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Analysis of Conti Ransomware Attack on Computer Network with Live Forensic Method Umar, Rusydi; Riadi, Imam; Kusuma, Ridho Surya
IJID (International Journal on Informatics for Development) Vol. 10 No. 1 (2021): IJID June
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2021.2423

Abstract

Ransomware viruses have become a dangerous threat increasing rapidly in recent years. One of the variants is Conti ransomware that can spread infection and encrypt data simultaneously. Attacks become a severe threat and damage the system, namely by encrypting data on the victim's computer, spreading it to other computers on the same computer network, and demanding a ransom. The working principle of this Ransomware acts by utilizing Registry Query, which covers all forms of behavior in accessing, deleting, creating, manipulating data, and communicating with C2 (Command and Control) servers. This study analyzes the Conti virus attack through a network forensic process based on network behavior logs. The research process consists of three stages, the first stage is simulating attacks on the host computer, the second stage is carrying network forensics by using live forensics methods, and the third stage is analysing malware by using statistical and dynamic analysis. The results of this study provide forensic data and virus behavior when running on RAM and computer networks so that the data obtained makes it possible to identify ransomware traffic on the network and deal with zero-day, especially ransomware threats. It is possible to do so because the analysis is an initial step in generating virus signatures based on network indicators.
Android Malware Threats: A Strengthened Reverse Engineering Approach to Forensic Analysis Kusuma, Ridho Surya; Putra , Muhammad Dirga Purnomo
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 10 No. 1 (2025): January 2025
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2025.10.1.122-138

Abstract

The widespread adoption of Android devices has rendered them a primary target for malware attacks, resulting in substantial financial losses and significant breaches of user privacy. Malware can exploit system vulnerabilities to execute unauthorized premium SMS transactions, exfiltrate sensitive data, and install additional malicious applications. Conventional detection methodologies, such as static and dynamic analysis, often prove inadequate in identifying deeply embedded malicious behaviors. This study introduces a systematic reverse engineering framework for analysing suspicious Android applications. In contrast to traditional approaches, the proposed methodology consists of six distinct stages: Initialization, decompilation, static analysis, code reversing, behavioral analysis, and reporting. This structured process facilitates a comprehensive examination of an application's internal mechanisms, enabling the identification of concealed malware functionalities. The findings of this study demonstrate that the proposed method attains an overall effectiveness of 84.3%, surpassing conventional static and dynamic analysis techniques. Furthermore, this research generates a detailed list of files containing specific malware indicators, thereby enhancing future malware detection and prevention systems. These results underscore the efficacy of reverse engineering as a critical tool for understanding and mitigating sophisticated Android malware threats.
Improvement of Learning Outcomes Using the Scramble Model with Interactive Video Media Anam, Khoirul; Kusuma, Ridho Surya; Sirajuddin, Suharti; Santosa, Eric
Vocational: Journal of Educational Technology Vol. 2 No. 2 (2025)
Publisher : Yayasan Pendidikan Dan Pengembangan Harapan Ananda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58740/vocational.v2i2.609

Abstract

The integration of active learning strategies with digital media has become increasingly essential in higher education to enhance student learning outcomes. This classroom action research investigated the effectiveness of the Scramble learning model supported by interactive video media in improving student achievement in the English Language Education Department at Universitas Negeri Makassar. The study was conducted in two cycles, each consisting of planning, action, observation, and reflection. A total of 32 undergraduate students participated, selected through purposive sampling. Data collection employed tests, observations, and reflective notes, while data analysis combined descriptive statistics with normalized gain (N-gain) to evaluate improvements in learning outcomes. The findings showed consistent progress across cycles. Average student performance improved significantly from the baseline measurement to the second cycle, demonstrating that the instructional strategy effectively supported knowledge acquisition. Moreover, the integration of Scramble activities with interactive video fostered greater classroom engagement, collaboration, and motivation. Students responded positively to the use of multimedia-based tasks, which provided a more dynamic and student-centered learning environment. The study concludes that the Scramble model, when combined with interactive video media, is a highly effective approach to improving learning outcomes in teacher education courses. Beyond raising academic achievement, this model also contributes to enhancing students’ critical thinking, active participation, and collaborative learning. These findings highlight the potential of technology-enhanced active learning models to address challenges in higher education and provide meaningful benefits for both teaching practice and student development.