Abstract

The rapid expansion of social media platforms in recent years has completely changed worldwide connectivity and communication. These platforms offer new obstacles in terms of social media crime even as they provide never-beforeseen chances for online communication, community building, and information exchange. This abstract summarizes key subjects, trends, and implications while offering an accessible overview of the connection between criminal activity and social media. The article highlights the advantages of social media, emphasizing how it may help people interact, spread knowledge, and support social activity. Social media platforms function as digital environments where people can express themselves, share personal stories, and assist in the growth of a digital community. However, this portion digs into the multiple drawbacks of social media. In Open-Source Intelligence (OSINT), data collection and profiling of readily available private and public sources are undertaken. Resources for sector information for business intelligence and personal data. The internet and other social media sites like Facebook, Gmail, Twitter, and What’s App, Instagram are some examples of these sources. Although there has been much discussion and investigation about the risks, weaknesses, and effects of using social networking sites, the purpose of this study is to reduce bias. Objective: To perform a thorough analysis and summary of the results of recent empirical research on open source and cyber intelligence profiling to find online social networks’ faults and threats for mitigation targets. Need and Rationale: Social media emerged as rapidly imposing tools of connection, expression, and dissemination of information. Unfortunately, with this growth came a rush in crime, such as cyberbullying, identity theft, online harassment, misinformation, and financial fraud, through social media. These crimes pose severe dangers to the safety and privacy of individual lives and even put existing legal and regulatory frameworks to test. Urgent analysis of these emerging threats is needed to advance digital literacy, inform policy, and develop effective prevention strategies to enhance safer online environments for all users. This study comes in the face of a need for expediency in balancing great opportunities given by social media with measures that will curtail its fraudulent use or misuse. By explaining the patterns, causes, consequences, and policy gaps regarding crimes in social media, this study aims to add to the safer, ethical, and informed digital environment by its findings. This could direct stakeholders in constructing reasonable policies and awareness campaigns in line with responsible digital citizenship building and reducing online crime. Methods: A methodical narrative review of the literature based on thorough database searches on the internet. Next, the results were subjected to review using a narrative synthesis technique along with a quantitative and qualitative rating device. Using concepts from articles on “The Effectiveness of Neighborhood Watch,” a theoretical framework was developed for the synthesis. Result: Advancements based on open-source intelligence theories. According to reports, using social media improves peer interaction and expands company potential by facilitating swift consumer information distribution. In the current fight on terror, safe identity experiments, open-source intelligence collection through social media, and online surveillance are particularly important. Recognizing terrorist network structures, mining and analyzing criminal data, and combating improvised explosive devices. The study also emphasized the possible drawbacks and dangers, including identity theft, social networking, and social engineering risks in SNSs (social networking sites). vulnerabilities in the way that cookies and HTTP header data are transmitted to third-party aggregator, in addition to the negative consequences of being exposed to attacks. Conclusion: The results of the systematic review revealed unexpected results and contradicting theories. Additionally, it has disclosed the spotlighting the research problems that affect open-source intelligence. Social media platforms are constantly used for business, social, and intelligence gathering purposes because social media technologies are invincible. However, to ensure proper and advanced mitigating circumstances, additional research is needed to gain situational awareness and appropriate measures to mitigate them.

• 1.   Thukral, P., & Kainya, V. (2022). How social media influence crimes. Indian Journal of Law and Legal Research, 4(2), 1-1.
• 2.   Prieto Curiel, R., Cresci, S., Muntean, C.I., & Bishop, S.R. (2020). Crime and its fear in social media. Palgrave Communications, 6(1).
• 3.   Nagarwal, N. (2019). Social Media Crime in Digital World-A Critique through Law, Policy and Practice. Indian JL & Just., 10, 34.
• 4.   Amedie, J. (2015). The impact of social media on society.
• 5.   Sambhe, N., Varma, P., Adlakhiya, A., Mahakalkar, A., Nakade, N., & Lakhe, R. (2021). Using OSINT to gather information about a user from multiple social networks. Information Technology in Industry, 9(2), 207-211.
• 6.   Pastor-Galindo, J., Nespoli, P., Mármol, F.G., & Pérez, G.M. (2020). The not yet exploited goldmine of OSINT: Opportunities, open challenges and future trends. IEEE Access, 8, 10282-10304.
• 7.   Edwards, L., & Urquhart, L. (2016). Privacy in public spaces: what expectations of privacy do we have in social media intelligence? International Journal of Law and Information Technology, 24(3), 279-310.
• 8.   Rønn, K.V., & Søe, S.O. (2020). Is social media intelligence private? Privacy in public and the nature of social media intelligence. In Intelligence on the frontier between state and civil society (pp. 52-68). Routledge.
• 9.   Yeboah-Ofori, A., & Brimicombe, A. (2018). Cyber intelligence and OSINT: Developing mitigation techniques against cybercrime threats on social media. International Journal of Cyber-Security and Digital Forensics (IJCSDF), 7(1), 87-98.
• 10.   Gibson, H. (2016). Acquisition and preparation of data for OSINT investigations. Open-source intelligence investigation: From Strategy to Implementation, 69-93.
• 11.   Karle, M. (2020). A social media survival guide: how to use the most popular platforms and protect your privacy. Rowman & Littlefield Publishers.
• 12.   Bartos, V. (2022). Open-source Intelligence in the Czech Media Landscape.
• 13.   McHatton, J., & Ghazinour, K. (2023, April). Mitigating Social Media Privacy Concerns-A Comprehensive Study. In Proceedings of the 9th ACM International Workshop on Security and Privacy Analytics (pp. 27-32).
• 14.   Belov, V., Tatarintsev, A., & Nikulchev, E. (2021). Choosing a data storage format in the apache hadoop system based on experimental evaluation using apache spark. Symmetry, 13(2), 195.
• 15.   Molin, S. (2019). Hands-On Data Analysis with Pandas: Efficiently perform data collection, wrangling, analysis, and visualization using Python. Packt Publishing Ltd.
• 16.   Pham, V.V.H., Yu, S., Sood, K., & Cui, L. (2018). Privacy issues in social networks and analysis: a comprehensive survey. IET networks, 7(2), 74-84.
• 17.   Anand V.A., & Mohan, A.K. (2020). PeopleXploit—A hybrid tool to collect public data. arXiv preprint arXiv:2010.15668.
• 18.   Asif, M., Ishtiaq, A., Ahmad, H., Aljuaid, H., & Shah, J. (2020). Sentiment analysis of extremism in social media from textual information. Telematics and Informatics, 48, 101345.
• 19.   Waldman, S., & Verga, S. (2016). Countering violent extremism on social media. Defence Research and Development Canada, 1, 1-28.
• 20.   Hossain, M.S. (2015). Social media and terrorism: threats and challenges to the modern era. South Asian Survey, 22(2), 136-155.
• 21.   Englander, E., Donnerstein, E., Kowalski, R., Lin, C.A., & Parti, K. (2017). Defining cyberbullying. Pediatrics, 140 (Supplement_2), S148-S151.
• 22.   Irshad, S., & Soomro, T.R. (2018). Identity theft and social media. International Journal of Computer Science and Network Security, 18(1), 43-55.
• 23.   Alwanain, M.I. (2020). Phishing awareness and elderly users in social media. Int J Comput Sci Netw Secur, 20(9), 114-19.
• 24.   Patel, P., Kannoorpatti, K., Shanmugam, B., Azam, S., & Yeo, K.C. (2017, January). A theoretical review of social media usage by cyber-criminals. In 2017 International Conference on Computer Communication and Informatics (ICCCI) (pp. 1-6). IEEE.
• 25.   King, M., Alhadidi, D., & Cook, P. (2018). Text-based detection of unauthorized users of social media accounts. In Advances in Artificial Intelligence: 31st Canadian Conference on Artificial Intelligence, Canadian AI 2018, Toronto, ON, Canada, May 8–11, 2018, Proceedings 31 (pp. 292-297). Springer International Publishing.
• 26.   Starr, T.S., & Lavis, T. (2018). Perceptions of revenge pornography and victim blame. International Journal of Cyber Criminology, 12(2), 427-438.
• 27.   Dhir, A., Talwar, S., Kaur, P., Budhiraja, S., & Islam, N. (2021). The dark side of social media: Stalking, online self-disclosure and problematic sleep. International Journal of Consumer Studies, 45(6), 1373-1391.
• 28.   Aïmeur, E., Amri, S., & Brassard, G. (2023). Fake news, disinformation and misinformation in social media: a review. Social Network Analysis and Mining, 13(1), 30.
• 29.   Chetty, N., & Alathur, S. (2018). Hate speech review in the context of online social networks. Aggression and violent behavior, 40, 108-118.
• 30.   Ali, S., Haykal, H.A., & Youssef, E.Y.M. (2023). Child sexual abuse and the internet—a systematic review. Human Arenas, 6(2), 404-421.
• 31.   Tropotei, T., & DEAC, I. (2019). Social Media In Intelligence Analysis. Strategic Impact.
• 32.   Omand, D., Bartlett, J., & Miller, C. (2012). Introducing social media intelligence (SOCMINT). Intelligence and National Security, 27(6), 801-823.
• 33.   Nasr, B. (2022). Defense Mechanisms with Threat Intelligence Capabilities against Blended Threats (Doctoral dissertation, Northcentral University).
• 34.   Rajamäki, J., & Simola, J. (2019, July). How to apply privacy by design in OSINT and big data analytics. In ECCWS 2019 18th European Conference on Cyber Warfare and Security (p. 364). Academic Conferences and publishing limited.
• 35.   Mittelstadt, B.D., & Floridi, L. (2016). The ethics of big data: current and foreseeable issues in biomedical contexts. The ethics of biomedical big data, 445-480.
• 36.   Gong, S., Cho, J., & Lee, C. (2018). A reliability comparison method for OSINT validity analysis. IEEE Transactions on Industrial Informatics, 14(12), 5428-5435.
• 37.   37. Kamal, M. (2023). Legal Implications of AIDriven OSINT: Insider Threats and Data Leaks in Egypt and the European Union. Available at SSRN 4672751.
• 38.   Ivan, A.L., Iov, C.A., Lutai, R.C., & Grad, M.N. (2015). Social media intelligence: opportunities and limitations. CES Working Papers, 7(2A), 505.
• 39.   Pastor Galindo, J. (2023). Opportunities, risks and applications of open-source Intelligence in cybersecurity and cyberdefence. Proyecto de investigación.
• 40.   Putter, D., & Henrico, S. (2022). Social media intelligence: The national security–privacy nexus. Scientia Militaria: South African Journal of Military Studies, 50(1), 19-44.

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