• Title/Summary/Keyword: 국방 AI

Search Result 83, Processing Time 0.023 seconds

Study on Trends and Strategies for Defense Blockchain and ICT Technologies (국방 블록체인 기술 동향 및 국방 ICT 융합 전략 연구)

  • Lee, K.Hyu;Park, H.Sook
    • Electronics and Telecommunications Trends
    • /
    • v.35 no.1
    • /
    • pp.12-24
    • /
    • 2020
  • To keep pace with other powerful nations in this era of the era of digitalization and to emerge stronger in the world, the defense forces of South Korea aim to innovate and prepare themselves for digital battlefields of possible wars in the future. The resources in the defense sector, which is the core of defense intelligence, is based on an intelligent mission collaboration tactical network system via cyber, command, control, communication, and computer (C4), and military and non-human weapons. Defense intelligence depends on the degree of the convergence of advanced Information and communication technologies (ICTs). Considering this aspect of defense intelligence, We plan to determine the application status of defense blockchain technology and examine the feasibility of applying blockchain technology and the core of applied technology. Generally, a key feature of blockchain technology is its data integrity in untrusted environments. There are various types of core technologies for the blockchain depending on the target areas of application in the defense sector, and it is also essential to derive new application strategies for core technologies that are applied in combination with other ICT technologies. We plan to demonstrate new defense ICT converged technologies (DNAB2: Data, Network, AI, BigData, Blockchain) and DNAB2-As-Services in the defense strategy.

5G MUM-T Operation System Analysis (5G MUM-T 운용 시스템 분석)

  • Byungwoon Kim
    • Journal of The Korean Institute of Defense Technology
    • /
    • v.5 no.2
    • /
    • pp.10-16
    • /
    • 2023
  • This study establishes the operation concept of the 4th industrial revolution defense technology and communication facility-based 5G MUM-T system, and diagnoses our current situation, focusing on the case of US government technology policy, which is a leading country in 5G MUM-T system and operation. And to advance the operation of the 5G MUM-T system, reflect combat robots and drones in the detailed classification of weapon systems, early introduction of low-orbit 5G satellite communication, expansion of the use of 5G specialized networks and wholesale provision for demonstration and verification, establishment of a defense AI governance system, Suggests the necessity of a 3-class method for radiological weapon systems. For future research, it is important to respond to the technological evolution of 6G MUM-T and 6G NTN and compare and analyze each country's policy cases, such as China, Germany, the United Kingdom, and Japan.

  • PDF

Time-based Expert System Design for Coherent Integration Between M&S and AI (M&S와 AI간의 유기적 통합을 위한 시간기반 전문가 시스템 설계)

  • Shin, Suk-Hoon;Chi, Sung-Do
    • Journal of the Korea Society for Simulation
    • /
    • v.26 no.2
    • /
    • pp.59-65
    • /
    • 2017
  • Along with the development of M&S, modeling research utilizing AI technology is attracting attention because of the fact that the needs of fields including human decision making such as defense M&S are increased. Obviously AI is a way to solve complex problems. However, AI did not consider logical time such as input time and processing time required by M&S. Therefore, in this paper we proposed a "time-based expert system" which redesigned the representative AI technology rule-based expert system. It consists of a rule structure "IF-THEN-AFTER" and an inference engine, takes logical time into consideration. We also tried logical analysis using a simple example. As a result of the analysis, the proposal Time-based Expert System proved that the result changes according to the input time point and inference time.

An Empirical Study on Defense Future Technology in Artificial Intelligence (인공지능 분야 국방 미래기술에 관한 실증연구)

  • Ahn, Jin-Woo;Noh, Sang-Woo;Kim, Tae-Hwan;Yun, Il-Woong
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.21 no.5
    • /
    • pp.409-416
    • /
    • 2020
  • Artificial intelligence, which is in the spotlight as the core driving force of the 4th industrial revolution, is expanding its scope to various industrial fields such as smart factories and autonomous driving with the development of high-performance hardware, big data, data processing technology, learning methods and algorithms. In the field of defense, as the security environment has changed due to decreasing defense budget, reducing military service resources, and universalizing unmanned combat systems, advanced countries are also conducting technical and policy research to incorporate artificial intelligence into their work by including recognition systems, decision support, simplification of the work processes, and efficient resource utilization. For this reason, the importance of technology-driven planning and investigation is also increasing to discover and research potential defense future technologies. In this study, based on the research data that was collected to derive future defense technologies, we analyzed the characteristic evaluation indicators for future technologies in the field of artificial intelligence and conducted empirical studies. The study results confirmed that in the future technologies of the defense AI field, the applicability of the weapon system and the economic ripple effect will show a significant relationship with the prospect.

An Architecture Model on Artificial Intelligence for Ground Tactical Echelons (지상 전술 제대 인공지능 아키텍처 모델)

  • Kim, Jun Sung;Park, Sang Chul
    • Journal of the Korea Institute of Military Science and Technology
    • /
    • v.25 no.5
    • /
    • pp.513-521
    • /
    • 2022
  • This study deals with an AI architecture model for collecting battlefield data using the tactical C4I system. Based on this model, the artificial staff can be utilized in tactical echelon. In the current structure of the Army's tactical C4I system, Servers are operated by brigade level and above and divided into an active and a standby server. In this C4I system structure, the AI server must also be installed in each unit and must be switched when the C4I server is switched. The tactical C4I system operates a server(DB) for each unit, so data matching is partially delayed or some data is not matched in the inter-working process between servers. To solve these issues, this study presents an operation concept so that all of alternate server can be integrated based on virtualization technology, which is used as an source data for AI Meta DB. In doing so, this study can provide criteria for the AI architectural model of the ground tactical echelon.

A Study on the Strategic Application of National Defense Data for the Construction of Smart Forces in the 4th IR (4차 산업혁명시대 스마트 강군 건설을 위한 국방 데이터의 전략적 활용 방안연구)

  • Kim, Seyong;Kim, Junsang;Kang, Seokwon
    • Convergence Security Journal
    • /
    • v.20 no.4
    • /
    • pp.113-123
    • /
    • 2020
  • The fourth industrial revolution can be called the hyper-connected-based intelligent revolution triggered by advanced information technology and intelligent technology, and the basis for implementing these technologies is 'data'. This study proposes a way to strategically use data in order to lead this intelligent revolution in the defense area. First of all, implications through analysis of domestic and international trends and prior research and current status of defense data management were analyzed, and four directions for development were presented. If the government composes conditions for building, releasing, sharing, distribution, and convergence of defense data considering the environment of national defense in the future, it is expected that it will serve as a foundation and a shortcut to be a digitalized strong military through smart defense innovation in the era of the fourth industrial revolution.

Two Circle-based Aircraft Head-on Reinforcement Learning Technique using Curriculum (커리큘럼을 이용한 투서클 기반 항공기 헤드온 공중 교전 강화학습 기법 연구)

  • Insu Hwang;Jungho Bae
    • Journal of the Korea Institute of Military Science and Technology
    • /
    • v.26 no.4
    • /
    • pp.352-360
    • /
    • 2023
  • Recently, AI pilots using reinforcement learning are developing to a level that is more flexible than rule-based methods and can replace human pilots. In this paper, a curriculum was used to help head-on combat with reinforcement learning. It is not easy to learn head-on with a reinforcement learning method without a curriculum, but in this paper, through the two circle-based head-on air combat learning technique, ownship gradually increase the difficulty and become good at head-on combat. On the two-circle, the ATA angle between the ownship and target gradually increased and the AA angle gradually decreased while learning was conducted. By performing reinforcement learning with and w/o curriculum, it was engaged with the rule-based model. And as the win ratio of the curriculum based model increased to close to 100 %, it was confirmed that the performance was superior.

Korean Lip-Reading: Data Construction and Sentence-Level Lip-Reading (한국어 립리딩: 데이터 구축 및 문장수준 립리딩)

  • Sunyoung Cho;Soosung Yoon
    • Journal of the Korea Institute of Military Science and Technology
    • /
    • v.27 no.2
    • /
    • pp.167-176
    • /
    • 2024
  • Lip-reading is the task of inferring the speaker's utterance from silent video based on learning of lip movements. It is very challenging due to the inherent ambiguities present in the lip movement such as different characters that produce the same lip appearances. Recent advances in deep learning models such as Transformer and Temporal Convolutional Network have led to improve the performance of lip-reading. However, most previous works deal with English lip-reading which has limitations in directly applying to Korean lip-reading, and moreover, there is no a large scale Korean lip-reading dataset. In this paper, we introduce the first large-scale Korean lip-reading dataset with more than 120 k utterances collected from TV broadcasts containing news, documentary and drama. We also present a preprocessing method which uniformly extracts a facial region of interest and propose a transformer-based model based on grapheme unit for sentence-level Korean lip-reading. We demonstrate that our dataset and model are appropriate for Korean lip-reading through statistics of the dataset and experimental results.

Modeling and Simulation on One-vs-One Air Combat with Deep Reinforcement Learning (깊은강화학습 기반 1-vs-1 공중전 모델링 및 시뮬레이션)

  • Moon, Il-Chul;Jung, Minjae;Kim, Dongjun
    • Journal of the Korea Society for Simulation
    • /
    • v.29 no.1
    • /
    • pp.39-46
    • /
    • 2020
  • The utilization of artificial intelligence (AI) in the engagement has been a key research topic in the defense field during the last decade. To pursue this utilization, it is imperative to acquire a realistic simulation to train an AI engagement agent with a synthetic, but realistic field. This paper is a case study of training an AI agent to operate with a hardware realism in the air-warfare dog-fighting. Particularly, this paper models the pursuit of an opponent in the dog-fighting setting with a gun-only engagement. In this context, the AI agent requires to make a decision on the pursuit style and intensity. We developed a realistic hardware simulator and trained the agent with a reinforcement learning. Our training shows a success resulting in a lead pursuit with a decreased engagement time and a high reward.

The study of Defense Artificial Intelligence and Block-chain Convergence (국방분야 인공지능과 블록체인 융합방안 연구)

  • Kim, Seyong;Kwon, Hyukjin;Choi, Minwoo
    • Journal of Internet Computing and Services
    • /
    • v.21 no.2
    • /
    • pp.81-90
    • /
    • 2020
  • The purpose of this study is to study how to apply block-chain technology to prevent data forgery and alteration in the defense sector of AI(Artificial intelligence). AI is a technology for predicting big data by clustering or classifying it by applying various machine learning methodologies, and military powers including the U.S. have reached the completion stage of technology. If data-based AI's data forgery and modulation occurs, the processing process of the data, even if it is perfect, could be the biggest enemy risk factor, and the falsification and modification of the data can be too easy in the form of hacking. Unexpected attacks could occur if data used by weaponized AI is hacked and manipulated by North Korea. Therefore, a technology that prevents data from being falsified and altered is essential for the use of AI. It is expected that data forgery prevention will solve the problem by applying block-chain, a technology that does not damage data, unless more than half of the connected computers agree, even if a single computer is hacked by a distributed storage of encrypted data as a function of seawater.