Mô hình hóa luật hình sự việt nam

ĐẠI HỌC QUỐC GIA TP.HCM TRƯỜNG ĐẠI HỌC BÁCH KHOA ———————————– ĐÀO QUỐC TUẤN MƠ HÌNH HỐ LUẬT HÌNH SỰ VIỆT NAM Chuyên ngành: Khoa Học Máy Tính Mã số: 8.48.01.01 LUẬN VĂN THẠC SĨ TP HỒ CHÍ MINH, tháng 02 năm 2023 CƠNG TRÌNH ĐƯỢC HỒN THÀNH TẠI TRƯỜNG ĐẠI HỌC BÁCH KHOA ĐHQG-HCM Cán hướng dẫn khoa học 1: PGS TS Đặng Trần Khánh Cán hướng dẫn khoa học 2: PGS TS Lê Hồng Trang Cán chấm nhận xét 1: TS Đặng Trần Trí Cán chấm nhận xét 2: PGS.TS Nguyễn Tuấn Đăng Luận văn thạc sĩ bảo vệ Trường Đại học Bách Khoa, ĐHQG Tp HCM ngày 07 tháng 02 năm 2023 Thành phần Hội đồng đánh giá luận văn thạc sĩ gồm: Chủ Tịch: PGS.TS Trần Minh Quang Thư Ký: TS Phan Trọng Nhân GV Phản Biện 1: TS Đặng Trần Trí GV Phản Biện 2: PGS.TS Nguyễn Tuấn Đăng Ủy Viên: TS Nguyễn Thị Ái Thảo Xác nhận Chủ tịch Hội đồng đánh giá LV Trưởng Khoa quản lý chuyên ngành sau luận văn sửa chữa (nếu có) CHỦ TỊCH HỘI ĐỒNG TRƯỞNG KHOA KHOA HỌC VÀ KỸ THUẬT MÁY TÍNH ĐẠI HỌC QUỐC GIA TP.HCM TRƯỜNG ĐẠI HỌC BÁCH KHOA CỘNG HÒA XÃ HỘI CHỦ NGHĨA VIỆT NAM Độc lập - Tự - Hạnh phúc NHIỆM VỤ LUẬN VĂN THẠC SĨ Họ tên học viên: Đào Quốc Tuấn MSHV: 1970598 Ngày, tháng, năm sinh: 21/09/1983 Nơi sinh: TP.HCM Chuyên ngành: Khoa Học Máy Tính Mã số : 8480101 I TÊN ĐỀ TÀI: - Mơ hình hóa luật hình Việt Nam / Modelling the Vietnam Criminal Code II NHIỆM VỤ VÀ NỘI DUNG: - Tìm hiểu luật hình Việt Nam - Đề xuất phương pháp xây dựng mơ hình dựa vào thể sở thể luật cho đặc trưng luật Việt Nam - Tìm hiểu kỹ thuật để áp dụng vào phương pháp đề xuất thực dựa luật hình Việt Nam 2015, luật sửa đổi bổ sung 2017 III NGÀY GIAO NHIỆM VỤ : 20/01/2022 IV NGÀY HOÀN THÀNH NHIỆM VỤ: 07/02/2023 V CÁN BỘ HƯỚNG DẪN: PGS TS Đặng Trần Khánh, PGS TS Lê Hồng Trang Tp HCM, ngày tháng năm 2023 CÁN BỘ HƯỚNG DẪN I (Họ tên chữ ký) PGS TS Đặng Trần Khánh CÁN BỘ HƯỚNG DẪN II (Họ tên chữ ký) HỘI ĐỒNG NGÀNH (Họ tên chữ ký) PGS TS Lê Hồng Trang TRƯỞNG KHOA KHOA HỌC VÀ KỸ THUẬT MÁY TÍNH (Họ tên chữ ký) Lời cám ơn Đầu tiên, tơi xin bày tỏ lịng biết ơn sâu sắc tới PGS TS Đặng Trần Khánh, người hướng dẫn tơi suốt q trình thực luận văn đề cương Nhờ có hướng dẫn góp ý thầy hỗ trợ tơi thực nghiên cứu mình, hồn thành tốt luận văn báo cáo hội nghị IMCOM 2023 Thầy cho tơi nhiều ý kiến đóng góp hữu ích tạo hội để tham dự số hội nghị, hội thảo tạo điều kiện cho tơi tham gia đóng góp vào dự án cấp Bộ hợp tác với trường Đại Học Luật Thành Phố Hồ Chí Minh để tạo kết nối với chuyên gia pháp lý hỗ trợ cho nghiên cứu Xin gửi lời cảm ơn chân thành đến PGS TS Nguyễn Thị Phương Hoa - Trưởng khoa Luật Hình Sự - Đại Học Luật Thành Phố Hồ Chí Minh hỗ trợ, tư vần kiến thức chuyên ngành Luật góp ý, đánh giá kết nghiên cứu mà thực Xin cảm ơn thầy đồng hướng dẫn luận văn tôi, PGS TS Lê Hồng Trang hỗ trợ thầy q trình nghiên cứu tơi Bên cạnh đó, tơi xin gửi lời cảm ơn đến quý thầy cô khoa Khoa học Kỹ thuật máy tính truyền thụ kiến thức, kinh nghiệm quý báu cho hai năm qua Cuối cùng, xin gửi lời cảm ơn chân thành đến gia đình bạn bè, người ln động viên, ủng hộ suốt thời gian học cao học Thành phố Hồ Chí Minh, 02/2023 Đào Quốc Tuấn i Tóm tắt Mục đích đề tài nghiên cứu đề xuất phương pháp để mơ hình hóa luật hình Việt Nam nhằm để phục vụ cho hệ thống hỗ trợ định pháp luật hệ thống lập luận pháp lý Phương pháp để xuất sử dụng thể học (Ontology) xây dựng dựa vào ngôn ngữ OWL-DL trích xuất từ luật hình Việt Nam Các mối quan hệ luận lý định nghĩa dạng luật ngôn ngữ SWRL Trong thực tế, việc xây dựng Ontology lĩnh vực pháp luật nhiệm vụ khó khăn phức tạp tính chất riêng biệt ngành luật Luận văn tiếp cận chiến lược phân tích từ trung tâm (middle-out) Đây phương pháp kết hợp từ hai chiến lược phổ thơng là: phân tích trừ xuống (top-down) chiến lược phân tích từ lên (bottom-up) Ontology sau xây dựng trở thành thành phần hệ thống lý luận pháp lý Đây hệ thống thơng minh có khả đưa phân tích, đánh giá, kiểm tra hành vi có yếu tố pháp lý Hệ thống công cụ hỗ trợ đắc lực cho chuyên gia pháp luật, chuyên gia lập pháp phủ thời đại cơng nghiệp 4.0 kéo theo phát triển nhanh chóng mạnh mẽ tội phạm công nghệ cao hành vi xuất thời đại Hỗ trợ kịp thời cho phủ nhanh chóng kiểm tra đánh giá luật tình hình kinh tế xã hội ngày Phương pháp xây dựng dựa vào tảng đặc trưng luật hình Việt Nam, bên cạnh nghiên cứu luận văn hy vọng áp dụng mở rộng luật khác Việt Nam luật giới tương lai ii Abstract The main purpose of this thesis is to develop a method to model the criminal code of the Vietnamese Assembly by its essence to serve a legal reasoningable expert system Ontology incorporates a hierarchical structure and supports logical reasoning, which can reduce semantic ambiguities and extract implied semantic information The ontology is based on Description Logics Semantic Web Ontology Language (OWL-DL) extracted from the Vietnamese Penal Code Logical relationships will be defined as rules in the Semantic Web Rule Language (SWRL) language In fact, building well-founded legal domain ontologies is considered a difficult and complex process due to the complexity of the legal domain This study approaches the middle-out strategy It is composed of two complementary strategies: top-down and bottom-up Moreover, the model will be used as a component in a legal reasoning-able expert system The reasoningable system is a smart system that is able to provide critical analytical, and evaluation for checking and evaluating an act whether it is legitimate The system also supported the purposes of legal reasoning and law-making in the Fourth Industrial Revolution which causes the rapid development of quantity and quality high-tech crime, and new criminal minds All are being analyzed and built on the basis of Vietnam Law characteristics, but also expected to be able to apply in other countries in the World iii Lời cam đoan Tôi Đào Quốc Tuấn học viên cao học khoa Khoa Học Kỹ Thuật Máy Tính, Đại học Bách Khoa TP HCM, MSHV 1970598 Tôi xin cam đoan luận văn thạc sĩ "Mơ hình hố luật hình Việt Nam" kết tìm hiểu, nghiên cứu độc lập thân Tơi xin cam đoan: Luận văn thực cho mục đích tìm hiểu nghiên cứu bậc cao học Các cơng trình, báo tham khảo để xây dựng nên luận văn trích dẫn, tham khảo Tất tài liệu trích dẫn có tính kế thừa từ tạp chí cơng trình nghiên cứu cơng bố Những cơng cụ, phần mềm cho trình thực luận văn phần mềm mã nguồn mở Hình ảnh số liệu trích dẫn nguồn tham khảo rõ ràng Kết nghiên cứu trình bày trung thực dựa xem xét đánh giá chuyên gia ngành luật TP Hồ Chí Minh, Ngày 07 Tháng 02 Năm 2023 Học viên Đào Quốc Tuấn iv Mục lục Giới thiệu 1.1 Mở đầu 1.2 Bố cục luận văn 1 2 Cơ sở lý thuyết 2.1 Tổng quan tội phạm thời đại công nghiệp 4.0 2.2 Tội phạm công nghệ cao 2.2.1 Phishing Attack 2.2.2 Dolphin Attack 2.2.3 Tấn công lỗ hổng bảo mật hệ thống 2.2.4 Trojan Attack 2.2.5 Man-in-the-Middle (MitM) Attacks 2.2.6 Tấn công từ chối dịch vụ phân tán (Distributed Denial-Of-Service Attack) 2.2.7 Ransomware 2.2.8 Tuyên truyền, phổ biến nội dung vi phạm pháp luật không gian internet 2.2.9 Xâm phạm thông tin riêng tư 2.2.10 Deepfakes 2.2.11 Robot 2.2.12 Blockchain hợp đồng thông minh 2.3 Khái quát hệ thống pháp luật Việt Nam 2.3.1 Nguồn gốc đặc điểm luật pháp Việt Nam 2.3.2 So sánh với hệ thống luật pháp khác Thế Giới 2.4 Ontology 2.4.1 Khái niệm Ontology 2.4.2 Phân loại 2.4.3 Tiêu chí Ontology 2.4.4 Các thành phần Ontology 2.4.5 Vai trò ứng dụng Ontology ngành luật 2.4.6 Các Ontology lĩnh vực pháp luật 2.5 Các phương pháp luận để xây dựng Ontology 4 5 10 11 v 12 14 16 17 18 21 24 26 26 28 28 28 31 33 34 36 38 45 MỤC LỤC 2.5.1 Uschold 2.5.2 Phương pháp tiếp cận có hệ thống để xây dựng ontology (SABiO) Các công cụ môi trường để xây dựng Ontology 2.6.1 Protégé 2.6.2 OntoUML Lightweight Editor (OLED) Các ngơn ngữ hình thức 2.7.1 RDF RDF Schema 2.7.2 OWL 2.7.3 Description Logics (DL) 2.7.4 SWRL Các quy trình để xây dựng Ontology 2.8.1 Học Ontology 2.8.2 Sử dụng lại Ontology 2.8.3 Module hoá Ontology 2.8.4 Đánh giá Ontology Hệ thống dựa sở tập luật pháp luật 2.9.1 Đánh giá hệ thống dựa sở tập luật 2.9.2 Các phương pháp xây dựng tập luật 45 47 49 49 50 50 51 51 52 55 56 56 58 59 60 64 65 66 Các hướng tiếp cận cơng trình liên quan 3.1 Bài nghiên cứu - Mơ hình hố luật để dự đốn tìm kiếm [1] 3.2 Bài nghiên cứu - AutoLAW : Hệ thống suy luận dựa dự đoán án lệ [2] 3.3 Bài nghiên cứu - CRIKE: Hệ thống khai phá trích xuất liệu văn luật [3] 3.4 Bài nghiên cứu - CLCS: Hệ thống tư vấn pháp luật Trung Quốc dựa vào Ontology [4] 3.5 Bài nghiên cứu - Mơ hình hố Luật hình Hàn Quốc Ontology [5] 3.6 Bài nghiên cứu - Suy luận văn luật Malawi học máy [6] 69 69 2.6 2.7 2.8 2.9 Phương pháp đề xuất 4.1 Phân tích đặc điểm luật 4.2 Mơ hình hóa luật dựa vào ontology 4.2.1 Xác định nguồn liệu 4.2.2 Xây dựng Ontology module 4.2.3 Từ xuống: Mơ hình hóa khái niệm tái sử dụng 4.2.4 Từ lên: Quá trình học Ontology 4.2.5 Module Ontology Cấp Cao (UO) 4.2.6 Module Ontology Lõi (CO) 4.2.7 Module Ontology Miền (DO) 4.2.8 Tích hợp module 4.2.9 Đánh giá 4.3 Xây dựng tập luật SWRL 4.4 Mơ hình khơng gian khái niệm (Conceptual Spaces Model) vi 71 72 74 76 77 80 80 81 82 83 84 84 89 92 98 98 101 102 102 MỤC LỤC 4.5 Kết 5.1 5.2 5.3 4.4.1 Mơ hình khơng gian khái niệm ngữ Hệ chuyên gia pháp lý Việt Nam (VNLES) 4.5.1 Kiến trúc hệ thống 4.5.2 Thảo luận cảnh luật 104 107 107 111 luận Các kết đạt Những hạn chế Hướng nghiên cứu 114 114 115 116 Danh mục cơng trình khoa học 118 Tài liệu tham khảo 146 vii The 17th International Conference on Ubiquitous Information Management and Communication Table of Content | 10:30-10:55, Thursday, January 05, 2023 | Online Presentation 4: Social Interaction 10:30-10:55, Thursday, January 05, 2023 P4-1 Room: Whova Multi-Objective Information Maximization in a Social Network Kundan Kandhway (Indian Institute of Science Education and Research Bhopal, India) When social networks meet payment: a security perspective P4-2 P4-3 P4-4 P4-5 Nivedita Singh (Sungkyunkwan University, Korea), Mohsen Ali Alawami (Sungkyunkwan University, Korea), Hyoungshick Kim (Sungkyunkwan University, Korea) Maximizing Spread of a Message in the Susceptible-Infected-Recovered Process Kundan Kandhway (Indian Institute of Science Education and Research Bhopal, India) The Effect of Inclusive Design on Easy Accessibility for Disabled E-Commerce Users in Indonesia Chindy Jessika Trielsa (Bina Nusantara University, Indonesia), Mia Angeline (Bina Nusantara University, Indonesia) Ramadan Spirit: A Digital Game Incorporating Malaysian Culture to Teach Malaysian Muslim Children the Islamic Essence of Ramadan Suhaili Din (Universiti Kuala Lumpur, Malaysia), Maisarah Mohd Ramli (Universiti Kuala Lumpur, Malaysia) Assistive Technology for Children with Learning Disabilities: A Systematic Literature Review P4-6 Ahmad Haiqal Abd Khalid (International Islamic University, Malaysia), Nur Nazihah Mohkhlas (International Islamic University, Malaysia), Noor Azura Zakaria (International Islamic University, Malaysia), Mazidah Mat Rejab (Universiti Tun Hussien Onn Malaysia, Malaysia), Ruwinah Abdul Karim (Penawar Special Learning Centre, Malaysia), Suharsiwi (Universitas Muhammadiyah Jakarta, Indonesia) Cultivating Social Media Utilization by Television Stations: An Analysis of Instagram Practices in Czech Republic P4-7 Daniel Messele Balcha (Czech Life Science University, Czech Republic), Irmawan Rahyadi (Binus University, Indonesia), Ayu Agung Mirah Krisnawati (Binus University, Indonesia), Rifa Bestari (Binus University, Indonesia) Pedatren: Educational Administration Applications for Simplifying Paiton Probolinggo’s Nurul Jadid Islamic Boarding School’s Management P4-8 Gamal Kusuma Zamahsari (Binus University, Indonesia), Agus Purnomo AP (IAIN Madura, Indonesia), Agus Purnomo AP (IAIN Madura, Indonesia), Agik Nur Efendi (IAIN Madura, Indonesia), Moh Hafid Effendy (IAIN Madura, Indonesia), Ika Cahya Adiebia (IAIN Madura, Indonesia) An Evaluation of Smartwatch Contribution in Improving Human Health P4-9 Kok Yin Long (Asia Pacific University of Technology & Innovation, Malaysia), Kamalanathan Shanmugam (Asia Pacific University of Technology & Innovation, Malaysia), Muhammad Ehsan Rana (Asia Pacific University of Technology & Innovation, Malaysia) The Effect of Portable Laboratory Integrated with Local Wisdom (PL-ILW) for Physics Learning P4-10 Rudi Susanto (Universiti Kuala Lumpur, Malaysia), Mohd Nizam Husen (Universiti Kuala Lumpur, Malaysia), Adidah Lajis (Universiti Kuala Lumpur, Malaysia), Space from Line: What can Metaverse Support in Education/Learning Activity? P4-11 Toyohide Watanabe (Nagoya Industrial Science Research Institute, Japan) 13 http://www.IMCOM.org VNLES: A Reasoning-enable Legal Expert System using Ontology Modeling-based Method: A Case Study of Vietnam Criminal Code Quoc Tuan Dao1 , Tran Khanh Dang2 * , Thi Phuong Hoa Nguyen3 , Thi Minh Chau Le4 Ho Chi Minh City University of Technology, VNU-HCM, Vietnam Ho Chi Minh City University of Food Industry, Vietnam Ho Chi Minh City University of Law, Vietnam Ho Chi Minh City University of Technology and Education, Vietnam daoquoctuan@gmail.com, khanh@hufi.edu.vn, ntphoa@hcmulaw.edu.vn, chaultm@hcmute.edu.vn Abstract—The main purpose of this research is to develop a method to model the criminal code by its essence to serve a legal reasoning-enable expert system Ontology combines a hierarchical structure and logical reasoning, that can mitigate semantic equivocation and produce the figured semantic information The ontology is based on Description Logics Semantic Web Ontology Language (OWL-DL) extracted from the Vietnamese Penal Code Logical relationships will be defined as rules in the Semantic Web Rule Language (SWRL) language The fact that legal domain is very complicated, so the construction of solid legal domain ontologies is acknowledged as a difficult and complex process This study approaches the strategy named middle-out, which is composed of two interrelated strategies: top-down and bottomup Moreover, the model will be used as a component in a legal reasoning-enable expert system The reasoning-enable system is a smart system that can provide critical analytical, and evaluation for checking and evaluating an act and whether is legitimate The system also supported the purposes of legal reasoning and law-making in the Fourth Industrial Revolution which caused the rapid development of quantity and quality high-tech crime, and new criminal minds All are being analyzed, built, and evaluated based on Vietnam Law characteristics, but also expected to be able to apply in other countries Index Terms—legal ontology, automation legal, SWRL rules, rule modeling, OWL-DL, reasoning, cyber security, and high-tech crime I I NTRODUCTION Law is a major with distinct characteristics and takes a crucial role in society The fast-growing up application of Artificial Intelligence (AI) in many fields of society, causes an urgent demand for the application of AI in the legal field Some characteristics of the legal field include confidentiality of the case information, various kinds of legal sources with different structures, complexity, and conflict of the rules There are vast numbers of documents related to legal every year in Vietnam which are included the conclusion of cases, precedents, resolutions, decrees, and circulars So that requires an efficient tool for legal experts to search and compare rules * Corresponding author 978-1-6654-5348-6/23/$31.00 ©2023 IEEE by using machine learning within data-driven applications for legal reasoning systems and legal consulting systems Various studies on this topic approach some methods: Legal information generalization, semantic web technology, legal ontology, and rule designs This study proposes a suitable method to build the legal ontology base on the characteristic of the legal system in Vietnam The data will be used in the Vietnam criminal code specifically applied and validate in Chapter XIV Offenses against the person and reputation - article 123 Murder This assignment also proposes a legal expert system named VNLES, which helps legal experts quickly validate the model designed by ontology engineers and support legal reasoning for their decision Overall, this study has three main contributions as follows: • • • A method to model legal documents A solution to build a reasoning-enable legal expert system A case study working on the Criminal Code of Vietnam The remaining of this paper is organized as follows: Section II introduces related work on legal ontology Section III presents the characteristics of the Vietnamese legal system and criminal code, together with a brief comparison between Vietnam law and other countries Section IV proposes the methodology to design and build ontology by inheriting from the related studies with the customization and improvement to be suitable for Vietnam criminal law The VNLES is presented in Section V Finally, the concluding remarks and future work are presented in Section VI II R ELATED W ORK Currently, there are various studies related to modeling legal on different approaches which are related to logical rules and ontology, some recent studies use the semantic web in addition Gordon’s study presented the syntax of the Legal Knowledge Interchange Format (LKIF) rule language and argumentation-theoretic semantics in the ESTRELLA European project [6] LKIF builds on and uses the Web Ontology Language (OWL) for representing concepts and includes a reusable basic ontology of legal concepts The core of LKIF consists of a combination of OWL-DL and SWRL LKIF was designed with two main roles in mind: the translation of legal knowledge bases written in different representation formats and formalisms and to be a knowledge representation formalism that could be part of larger architectures for developing legal knowledge systems There are several studies about ontology and legal reasoning systems coming from China [8], Korea [7], Lebanon [5], Tunisia [9], Malawi [10] etc Each of them proposes some idea to improve the building’s automated legal reasoning besides solving problems of the local issue when applied to the specific local law system Table I is a summary table of all similar studies in this subject with different methodologies and functions TABLE I S UMMARY TABLE OF OTHER STUDIES Paper China [8] Korea [7] Lebanon [5] Tunisia [9] Malawi [10] Vietnam Rules ✓ ✓ ✓ Ontology ✓ ✓ ✓ ✓ ✓ Reasoning-able ✓ Multi Docs ✓ ✓ ✓ ✓ III L EGAL S YSTEMS AND P ENAL C ODE IN V IETNAM A The Differences between Vietnamese Legal System and Other Countries Vietnamese legal system belongs to the legal family of Socialism [1] Similar to Asian Socialism countries such as the People’s Republic of China and the Democratic People’s Republic of North Korea Because of that, the system has some characteristics such as it is associated with the ideology of Karl Mark and Lenin This is the latest legal system compared with other legal systems Although this is a legal system that is heavily influenced by the continental legal system of Europe, especially civil law institutions, this legal system does not divide into public and judicial This system respects the written law and has no tradition of using precedents Table II is the hierarchy and the law document types which can be issued by each Unit in Vietnam Government On the other hand, legal systems around the world generally fall into one of two main categories: continental law (civil law) and common law systems The differences between the two systems are the codification, procedure, and role of the jurists [2] Recently, precedents are becoming more popular and important in the continental law system, and the difference gap between the legal systems is getting closer B Vietnamese Criminal Code The Criminal Code is meant to protect Vietnam’s sovereignty and security; protect the socialist regime, human rights, and citizenship rights; protect the equality among ethnic groups; protect the interests of the State; organize and protect the law; punish crimes; raise people’s awareness of compliance with the law; prevent and fight crimes [3] The Vietnam Criminal Code (Penal Code) 2015, amended and supplemented in 2017 includes 426 articles which are structured into three parts: The first part is General Provisions, the second part is Crimes, and the third part is Enforcement Terms The general provisions and the crimes are the main content of the Penal Code with chapter structure In particular, the general regulations section includes 12 chapters, while the crime section includes 14 chapters The general provisions section includes laws regulating crimes, criminal liability, and penalties It is divided into 12 issues into 12 chapters The crimes section includes the laws governing each specific crime and the penalties applicable to those crimes The crimes in the Penal Code are grouped by chapters, structured in the order of chapters-articles-points There are 14 chapters in this section, with chapters following an order: namely chapters-sectionsarticles-points Besides 318 articles in the crime section, laws deal with the general issues of the criminal group in the chapter (articles 122, 352, 367, 392); the remaining laws are all about each crime group specific crimes and the possible penalties for those crimes IV A M ETHODOLOGY OF C RIMINAL L AW O NTOLOGY A Criminal Law Ontology Overview Generally, most of the studies in the major use a similar structure to legal ontology The structure includes the common sector and domain sector The common sector includes Upper Ontology and Legal Core Ontology connected with the domain sector includes domain ontology and domainspecific ontology The middle-out approach is composed of two complementary strategies top-down and bottom-up where the criminal domain ontology is modularized into four independent modules which are themselves ontologies: upper, core, domain, and domain-specific [5] (see Fig.1) According to the property of the Vietnamese law system, the customized ontology structure is proposed There are also two sectors which are the foundation sector and the domain sector Within the foundation sector, it will contain the Legal Core Ontology inherited by LKIF Core and the expert sector will contain the Domain Ontology and Domain Specific Ontology which are produced by analyzing and learning from the law documents; in this paper, it is the Vietnamese Penal Code B Criminal Law Fundamental and Judgment Rules To design a judgment rule, legal experts and ontologists need to work together A legal expert will explain the fundamentals and the meaning of the law while the ontologists will convert that information to become a rule in the ontology Fig.2 shows a fundamental diagram of most of the Criminal cases after working with legal experts to overview the whole Vietnam Penal Code This is a base to build the specificdomain ontology, and it also helps to define each rule inside the code Fig.3 and show the legal codes for Murder in the United States and Vietnam The biggest difference between them is TABLE II H IERACHY OF V IETNAMESE L EGAL D OCUMENT S YSTEM Issuing Unit National Assembly National Assembly Standing Committee of the National Assembly President Government Prime Minister Supreme People’s Court Document Type Constitution Code, Law, Resolution Ordinance, Resolution, Joint Resolution Order, Decision Decree, Joint Resolution Decision Circular, Precedent Fig Structure of the Legal Ontology Fig A Criminal Law Case in Vietnam overview diagram the level of detail of each rule The United States Code seems to build generic information about each type of murder They only mention the offence action but not care about the circumstances whereas the Vietnam code defines very details about circumstances that belong with reality and offence action That’s why leads to the second difference are that the Vietnam Code can define the exact punishment time for each rule whereas United States Code only uses a generic punishment which is punished by death or by imprisonment for life Those differences will cause an advantage in defining rules in Vietnam law when the law is designed to define as cases and rules definition while the United States Code is easier for ontology design when it tends to be category definition In the legal domain, a legal norm is represented by an obligation rule that denotes that the rule’s conclusion will be treated as an obligation Representing legal contents through obligation rules have the conditional form: IF condition (operative facts) THEN conclusion (legal effect) Some examples of murder actions in Fig can be described using SWRL expression See the Fig.4, in the first example a), the rule points to the nature and damage specifically Quantification Next, the second example b) mentions the rule specific to the Individual Record of the victim The last one m) is the condition of the offence In short, each crime has different causes leading to different damages and the final punishment decision of the case These causes can come from external influences or the inside of the perpetrator The legal expert system needs to solve the problem by using some strategies: deductive logic and inductive logic or data-driven and goal-driven Deductive logic initiates from existing facts and then uses rules to emanate all possible facts, while inductive reasoning begins with the expected judgment and processes backward to find supporting facts [5] V VNLES: A R EASONING - ENABLE L EGAL E XPERT S YSTEM A VNLES Architecture After overviewing the big picture of the legal system, it is easy to see the complexity of regulations today For this reason, automated support for legal reasoning is becoming increasingly necessary The system should have to support both sides: legal experts and ontology engineers to easier create and validate the resulting outcome We propose a legal expert system named Vietnam Legal Expert System VNLES targeted mainly to take profit from the value of ontology characteristics to build a reasoning-able legal expert system The system is designed on the background of the legal domain ontology integration and a set of rules that use logic rule language named SWRL The system includes parts: the user interface, the NLP Core, the Legal Expert Core, and the Knowledge Core (see Fig.5) 1) User Interface: In VNLES, the interface is the layer built on the ontology-based interface for the user to communicate with the expert system It provides a control that helps the user enter facts or queries, which are also the input source to the legal expert core Moreover, the reasoning result after processing is completed also shown on the interface (see Fig.6) 2) NLP Core: NLP Core reuses the VnCoreNLP which is a fast and accurate NLP annotation pipeline for Vietnamese, providing rich linguistic annotations through key NLP components of word segmentation, POS tagging, named entity recognition (NER), and dependency parsing [21] This is the core helping us analyze and break down all NLP components of a word segmentation then we can extract those data and put them into the legal expert core (see Fig.6) 3) Legal Expert Core: The core consists of algorithms for exploiting the knowledge represented in the knowledge base (see Fig.6) It uses the cleaned data transferred from NLP Core and applies the logic contained in the knowledge base to the information input by the user and outputs advice Expert core links The SWRL rules and the ontology facts and processes them to reach an output solution 4) Knowledge Core: Generally, the Knowledge Core contains a completed ontology segment: the foundation and domain sectors On the other hand, this core also has knowledge defined as a set of rules Each rule stipulates a relationship, recommendation, order, procedure, or heuristic and has a conditional structure (IF condition-THEN action) When the IF is satisfied, the THEN will be executed (see Fig.6) The following steps have consisted of the reasoning procedure (see Fig.6): • Receive the input data from the user • Analyze and extract input data (legal documents) from NLP Core • Using the cleaned data select the applicable rules • Match the facts in the Knowledge Core from the Ontology base • Decide the rules to be applied and selected • Execute the matched rule • Legal expert core continues to repeat the reasoning process in a loop through all the rules and facts until there is no more conclusion • Return the legal arguments B Discussion: Towards A Smarter VNLES VNLES is anticipated as a smarter legal expert system It will be used by first-regular users such as people who have a demand to check the licit of their actions Second is legal experts such as lawyers, judges, magistrates, jury members, and lawmakers Besides the demand for the validation of the case that happened which is matched with any firm in law documents such as Code, Precedent, Circular, Decree, etc, the lawmakers need to know how it matches, any conflict or loopholes in the current law Some predictions of the new Fig United States murder article Fig Vietnamese murder article TABLE III T HE SWRL RULE EXAMPLES FOR MURDER ONTOLOGY A murderer in any of the cases below shall face a penalty of 12 - 20 years’ imprisonment, life imprisonment, or death: a) Murder of 02 or more people; Criminal Of f ence(murder) ∧ committed towards(murder, ?y) ∧ committed towards(murder, ?z) ∧ committed by(murder, ?x) − → is punished by(?x, death) ∧ is punished by(?x, lif e imprisonment) ∧ is punished by(?x, imprisonment)∧ imposed f or maximum(imprisonment, max) ∧ imposed f or minimum(imprisonment, min) ∧ term value(max, 20)∧ term value(min, 12) ∧ term type(max, ”years”) ∧ term type(min, ”year”) b) Murder of a person aged under 16; Criminal Of f ence(murder) ∧ committed towards(murder, ?y) ∧ Age(?y, ?age)∧?age < 16 ∧ committed by(murder, ?x) − → is punished by(?x, death) ∧ is punished by(?x, lif e imprisonment) ∧ is punished by(?x, imprisonment)∧ imposed f or maximum(imprisonment, max) ∧ imposed f or minimum(imprisonment, min) ∧ term value(max, 20)∧ term value(min, 12) ∧ term type(max, ”years”) ∧ term type(min, ”year”) m) Contract killing; Criminal Of f ence(murder) ∧ committed towards(murder, ?y) ∧ Of f ence Condition(contract) ∧ ordered by(contract, ?z)∧ committed by(murder, ?x) − → is punished by(?x, death) ∧ is punished by(?x, lif e imprisonment)∧ is punished by(?x, imprisonment) ∧ imposed f or maximum(imprisonment, max), imposed f or minimum(imprisonment, min) ∧ term value(max, 20)∧ term value(min, 12) ∧ term type(max, ”years”) ∧ term type(min, ”year”) Fig VNLES Model Fig VNLES Reasoning process type of criminal in the future and need to check if that case still works with the current law The system can suggest adjustment advice to legal experts or create new laws that prevent criminal acts in advance For instance, stories about Artificial Intelligent (AI) and Robotics applications in normal life are viral nowadays Many studies are about the problem of who should take responsibility for the damage from AI and Robotics Robotics and AI-based applications (RAI) are often said to be so technologically advanced that they should be held responsible for their actions, instead of the human who designs or operates them [24] In this situation, the lawmakers can use some case studies input into VNLES, get the output records and examine them to see how the law covers them VI C ONCLUSION AND F UTURE W ORK This paper has presented the Ontology design methodology and built a set of rules to support the legal expert system The method is applied specifically to Vietnam Criminal Code It is built based on previous studies of other countries in the World by applying a middle-out strategy combined with top-down and bottom-up to analyze laws and model them as ontology We also provide the general diagram of criminal law cases in Vietnam law, which can help an ontologist easier to identify, analyze and categorize the ontology or decision rules A particular case study is used in this paper that applies the presented methodology in the Vietnam murder article to construct the SWRL rules for the Knowledge Core in the VNLES We also introduce the VNLES, which is a legal reasoning-able expert system It is a smart system to support people checking and validating the licit of action On the other hand, the system also supports experts in legal arguments or legal reasoning not only the case already defined in law but also the cases that are outside the law In future works, the domain sector which includes domain ontology and specificdomain ontology will be extended by adding other laws such as Labor Law, Enterprise Law, etc It also supports many law document types such as Precedent, Decree, Constitution, Resolution, etc Furthermore, the methodology should be checked and supported on all codes around the World Based on that the VNLES can be developed by using AI to develop to support more features such as multiple codes, and multi-language VNLES is also expected to have automatic construction of ontology design, and judgment rules that will be more helpful to the experts because they can exclude the ontologist engineer when they create or adjust the Knowledge Core Currently, the legal major is very sensitive and has a high impact on humans and society Automation judges still an argument between legal experts and the government So that all the ontology and output result validation is done manually by legal experts and the system just takes the role of a consultant system 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