Salza Aulia Fitri, Muhammad Ramadhan, Raffi Ciputra, Ernis Sita Eriana, M.Irham

Detecting Cyber Crime for Forensic Computer Handling using OSINT

Introduction

Detecting cyber crime for forensic computer handling using osint. Detect cybercrime with an OSINT-based expert system for computer forensics. Identify internet violations, laws, and punishments using PHP/MySQL, streamlining live, network, and mobile investigations.

Abstract

In handling computer forensics with backward chaining, the cybercrime detection expert system serves to detect cybercrime crimes committed by criminals. Problems encountered include how to detect cybercrime crimes committed, articles that correspond to cybercrime crimes committed, and what punishment should be given to cybercrime offenders. This article provides a brief explanation of the meaning of forensics, techniques, and applications with various applications available: This expert system uses observation, interviews, and literature studies. into a system that uses hypertext preprocessor programming (PHP) and MySQL database. The design that uses HTML and CSS during the process of making this system can help in the process of detecting and handling internet violations. to supervise the forensic stove, so as to be able to find out with the type of crime committed easily and cyber crime law. The search results show that live forensic, network forensic, and mobile forensic are the most handled crimes, with a trend topic graph above 10. In contrast, computer and database forensics only have two courses.

Review

This paper proposes an expert system utilizing backward chaining to assist in cybercrime detection within computer forensics, aiming to identify specific crimes, relevant legal articles, and appropriate punishments. The overarching goal of developing a system to streamline cybercrime investigation and legal linkage is highly pertinent given the growing complexity of digital offenses. However, the abstract's initial problem statement is somewhat broad, and the subsequent explanation regarding the system's purpose and scope lacks immediate clarity and coherence, making it challenging to grasp the specific scientific contribution beyond a general statement of intent. The integration of "OSINT" from the title is barely touched upon, raising questions about its actual role and depth within the proposed methodology. Methodologically, the abstract mentions the system's reliance on observation, interviews, and literature studies to inform a PHP/MySQL application with HTML/CSS for its front end. While this describes a common web development stack, it provides minimal insight into the "expert system" components, particularly how backward chaining is implemented or how it specifically leverages OSINT for detection. The phrase "supervise the forensic stove" is colloquial and obscures the system's technical functionality, diminishing the abstract's scientific precision. A critical gap is the absence of detail on how OSINT data is gathered, processed, and integrated into the backward chaining rules or knowledge base, which is crucial for a paper with "OSINT" in its title. The "search results" presented in the abstract are particularly perplexing and disconnected from the preceding description of an expert system for crime detection. Statements like "live forensic, network forensic, and mobile forensic are the most handled crimes, with a trend topic graph above 10," and "computer and database forensics only have two courses," are highly ambiguous. It is unclear if these refer to the system's outputs, statistics from a separate study, or even academic offerings. This section severely undermines the abstract's ability to convey scientific findings, as it fails to demonstrate how the proposed expert system contributes to these observations or how these observations validate the system's effectiveness in detecting cybercrimes, identifying articles, or assigning punishments. Greater clarity on the specific functionalities and evaluative metrics of the expert system is essential for any meaningful assessment.

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