• Title/Summary/Keyword: ATO(Air Tasking Order

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Proposal of a framework for evaluating the operational impact of cyber attacks on aviation weapons systems(EOICA) (항공무기체계 사이버공격에 대한 작전영향성평가 프레임워크 제안)

  • Hong, Byoung-jin;Kim, Wan-ju;Lee, Soo-jin;Lim, Jae-sung
    • Convergence Security Journal
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    • v.20 no.4
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    • pp.35-45
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    • 2020
  • Cyber attacks on the aviation weapon system, a state-of-the-art asset, have become a reality and are approaching as a constant threat. However, due to the characteristics of embedded software of the current aviation weapon system, it is managed and operated without connection to the network in peacetime, so the response management to cyber attacks is relatively weak. Therefore, when a cyber attack becomes a reality, it is urgent to prepare and evaluate measures for the adverse effects that such attack will have on the execution of the Air Tasking Order(ATO). In this paper, we propose a framework for operational impact assessment in order to avoid confusion in ATO execution and systematic response to cyber attacks on aviation weapons systems. The proposed framework is designed to minimize the negative impact on operations against cyber attacks that may occur under no warning by analyzing the impact on air operations for each aviation weapon system and standardizing countermeasures for this. In addition, it supports the operational commander to make a quick decision to command for the execution of the operation even in a situation where a cyber attack occurs.

A Study on Methodology for Air Target Dynamic Targeting Applying Machine Learning (기계학습을 활용한 항공표적 긴급표적처리 발전방안 연구)

  • Kang, Junghyun;Yim, Dongsoon;Choi, Bongwan
    • Journal of the Korea Institute of Military Science and Technology
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    • v.22 no.4
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    • pp.555-566
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    • 2019
  • In order to prepare for the future warfare environment, which requires a faster operational tempo, it is necessary to utilize the fourth industrial revolution technology in the field of military operations. This study propose a methodology, 'machine learning based dynamic targeting', which can contribute to reduce required man-hour for dynamic targeting. Specifically, a decision tree algorithm is considered to apply to dynamic targeting process. The algorithm learns target prioritization patterns from JIPTL(Joint Integrated Prioritized Target List) which is the result of the deliberate targeting, and then learned algorithm rapidly(almost real-time) determines priorities for new targets that occur during ATO(Air Tasking Order) execution. An experiment is performed with artificially generated data to demonstrate the applicability of the methodology.

Research on Cyber Kill Chain Models for Offensive Cyber Operations (공세적 사이버 작전을 위한 사이버 킬체인 모델 연구)

  • Seong Bae Jo;Wan Ju Kim;Jae Sung Lim
    • Convergence Security Journal
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    • v.23 no.4
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    • pp.71-80
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    • 2023
  • Cyberspace has emerged as the fifth domain of warfare, alongside land, sea, air, and space. It has become a crucial focus for offensive and defensive military operations. Governments worldwide have demonstrated their intent to engage in offensive cyber operations within this domain. This paper proposes an innovative offensive cyber kill chain model that integrates the existing defensive strategy, the cyber kill chain model, with the joint air tasking order (ATO) mission execution cycle and joint target processing procedure. By combining physical and cyber operations within a joint framework, this model aims to enhance national cyber operations capabilities at a strategic level. The integration of these elements seeks to address the evolving challenges in cyberspace and contribute to more effective jointness in conducting cyber operations.

A Study on the Criteria to Decide the Number of Aircrafts Considering Operational Characteristics (항공기 운용 특성을 고려한 적정 운용 대수 산정 기준 연구)

  • Son, Young-Su;Kim, Seong-Woo;Yoon, Bong-Kyoo
    • Journal of the Korea Institute of Military Science and Technology
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    • v.17 no.1
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    • pp.41-49
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    • 2014
  • In this paper, we consider a method to access the number of aircraft requirement which is a strategic variable in national security. This problem becomes more important considering the F-X and KF-X project in ROKAF. Traditionally, ATO(Air Tasking Order) and fighting power index have been used to evaluate the number of aircrafts required in ROKAF. However, those methods considers static aspect of aircraft requirement. This paper deals with a model to accommodate dynamic feature of aircraft requirement using absorbing Markov chain. In conclusion, we suggest a dynamic model to evaluate the number of aircrafts required with key decision variables such as destroying rate, failure rate and repair rate.