Attack Graphs and Scenario Driven Wireless Computer Network Defense

2013 ◽  
pp. 774-791
Author(s):  
Peter J. Hawrylak ◽  
George Louthan ◽  
Jeremy Daily ◽  
John Hal ◽  
Mauricio Papa
Keyword(s):  
Radio Frequency Identification ◽  
Computer Network ◽  
Security Vulnerabilities ◽  
Attack Graphs ◽  
Network Defense ◽  
Embedded Computer ◽  
The Usa ◽  
Vehicle Networks ◽  
Frequency Identification ◽  
Computer Network Defense

This chapter describes how to use attack graphs to evaluate the security vulnerabilities of an embedded computer network and provides example cases of this technique. Attack graphs are powerful tools available to system administrators to identify and manage vulnerabilities. Attack graphs describe the steps an adversary could take to reach a desired goal and can be analyzed to quantify risk. The systems investigated in this chapter are embedded systems that span hardware, software, and network communication. The example cases studied will be (1) radio frequency identification (RFID), (2) vehicle networks, and (3) the Smart Grid (the next generation power and distribution network in the USA).

Attack Graphs and Scenario Driven Wireless Computer Network Defense

2012 ◽  
pp. 284-301 ◽  
Author(s):  
Peter J. Hawrylak ◽  
George Louthan ◽  
Jeremy Daily ◽  
John Hal ◽  
Mauricio Papa
Keyword(s):  
Radio Frequency Identification ◽  
Computer Network ◽  
Security Vulnerabilities ◽  
Attack Graphs ◽  
Network Defense ◽  
Embedded Computer ◽  
The Usa ◽  
Vehicle Networks ◽  
Frequency Identification ◽  
Computer Network Defense

This chapter describes how to use attack graphs to evaluate the security vulnerabilities of an embedded computer network and provides example cases of this technique. Attack graphs are powerful tools available to system administrators to identify and manage vulnerabilities. Attack graphs describe the steps an adversary could take to reach a desired goal and can be analyzed to quantify risk. The systems investigated in this chapter are embedded systems that span hardware, software, and network communication. The example cases studied will be (1) radio frequency identification (RFID), (2) vehicle networks, and (3) the Smart Grid (the next generation power and distribution network in the USA).

Consumers' Perceptions of Item-Level RFID Use in FMCG

2017 ◽  
Vol 25 (1) ◽  
pp. 21-42 ◽  
Author(s):  
Wesley Kukard ◽  
Lincoln Wood
Keyword(s):  
Technology Acceptance ◽  
Radio Frequency Identification ◽  
Rfid Technology ◽  
Consumer Privacy ◽  
Consumer Benefits ◽  
Item Level ◽  
The Usa ◽  
Frequency Identification ◽  
Privacy Risks ◽  
Privacy Issues

This research explores how perceived consumer benefits affect the perceived privacy risks from implementation of Radio Frequency Identification (RFID) tags at an item-level in the Fast Moving Consumer Goods (FMCG) industry. Two new categories measure the benefits and risks: in-store and after-sales. These specific categories allow the respondents' willingness to accept RFID to be evaluated using a quantitative survey focused on the primary household grocery purchasers within the USA. The results suggest differences in perceptions of the in-store and after-sales risks and benefits of RFID use. While consumers are aware of privacy risks while using RFID technology, they would be willing to use the technology if sufficient benefits are available. This research moves the discussion away from a focus on consumer privacy issues to a balanced privacy/benefits approach for consumers and how that might affect their technology acceptance, suggesting that careful management of consumer benefits might allow FMCG firms to introduce RFID technology to support their global supply chains.

An Approach for Description of Computer Network Defense Scheme and Its Simulation Verification

2014 ◽  
Vol 9 (2) ◽  
Author(s):  
Zhao Wei ◽  
Chunhe Xia ◽  
Yang Luo ◽  
Xiaochen Liu ◽  
Weikang Wu
Keyword(s):  
Computer Network ◽  
Network Defense ◽  
Computer Network Defense

Ecological Interface Design for Computer Network Defense

2018 ◽  
Vol 60 (5) ◽  
pp. 610-625 ◽  
Author(s):  
Kevin B. Bennett ◽  
Adam Bryant ◽  
Christen Sushereba
Keyword(s):  
Interface Design ◽  
Computer Network ◽  
Technical Problem ◽  
Direct Perception ◽  
Data Set ◽  
Ecological Interface Design ◽  
Analysis And Design ◽  
Network Defense ◽  
Ecological Interface ◽  
Computer Network Defense

Objective: A prototype ecological interface for computer network defense (CND) was developed. Background: Concerns about CND run high. Although there is a vast literature on CND, there is some indication that this research is not being translated into operational contexts. Part of the reason may be that CND has historically been treated as a strictly technical problem, rather than as a socio-technical problem. Methods: The cognitive systems engineering (CSE)/ecological interface design (EID) framework was used in the analysis and design of the prototype interface. A brief overview of CSE/EID is provided. EID principles of design (i.e., direct perception, direct manipulation and visual momentum) are described and illustrated through concrete examples from the ecological interface. Results: Key features of the ecological interface include (a) a wide variety of alternative visual displays, (b) controls that allow easy, dynamic reconfiguration of these displays, (c) visual highlighting of functionally related information across displays, (d) control mechanisms to selectively filter massive data sets, and (e) the capability for easy expansion. Cyber attacks from a well-known data set are illustrated through screen shots. Conclusion: CND support needs to be developed with a triadic focus (i.e., humans interacting with technology to accomplish work) if it is to be effective. Iterative design and formal evaluation is also required. The discipline of human factors has a long tradition of success on both counts; it is time that HF became fully involved in CND. Application: Direct application in supporting cyber analysts.

Visualization techniques for computer network defense

2011 ◽  
Author(s):  
Justin M. Beaver ◽  
Chad A. Steed ◽  
Robert M. Patton ◽  
Xiaohui Cui ◽  
Matthew Schultz
Keyword(s):  
Computer Network ◽  
Network Defense ◽  
Visualization Techniques ◽  
Computer Network Defense
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