Cyber military strategy for cyberspace superiority in cyber warfare

Eom, Jung-Ho; Kim, Nam-Uk; Kim, Sunghwan; Chung, Tai-Myoung

doi:10.1109/cybersec.2012.6246114

Cited by 23 publications

(10 citation statements)

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“…It consists of 4 modules; Cyber infrastructure list, Cyber targets list, Cyber order of battle, and Pre-CTO(Cyber Tasking Order) [6].…”

Section: Fig 2 Architecture Of Proposed Systemmentioning

confidence: 99%

Architecture of Cyber Intelligence System for Cyber Attack & Defense Training

Seo¹,

Kim²,

Park³

et al. 2016

Advanced Science and Technology Letters

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Abstract. In this paper, we proposed architecture of cyber intelligence system for cyber-attack & defense training. In cyber training, the first process is exactly to acquire the cyber intelligence (data) related to cyber-attack and defense. The proposed cyber intelligence system is an optimized model for providing customized intelligence to trainees, for collecting and analyzing information (data) of cyber environment. When the cyber-attack training is performed, it must accurately identify data related to the target components. When the cyberdefense training is performed, it should be preceded to extract data related to cyber-attacks and detect signs of cyber-attack. The proposed system consists of 5 subsystems to efficiently collect, analyze, and propagate cyber intelligence.

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“…It consists of 4 modules; Cyber infrastructure list, Cyber targets list, Cyber order of battle, and Pre-CTO(Cyber Tasking Order) [6].…”

Section: Fig 2 Architecture Of Proposed Systemmentioning

confidence: 99%

Architecture of Cyber Intelligence System for Cyber Attack & Defense Training

Seo¹,

Kim²,

Park³

et al. 2016

Advanced Science and Technology Letters

Self Cite

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“…Eom, Kim, Kim, and Chung (2012) make the argument for the need for cyber superiority as well as for the development of a "cyber warrior." They contend that the cyber warrior should have thorough knowledge of military policies, cyber strategy, cyber tactics, cyber operations, cyber intelligence collection, as well as cyber attack and cyber defense technology.…”

Section: Cyberspace Damage Controlmentioning

confidence: 99%

Identifying and Embedding Common Indicators of Compromise in Virtual Machines for Lab-Based Incident Response Education

Dusen¹,

Matthew²

2015

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Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)Naval Postgraduate School Monterey, CA 93943-5000 PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING /MONITORING AGENCY NAME(S) AND ADDRESS(ES)N/A SPONSORING / MONITORING AGENCY REPORT NUMBER11. SUPPLEMENTARY NOTES The views expressed in this thesis are those of the author and do not reflect the official policy or position of the Department of Defense or the U.S. Government. IRB Protocol number ____N/A____. 12a. DISTRIBUTION / AVAILABILITY STATEMENTApproved for public release; distribution is unlimited 12b. DISTRIBUTION CODE ABSTRACT (maximum 200 words)Though typical malware delivery vectors, behaviors, and general "attack craft" can be verbally explained and even illustrated, greater familiarity and confidence is imbued in the cyber defender when such theoretical explanations are followed by guided practical exercises that provide realistic scenarios. To demonstrate this, we created seven scenarios utilizing common attack types combined with prominent artifacts for indicators of compromise and prominent incident investigative tools. These scenarios will help facilitate the educational experience for students as well as instill confidence, resulting in more proficient incident response across the field. Should this type of education become a part of the NPS curriculum, additional research can be conducted to reaffirm its true capacity. SUBJECT TERMS

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“…The information needed to make a command order decision is very important factor in achieving superiority in battle. Victory depends on how much of your opponent's data you possess, along with data on the general situation of the friendly side [2,3,4].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Feature Selection Method Based on a Naïve Bayes Algorithm that Enhances the Learning Speed while Maintaining a Similar Error Rate in Cyber ISR

2018

KSII TIIS

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Cyber intelligence, surveillance, and reconnaissance (ISR) has become more important than traditional military ISR. An agent used in cyber ISR resides in an enemy's networks and continually collects valuable information. Thus, this agent should be able to determine what is, and is not, useful in a short amount of time. Moreover, the agent should maintain a classification rate that is high enough to select useful data from the enemy's network. Traditional feature selection algorithms cannot comply with these requirements. Consequently, in this paper, we propose an effective hybrid feature selection method derived from the filter and wrapper methods. We illustrate the design of the proposed model and the experimental results of the performance comparison between the proposed model and the existing model.

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Cyber military strategy for cyberspace superiority in cyber warfare

Cited by 23 publications

References 0 publications

Architecture of Cyber Intelligence System for Cyber Attack & Defense Training

Architecture of Cyber Intelligence System for Cyber Attack & Defense Training

Identifying and Embedding Common Indicators of Compromise in Virtual Machines for Lab-Based Incident Response Education

Hybrid Feature Selection Method Based on a Naïve Bayes Algorithm that Enhances the Learning Speed while Maintaining a Similar Error Rate in Cyber ISR

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