effective in raising public awareness and resilience against disinformation, although challenges remain, such as the rapid spread of harmful content, reliance on platform cooperation, and limited institutional resources. In conclusion, participatory and literacy-based approaches to social cybersecurity are essential in countering digital information disorder. BSSN’s strategy demonstrates that fostering multi-stakeholder collaboration and community empowerment can mitigate cyber threats while ensuring ethical and legal protection of citizens.
References
Abdillah, A., Widianingsih, I., Buchari, R. A., & Nurasa, H. (2024). Big data security &individual (psychological) resilience: A review of social media risks and lessons learned from Indonesia. In Array. Elsevier. https://www.sciencedirect.com/science/article/pii/S259000562400002X
Abdo, J. B., Aledhari, M., Qadir, J., Carley, K., & Al-Fuqaha, A. (2025). A survey of social cybersecurity: Techniques for attack detection, evaluations, challenges, and future prospects. qspace.qu.edu.qa. https://qspace.qu.edu.qa/handle/10576/65983
Akhtar, M. M., Masood, R., Ikram, M., & Kanhere, S. S. (2023). False Information, Bots and Malicious Campaigns: Demystifying Elements of Social Media Manipulations. ArXiv eprint arXiv:2308.12497. https://ui.adsabs.harvard.edu/abs/2023arXiv230812497M/abstract
Almatrafi, O., Johri, A., & Lee, H. (2024). A Systematic Review of AI Literacy Conceptualization. In Constructs, and.
Alsmadi, I., Ahmad, K., Nazzal, M., Alam, F., & Al-Fuqaha, A. (2021). Adversarial attacks and defenses for social network text processing applications: Techniques, challenges and future research directions. ArXiv Preprint ArXiv. https://arxiv.org/abs/2110.13980
Arroyo, P., Schöttle, A., & Christensen, R. (2021). The ethical and social dilemma of AI uses in the construction industry. In Proc. 29th Annual Conference of the International Group for Lean Contruction (IGLC). academia.edu. https://www.academia.edu/download/97114376/iglc-9ce66acc-87ce-4f66-975b-b8fd667fbd34.pdf
Awadallah, A., Eledlebi, K., & Zemerly, M. J. (2024). Artificial intelligence-based cybersecurity for the metaverse: Research challenges and opportunities. IEEE Communications Surveys &Tutorials. https://ieeexplore.ieee.org/abstract/document/10634174/
Carley, K. M. (2020). Social cybersecurity: an emerging science. Computational and Mathematical Organization Theory, 26(4), 365–381. https://doi.org/10.1007/s10588-020-09322-9
Cartwright, E., Chai, Y., & Xue, L. (2025). Leadership in a social dilemma: Does it matter if the leader is pro‐social or just says they are pro‐social? Economic Inquiry. https://doi.org/10.1111/ecin.13256
Chaudhuri, A., Behera, R. K., & Bala, P. K. (2025). Factors impacting cybersecurity transformation: An Industry 5.0 perspective. Computers &Security. https://www.sciencedirect.com/science/article/pii/S016740482400573X
Chung, M., & Wihbey, J. (2024). The algorithmic knowledge gap within and between countries: Implications for combatting misinformation. In Harvard Kennedy School. misinforeview.hks.harvard.edu. https://misinforeview.hks.harvard.edu/article/the-algorithmic-knowledge-gap-within-and-between-countries-implications-for-combatting-misinformation/
Cloos, J., Greiff, M., & Kempa, K. (2025). The effect of exploiting the public good on climate cooperation: evidence from a collective-risk social dilemma experiment. In Environment, Development and Sustainability. Springer. https://doi.org/10.1007/s10668-024-05949-9
Dai, R., Thomas, M. K. E., & Rawolle, S. (2025). Revisiting Foucault’s panopticon: how does AI surveillance transform educational norms? British Journal of Sociology of Education, 46(5), 650–668. https://doi.org/10.1080/01425692.2025.2501118
Harris, T. (2019). Our Brains Are No Match for Our Technology. In International New York Times. go.gale.com. https://go.gale.com/ps/i.do?id=GALE%7CA608221582&sid=googleScholar&v=2.1&it=r&linkaccess=abs&issn=22699740&p=AONE&sw=w
Hoehe, M. R., & Thibaut, F. (2020). Going digital: how technology use may influence human brains and behavior. Dialogues in Clinical Neuroscience. https://doi.org/10.31887/DCNS.2020.22.2
Husandani, R. A., Utari, P., & Rahmanto, A. N. (2025). Impact of social media disinformation explored in’The Social Dilemma’. Jurnal ASPIKOM. http://jurnalaspikom.org/index.php/aspikom/article/view/1534
Iddianto, I., & Azi, R. (2022). Social Effect Of Social Media Revealed In The Social Dilemma Documentary Movie: Post-Truth Perspective. Seshiski: Southeast Journal of Language and Literary Studies, 2(1), 37–50. https://doi.org/10.53922/seshiski.v2i1.3
Kholili, A. (2025). Kultur Digital: Tantangan Dan Peluang Moderasi. In Kultur Budaya Dan Digital. repository.iainmadura.ac.id. http://repository.iainmadura.ac.id/1265/2/Layout Kultur Budaya dan Digital.pdf#page=43
Kominfo. (2023). “Pidato Presiden Jokowi Diduga Menggunakan Bahasa Mandarin.” Kementrian Komunikasi Dan Informatika. https://www.kominfo.go.id/berita/berita-hoaks/detail/disinformasi-video-pidato-presiden-jokowi-diduga-menggunakan-bahasa-mandarin
Kong, S.-C., Cheung, M.-Y. W., & Tsang, O. (2024). Developing an artificial intelligence literacy framework: Evaluation of a literacy course for senior secondary students using a project-based learning approach. Computers and Education: Artificial Intelligence, 6, 100214. https://doi.org/10.1016/j.caeai.2024.100214
Kurniawan. (2023). Dokumen Paparan Keamanan Siber Sosial Mewujudkan Media Sosial yang Humanis di Tahun Politik 2024 Guna Menjaga Persatuan Nasional Dalam Rangka Keamanan Nasional. Kemenkoinfra.Go.Id. https://jdih.kemenkoinfra.go.id/cfind/source/files/perpres/2025/perpres-nomor-12-tahun-2025/lampiran-i-perpres-nomor-12-tahun-2025.pdf
Maddock-Ferrie, B. (2022). A Policy Proposal for Canadian the Government to Counter Disinformation: Countering Disinformation Through Collaboration. Federalism-E. https://ojs.library.queensu.ca/index.php/fede/article/view/15368
McDavid, J. (2020). The social dilemma. In Journal of Religion and Film. search.proquest.com. https://digitalcommons.unomaha.edu/jrf/vol24/iss1/22
Mujib, M., Fahmi Wardhani, M., & Kurniawan, R. (2023). What Leads To Counterproductive Work Behavior? Predicting The Effect Of Resistance To Change. Sinergi : Jurnal Ilmiah Ilmu Manajemen, 13(2). https://doi.org/10.25139/sng.v13i2.6574
Mulahuwaish, A., Qolomany, B., Gyorick, K., Abdo, J. B., Aledhari, M., Qadir, J., Carley, K., & Al-Fuqaha, A. (2025). A survey of social cybersecurity: Techniques for attack detection, evaluations, challenges, and future prospects. Computers in Human Behavior Reports, 18, 100668. https://doi.org/10.1016/j.chbr.2025.100668
Olsson, E., & Öhman, C. (2025). The Quantum Panopticon: A Theory of Surveillance for the Quantum Era. Minds and Machines, 35(2), 17. https://doi.org/10.1007/s11023-025-09723-2
Patel, Y., Tanwar, S., Gupta, R., Bhattacharya, P., & Davidson, I. (2023). Deepfake generation and detection: Case study and challenges. IEEE Access. https://ieeexplore.ieee.org/abstract/document/10354308/
Roshanaei, M., Khan, M. R., & Sylvester, N. N. (2024). Enhancing cybersecurity through AI and ML: Strategies, challenges, and future directions. In Journal of Information Security. scirp.org. https://www.scirp.org/journal/paperinformation?paperid=134347
Schmitt, M., & Flechais, I. (2024). Digital deception: Generative artificial intelligence in social engineering and phishing. In Artificial Intelligence Review. Springer. https://doi.org/10.1007/s10462-024-10973-2
Surjatmodjo, D., Unde, A. A., Cangara, H., & Sonni, A. F. (2024). Information Pandemic: A Critical Review of Disinformation Spread on Social Media and Its Implications for State Resilience. Social Sciences, 13(8), 418. https://doi.org/10.3390/socsci13080418
Wardle, C., & Derakhshan, H. (2017). Information disorder: Toward an interdisciplinary framework for research and policymaking. tverezo.info. http://tverezo.info/wp-content/uploads/2017/11/PREMS-162317-GBR-2018-Report-desinformation-A4-BAT.pdf
Zhao Liu, J. (2025). Digital Governance, Dataveillance, and Participatory Panopticon: Public Health Surveillance in China from 2020 to 2022. Journal of Contemporary China, 1–17. https://doi.org/10.1080/10670564.2025.2513409
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Abid Prayoga Hutomo, Andre Noevi Rahmanto, Sudarmo

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
License and Copyright Agreement
In submitting the manuscript to the journal, the authors certify that:
- They are authorized by their co-authors to enter into these arrangements.
- The work described has not been formally published before, except in the form of an abstract or as part of a published lecture, review, thesis, or overlay journal. Please also carefully read Commicast's Posting Your Article Policy at http://journal2.uad.ac.id/index.php/commicast/about/editorialPolicies#custom-5
- That it is not under consideration for publication elsewhere,
- That its publication has been approved by all the author(s) and by the responsible authorities – tacitly or explicitly – of the institutes where the work has been carried out.
- They secure the right to reproduce any material that has already been published or copyrighted elsewhere.
- They agree to the following license and copyright agreement.
Copyright
Authors who publish with Commicast agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.Â
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
Licensing for Data Publication
Commicast use a variety of waivers and licenses, that are specifically designed for and appropriate for the treatment of data:
Open Data Commons Attribution License, http://www.opendatacommons.org/licenses/by/1.0/ (default)
Creative Commons CC-Zero Waiver, http://creativecommons.org/publicdomain/zero/1.0/
Open Data Commons Public Domain Dedication and Licence, http://www.opendatacommons.org/licenses/pddl/1-0/
Other data publishing licenses may be allowed as exceptions (subject to approval by the editor on a case-by-case basis) and should be justified with a written statement from the author, which will be published with the article.
Open Data and Software Publishing and Sharing
The journal strives to maximize the replicability of the research published in it. Authors are thus required to share all data, code or protocols underlying the research reported in their articles. Exceptions are permitted but have to be justified in a written public statement accompanying the article.
Datasets and software should be deposited and permanently archived inappropriate, trusted, general, or domain-specific repositories (please consult http://service.re3data.org and/or software repositories such as GitHub, GitLab, Bioinformatics.org, or equivalent). The associated persistent identifiers (e.g. DOI, or others) of the dataset(s) must be included in the data or software resources section of the article. Reference(s) to datasets and software should also be included in the reference list of the article with DOIs (where available). Where no domain-specific data repository exists, authors should deposit their datasets in a general repository such as ZENODO, Dryad, Dataverse, or others.
Small data may also be published as data files or packages supplementary to a research article, however, the authors should prefer in all cases a deposition in data repositories.

















