This paper describes the development of situational awareness models and applications to assess cybersecurity risks based on Annex ISO 27001:2013. The risk assessment method used is the direct testing method, namely audit, exercise and penetration testing. The risk assessment of this study is classified into three levels, namely high, medium and low. A high-risk value is an unacceptable risk value. Meanwhile, low and medium risk values can be categorized as acceptable risk values. The results of a network security case study with security performance index indicators based on the percentage of compliance with ISO 27001:2013 annex controls and the value of the risk level of the findings of the three test methods showed that testing with the audit method was 38.29% with a moderate and high-risk level. While the test results with the tabletop exercise method are 75% with low and moderate risk levels. On the other hand, the results with the penetration test method are 16.66%, with moderate and high-risk levels. Test results with unacceptable risk values or high-risk corrective actions are taken through an application. Finally, corrective actions have been verified to prove there is an increase in cyber resilience and security.

Cyberdisasters require an organization’s disaster team to be prepared. Disaster events are difficult to predict, but the impact of this risk on an organization is large. However, organizations sometimes struggle in being prepared for disaster situations. Here, awareness of disaster situations when analysing priority disasters (e.g., earthquakes and pandemics) and how to mitigate them can help an organization’s preparedness. Mitigation scenarios need to be determined and simulated so that a disaster team is ready to face disaster. Using Endsley’s situational awareness model and a tabletop exercise, this study aimed to help a disaster team determine cyberdisaster risk priority and assess a team’s preparedness for dealing with a cyberdisaster. The situation awareness model was divided into two stages: awareness of cyberdisaster situations and tabletop evaluations. Awareness of a disaster situation was carried out by determining the highest priority for disaster risk using the fuzzy failure modes and effects analysis (FMEA) method. The results of the first study show that the high-risk category contains ransomware attacks during pandemics and earthquakes. The second study performed a tabletop simulation questionnaire survey of earthquakes and ransomware attacks during a pandemic for several disaster teams with 152 respondents. The results of the survey evaluation of the earthquakes and ransomware attacks simulation survey show that the effect factors of cyberdisaster simulation decisions are 95% system capability (p < 0.05), 90% knowledge (p < 0.05), and 90% awareness of a disaster situation (p < 0.05); these factors show the effect of a disaster team’s decision during a tabletop simulation. The novelty of this research lies in building a model for how an organizational process determines the priority of a cyberdisaster tabletop simulation and the factors that contribute to increasing a disaster team’s awareness in dealing with cyberattacks.

The audit of Information Security Management Systems (ISMS) under ISO/IEC 27001:2022 has traditionally relied on human auditors whose competence, experience, and judgment shape audit outcomes. While effective, this human-centric approach suffers from inter-auditor variability, high cost, scheduling constraints, and limited scalability — challenges magnified by the post-pandemic shift toward remote audits and the growing volume of organisations seeking certification. Recent advances in Natural Language Processing (NLP), Computer Vision (CV), and Large Language Models (LLMs) suggest that significant portions of the audit workflow could be augmented by machine learning. However, prior research has examined these technologies in isolation; no integrated conceptual framework yet exists that unifies document review, field observation, and interviewing under a single multi-modal pipeline tailored to ISO/IEC 27001 audits and explicitly grounded in the audit methodology of ISO 19011:2018. This paper proposes such a framework — the Multi-Modal ML-Augmented ISO 27001 Audit Framework (M³A-Framework). We synthesise insights from ISO 19011:2018 audit guidelines, recent advances in AI-driven assurance, and the design science research paradigm to develop a five-stage conceptual model that augments the seven-step evidence-collection process specified in ISO 19011 Clause 6.4.7 and that extends the audit-methods matrix of ISO 19011 Annex A (Table A.1). The framework comprises: (1) audit planning and scoping; (2) multi-modal evidence collection through NLP for document analysis, CV for physical control verification (supported by inspection robots and drones), and LLM-based conversational AI for interview; (3) ML-based evidence processing and triangulation; (4) confidence-weighted finding classification using Explainable AI; and (5) human-in-the-loop validation. The framework explicitly maps each module to the 93 controls of Annex A of ISO/IEC 27001:2022 and to the audit phases mandated by ISO 19011. We further propose a set of testable propositions, evaluation metrics, and ethical considerations that ground the framework in both academic rigour and practical deployability.

In the era of digital transformation, public services such as PPK (District Election Committee) Kembangan in Jakarta are not exempt from information security challenges. This digital transformation involves integrating advanced technology into daily operations and providing services to the public through digital platforms. As the use of digital systems increases, so does the risk of cyberattacks. PPK Kembangan may face attacks such as phishing, ransomware, denial-of-service attacks, or misuse of citizens' personal data, which could disrupt election processes or other district activities. To enhance prevention against threats and vulnerabilities in information security within PPK Kembangan’s application services, a community service program was conducted through training for PPK Kembangan members. The results of this program showed that the training was successful, with participants demonstrating high enthusiasm. Participants actively asked questions regarding cases of information security attacks on both web-based and mobile applications. This program is expected to increase awareness of preventing cyber threats and vulnerabilities in PPK Kembangan’s service applications, thereby minimizing the occurrence of such attacks.

Keamanan data sebuah perusahaan adalah suatu hal yang sangat penting, maka diperlukannya keamanan untuk menjaga data-data penting tersebut agar tidak disalahgunakan. Salah satu celah yang dapat diserang ialah jaringan nirkabel karena dapat terlihat oleh publik. Pada PT. Gerak Puncak Lancar sendiri mempunyai jaringan nirkabel untuk akses internet karyawannya. Penelitian ini bertujuan untuk menguji seberapa kuat sistem keamanan dari perusahaan tersebut dengan metode Penetration Test ISSAF. ISSAF merupakan sebuah framework standar pengujian Penetration Test untuk berbagai keamanan. Seperti keamanan WLAN, website, keamanan Router, keamanan Firewall dan lain-lainnya. ISSAF sendiri mempunyai 9 aktivitas atau langkah meliputi Information Gathering, Network Mapping, Vulnerability Identification, Penetration, Gaining Access & Privilage Escalation, Enumerating Further, Compromise Remote User/Sites, Maintaining Access dan Covering tracks. Untuk WLAN Security Assessment sendiri mempunyai 6 tahap yakni, Information Gathering, Scanning, Audit, Analysis & Research, Exploit & Attacks, Reporting & Presentation. Hasil analisa penelitian ini, keamanan jaringan nirkabel Access Point staff PT. Gerak Puncak Lancar. Mempunyai nilai Overall Risk Rating tinggi atau High. Evaluasi pun dilakukan pada keamanan jaringan PT. Gerak Puncak Lancar, dan hasil evaluasi tersebut menurunkan Overall Risak Rating menjadi Medium.