Analysis of PTKIN Domain Security in West Sumatra Based on Spam Score, Cloudflare, and Backlink

Muhammad Rahfiqa Zainal, Ihdi Syahputra Ritonga, Ahmad Zaki, Agus Sundari

Abstract


This study investigates the security and digital reputation posture of three State Islamic Universities (UIN) in West Sumatra—UIN Imam Bonjol (uinib.ac.id), UIN Mahmud Yunus (uinmy.ac.id), and UIN Sjech M. Djamil Djambek Bukittinggi (uinbukittinggi.ac.id)—using externally observable indicators during December 1–15, 2025. The assessment integrates third‑party domain reputation metrics (Moz Spam Score, Domain/Page Authority, backlink volume, and toxic backlink ratio) with passive network inspection to identify Cloudflare reverse‑proxy/WAF adoption and the negotiated TLS protocol version. Data are analyzed descriptively and through inferential modeling, including Pearson correlation between Cloudflare activation (binary) and Spam Score, and K-Means clustering to classify institutional risk into low, medium, and high zones. Results show substantial disparity: UIN Imam Bonjol exhibits a healthy Spam Score (2%) with Cloudflare enabled and TLS 1.3, whereas UIN Bukittinggi records a critical Spam Score (45%) and a high toxic backlink ratio (7.3%) without Cloudflare. Correlation analysis indicates a strong inverse association between Cloudflare activation and Spam Score (r = −0.89). Forensic backlink inspection identifies SEO poisoning patterns on vulnerable academic subdomains, dominated by gambling-related anchors (45%) and adult content (20%). The proposed risk zoning supports targeted recommendations, including WAF standardization, OJS hardening and patching, content moderation, and the cleanup or disavowal of toxic backlinks to protect the institutional reputation.


Keywords


cybersecurity; SEO poisoning; spam score; Cloudflare; backlink quality; risk clustering

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References


J. Sureda-Negre, A. Calvo-Sastre, and R. Comas-Forgas, “Predatory journals and publishers: Characteristics and impact of academic spam to researchers in educational sciences,” Learned Publishing, vol. 35, no. 4, pp. 441–447, Oct. 2022, doi: 10.1002/LEAP.1450;PAGE:STRING:ARTICLE/CHAPTER.

F. Sinlae, F. Sabila Rosyad, F. Nurhidayat, and W. Jannah, “The Evolution of Web Technology and Its Impact on Digital Society,” Journal of Multidisciplinary Science, vol. 3, no. 2, pp. 146–154, Jul. 2024, doi: 10.38035/jim.v3i2.608.

T. D. Le, T. Le-Dinh, and S. Uwizeyemungu, “Search engine optimization poisoning: A cybersecurity threat analysis and mitigation strategies for small and medium-sized enterprises,” Technol Soc, vol. 76, p. 102470, 2024, doi: https://doi.org/10.1016/j.techsoc.2024.102470.

N. Kader, I. Kang, and O. Seneviratne, “Enhancing Web Spam Detection Through a Blockchain-Enabled Crowdsourcing Mechanism,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , vol. 15440 LNCS, pp. 485–499, 2025, doi: 10.1007/978-981-96-0576-7_35.

J. Kumar, A. Santhanavijayan, B. Janet, B. Rajendran, and B. S. Bindhumadhava, “Phishing website classification and detection using machine learning,” 2020 International Conference on Computer Communication and Informatics, ICCCI 2020, Jan. 2020, doi: 10.1109/ICCCI48352.2020.9104161.

J. Kumar, A. Santhanavijayan, B. Janet, B. Rajendran, and B. S. Bindhumadhava, “Phishing website classification and detection using machine learning,” 2020 International Conference on Computer Communication and Informatics, ICCCI 2020, Jan. 2020, doi: 10.1109/ICCCI48352.2020.9104161.

M. YILDIRIM, “Using and Comparing Machine Learning Techniques for Automatic Detection of Spam Website URLs,” NATURENGS MTU Journal of Engineering and Natural Sciences Malatya Turgut Ozal University, May 2022, doi: 10.46572/naturengs.1097970.

L. A. Abuwardih, “Towards Evaluating Web Spam Threats and Countermeasures,” IJACSA) International Journal of Advanced Computer Science and Applications, vol. 9, no. 10, 2018, Accessed: Dec. 01, 2025. [Online]. Available: www.ijacsa.thesai.org

A. Shahzad, N. M. Nawi, M. Z. Rehman, and A. Khan, “An Improved Framework for Content- And Link-Based Web-Spam Detection: A Combined Approach,” Complexity, vol. 2021, 2021, doi: 10.1155/2021/6625739.

J. R. Tadhani, V. Vekariya, V. Sorathiya, S. Alshathri, and W. El-Shafai, “Securing web applications against XSS and SQLi attacks using a novel deep learning approach,” Scientific Reports 2024 14:1, vol. 14, no. 1, pp. 1803-, Jan. 2024, doi: 10.1038/s41598-023-48845-4.

E. Ratnasari, A. M. Afrilia, and W. E. Putri, “Information Quality of Regional Government’s Websites in Central Java Province,” Mediator: Jurnal Komunikasi, vol. 16, no. 2, pp. 398–415, Jan. 2024, doi: 10.29313/mediator.v16i2.2639.

M. Fahreza Bahtiar, N. A. Sari, and M. F. Annshori, “From Regulation to Realization: Implementation of Public Information Disclosure Through Village Government Websites.”

T. Rochmadi, V. P. Widartha, T. A. Sarmento, A. A. Harahap, and I. Ajis, “Forensic Investigation of SEO Manipulation in Moodle LMS: Uncovering Illegal Content in Educational Platforms,” 2025.

I. Rohr, “Backlink Analysis Tools: A Nontraditional Resource for Intelligence Practitioners,” Security and Intelligence, vol. 9, no. 1, 2024, doi: 10.18278/SI.9.1.6.

K. Daram and P. Senthilkumar, “Optimizing Cloudflare security and performance with AI-based Web Application Firewall and anomaly detection,” International Journal on Smart Sensing and Intelligent Systems, vol. 18, no. 1, Jan. 2025, doi: 10.2478/ijssis-2025-0040.

M. Ouhssini, K. Afdel, M. Akouhar, E. Agherrabi, and A. Abarda, “Advancements in detecting, preventing, and mitigating DDoS attacks in cloud environments: A comprehensive systematic review of state-of-the-art approaches,” Egyptian Informatics Journal, vol. 27, p. 100517, Sep. 2024, doi: 10.1016/J.EIJ.2024.100517.

I. Drivas, D. Kouis, D. Kyriaki-Manessi, and G. Giannakopoulos, “Content Management Systems Performance and Compliance Assessment Based on a Data-Driven Search Engine Optimization Methodology,” Information 2021, Vol. 12, Page 259, vol. 12, no. 7, p. 259, Jun. 2021, doi: 10.3390/INFO12070259.

I. Riadi, A. Yudhana, and P. Korspondensi, “Website Security Analysis of the Open Journal System Using the Vulnerability Assessment Method,” Journal of Information Technology and Computer Science, vol. 7, no. 4, pp. 853–860, Aug. 2020, doi: 10.25126/JTIIK.2020701928.

F. Jáñez-Martino, R. Alaiz-Rodríguez, V. González-Castro, E. Fidalgo, and E. Alegre, “A review of spam email detection: analysis of spammer strategies and the dataset shift problem,” Artificial Intelligence Review 2022 56:2, vol. 56, no. 2, pp. 1145–1173, May 2022, doi: 10.1007/S10462-022-10195-4.

W. El Maouaki, N. Innan, A. Marchisio, T. Said, M. Bennai, and M. Shafique, “Quantum Clustering for Cybersecurity”.

N. Omer, F. Elssied, N. O. Fadl Elssied, and O. Ibrahim, “Research Article K-Means Clustering Scheme for Enhanced Spam Detection,” Research Journal of Applied Sciences, Engineering and Technology, vol. 7, no. 10, pp. 1940–1952, 2014, doi: 10.19026/ajfst.7.486.

B. N. Yulisasih, H. Herman, S. Sunardi, and H. Yuliansyah, “Evaluation of K-Means Clustering Using Silhouette Score Method on Customer Segmentation,” ILKOM Scientific Journal, vol. 16, no. 3, pp. 330–342, Dec. 2024, doi: 10.33096/ilkom.v16i3.2325.330-342.

J. Sureda-Negre, A. Calvo-Sastre, and R. Comas-Forgas, “Predatory journals and publishers: Characteristics and impact of academic spam to researchers in educational sciences,” Learned Publishing, vol. 35, no. 4, pp. 441–447, Oct. 2022, doi: 10.1002/LEAP.1450;PAGE:STRING:ARTICLE/CHAPTER.

Z. Lin, Z. Lin, R. Guo, J. Chen, M. Zhang, X. Liu, T. Yang, Z. Cao, and R. H. Deng, “Detecting and Measuring Security Implications of Entangled Domain Verification in CDN,” arXiv preprint, arXiv:2409.01887, Sep. 3, 2024, doi:10.48550/arXiv.2409.01887.




DOI: https://doi.org/10.15548/jostech.v6i1.13524

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