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Articles 61 - 63 of 63
Full-Text Articles in Physical Sciences and Mathematics
Efficient Generation Of Social Network Data From Computer-Mediated Communication Logs, Jason Wei Sung Yee
Efficient Generation Of Social Network Data From Computer-Mediated Communication Logs, Jason Wei Sung Yee
Theses and Dissertations
The insider threat poses a significant risk to any network or information system. A general definition of the insider threat is an authorized user performing unauthorized actions, a broad definition with no specifications on severity or action. While limited research has been able to classify and detect insider threats, it is generally understood that insider attacks are planned, and that there is a time period in which the organization's leadership can intervene and prevent the attack. Previous studies have shown that the person's behavior will generally change, and it is possible that social network analysis could be used to observe …
Analysis Of Effects Of Bgp Black Hole Routing On A Network Like The Niprnet, Michael D. Kleffman
Analysis Of Effects Of Bgp Black Hole Routing On A Network Like The Niprnet, Michael D. Kleffman
Theses and Dissertations
The Department of Defense (DoD) relies heavily on the Non-secure Internet Protocol Router Network (NIPRNET) to exchange information freely between departments, services, bases, posts, and ships. The NIPRNET is vulnerable to various attacks, to include physical and cyber attacks. One of the most frequently used cyber attacks by criminally motivated hackers is a Distributed Denial of Service (DDoS) attack. DDoS attacks can be used to exhaust network bandwidth and router processing capabilities, and as a leveraging tool for extortion. Border Gateway Protocol (BGP) black hole routing is a responsive defensive network technique for mitigating DDoS attacks. BGP black hole routing …
A New Blind Method For Detecting Novel Steganography, Brent T. Mcbride, Gilbert L. Peterson, Steven C. Gustafson
A New Blind Method For Detecting Novel Steganography, Brent T. Mcbride, Gilbert L. Peterson, Steven C. Gustafson
Faculty Publications
Steganography is the art of hiding a message in plain sight. Modern steganographic tools that conceal data in innocuous-looking digital image files are widely available. The use of such tools by terrorists, hostile states, criminal organizations, etc., to camouflage the planning and coordination of their illicit activities poses a serious challenge. Most steganography detection tools rely on signatures that describe particular steganography programs. Signature-based classifiers offer strong detection capabilities against known threats, but they suffer from an inability to detect previously unseen forms of steganography. Novel steganography detection requires an anomaly-based classifier. This paper describes and demonstrates a blind classification …