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Stephen Groat et al. Table 2: Probability conducted in simulation of detecting a target host with an 8-bit address within 64, 128, 192, and 256 guesses, each listed probability is the average over 100,000 iterations Probability of detection within: 64 guesses 128 guesses 192 guesses 256 guesses Static Address 0.249 0.503 0.748 1 0.248 0.435 0.578 0.682 Changing Address (r64) Changing Address (r8) Changing Address (r1) 7. Security through dynamic addressing 0.225 0.398 0.533 0.637 0.222 0.393 0.528 0.632 Establishing a moving target defense is an effective way of protecting users’ privacy and data. Changing hosts’ addresses, referred to as dynamic addressing, enhances security. If target addresses continually change, an attacker loses the expectation of narrowing the search space with successive guesses. If the attacker is able to locate a targeted host, a dynamically changing host address limits the time an attacker has access to the host. Since the discovered address changes, the attacker no longer knows the host’s location on the network. Additionally, the nature of dynamic addressing prevents other types of targeted attacks, which rely on static addressing. Changing the addresses of hosts allows them to logically move within the address space or subnet. As illustrated in Figure 2, the more often an address changes, the more difficult it is to locate and target the host. A changing address, combined with other factors such as address size and subnet density, creates a moving target defense. A large address space supporting many hosts is sparsely populated making it difficult for an attacker to pinpoint a specific target host. Other network hosts result in false positives for an attacker while unoccupied address spaces reduces the possibility of address collisions. The incorporation of dynamic addressing considerably reduces the probability of detecting a target host while still maintaining connectivity. Dynamic addressing also protects against certain classes of network attacks. For example, an attacker attempting a targeted DoS attack first has to find the target host on the subnet. Even if the attacker finds the host, the attack is limited by the interval between address changes. Other targeted network attacks, such as session hijacking and man-in-the-middle, are constrained by the same limitations as DoS attacks. To attack dynamically addressed hosts, an attacker must be able to either quickly find the host after an address change or predict the address change. If a sufficiently randomized dynamic address obscuration algorithm is utilized, targeting hosts in a large address space should not be possible. Providing security at the network layer also provides transitive security against attacks and exploits at layers above the network layer since many other attacks rely on network transmissions. The majority of application layer security flaws are exploited by either taking control of a system or transferring sensitive information back to an attacker. By securing the network layer, even if an attacker is able to identify a valid vector of attack on an application, the window for attack is limited by the frequency of the address change. Once the address changes, the attacker loses any existing vector to control the remote host. The attacker must then locate the host to reestablish the connection. 8. Future work The next phase of our research works to develop a sufficiently randomized algorithm for dynamically obscuring IP addresses. Our goal is to produce an approach that dynamically changes IP addresses multiple times within a single session. By changing addresses multiple times within a single session, an attacker will have more difficulty locating target hosts. Even if an attacker locates the host, 90
Stephen Groat et al. changing addresses multiple times within a session prevents the attacker from capturing enough network traffic to correlate the nature of a communication between two hosts. Our particular approach leverages IPv6. As eluded to in Section 4.1, current methods for locating a target address in an IPv6 subnet are infeasible in a reasonable amount of time. The immense IPv6 address space will also likely be sparsely populated. As discussed in Section 4.3, locating any host in a sparsely populated address space is probabilistically difficult. In addition to the difficulty of locating hosts in a sparsely populated subnet, hosts using a dynamic addressing scheme can reasonably expect not to collide with occupied addresses when rotating their addresses. In order to achieve a reasonable dynamic addressing algorithm in IPv4, hosts would have to draw from a pool of unused addresses. Reserving pools of addresses are more difficult with the depletion of the IPv4 address space (NRO 2010). Additionally, an IPv4 pool of addresses, regardless of how large, would be almost trivial for an attacker to scan. To achieve a sufficiently randomized dynamic addressing algorithm, we plan to repeatedly use a cryptographic hash function to obscure the 64-bit interface identifier that makes up the subnet portion of an IPv6 address. By using a cryptographic hash function, malicious hosts cannot feasibly predict the dynamic address (Schneier 1996). Since hosts in IPv6 can generate and advertise their own addresses (Thomson, Narten & Jinmei 2007), obscuration is kept local. Localizing obscuration reduces the possibility of a malicious host performing any type of address hijacking or man-in-the-middle attack. It also reduced the computational overhead that address generation servers would incur. 9. Conclusion As users exchange more personally identifiable information over the Internet, it is increasingly important to protect users’ security and privacy. One of the best ways to accomplish this is through the use of a moving target defense. At the network layer, this can be achieved by dynamically changing host IP addresses. Frequently changing addresses are probabilistically more difficult to detect than static addresses. Dynamic addresses also provide an additional layer of security for hosts that are detected by an attacker. An attacker is unable to compromise hosts for a significant period of time since the hosts’ network address changes. Dynamically changing addresses provide security and privacy by creating a moving target solution implementable as low as the network layer of the protocol stack. References Bagnulo, M., & Arkko, J. October 2006. Cryptographically Generated Addresses (CGA) Extension Field Format. RFC 4581 (Proposed Standard). Dunlop, M., Groat, S., Marchany, R., & Tront, J., 23-28 January 2011. ‘IPv6: Now You See Me, Now You Don't’, Proceedings of the Tenth International <strong>Conference</strong> on Networks (ICN 2011), St. Maarten, The Netherlands Antilles. Fink, R. A., Brannigan, M. A., Evans, S. A., Almeida, A. M., & Ferguson, S. A. 9 May 2006. Method and Apparatus for Providing Adaptive Self-Synchronized Dynamic Address Translation, United States Patent No. US 7,043,633 B1. GLORIAD. 2010. GLORIAD Average Round Trip Time - Last Week. [Online] Available http://www.gloriad.org/gloriad/monitor/stats/avg_round_trip_time.week.html. [11 October, 2010]. Johnson, P. C., Kapadia, A., Tsang, P. P., & Smith, S. W. 2007. ‘Nymble: Anonymous IP-Address Blocking’, Privacy Enhancing Technologies Symposium (PET '07), Ottawa, Canada, pp.113-133. Koukis, D., Antonatos, S., & Anagnostakis, K. 2006. On the Privacy Risks of Publishing Anonymized IP Network Traces. Communications and Multimedia Security, 4237: 22-32. Narten T., Draves, R., & Krishnan, S. September 2007. Privacy Extensions for Stateless Address Autoconfiguration in IPv6. RFC 4941 (Draft Standard). NRO. 2010. Remaining IPv4 address space drops below 5%. [Online] Available http://www.nro.net/ media/remaining-ipv4-address-below-5.html, [7 November, 2010]. Reiter, M., & Rubin, A. ‘Anonymous Web Transactions with Crowds’, Communications of the ACM, vol. 42, no. 2, pp. 32-48. Schneier, B. 1996. Applied Cryptography: Protocols, Algorithms, and Source Code in C. (2 nd Edition. New York: Wiley. Sheymov, V. I. 18 February, 2010. Method and Communications and Communication Network Intrusion Protection Methods and Intrusion Attempt Detection System, United States Patent No. US 2010/0042513 A1. Shields, C., & Levine, B. N. 2000. ‘A protocol for anonymous communication over the Internet’, Proceedings of the 7th ACM conference on Computer and communications security, Athens, Greece, pp. 33-42. Thomson, S., Narten T., & Jinmei, T. September 2007. IPv6 Stateless Address Autoconfiguration. RFC 4862 (Draft Standard). 91
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The Proceedings of the 6th Internat
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Contents Paper Title Author(s) Page
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Preface These Proceedings are the w
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Biographies of contributing authors
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Department of Computer Science, IQR
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Using the Longest Common Substring
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Jaime Acosta Some techniques that u
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Jaime Acosta assigned by an anti-vi
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Jaime Acosta Cormen, T.H., Leiserso
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Hind Al Falasi and Liren Zhang tran
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Hind Al Falasi and Liren Zhang ther
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Hind Al Falasi and Liren Zhang the
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Edwin Leigh Armistead and Thomas Mu
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Deception Operations Security (OPS
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The Uses and Limits of Game Theory
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3. Limits to using game theory 3.1
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Merritt Baer Effective cyberintrusi
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Merritt Baer 1.5), there seems to b
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Merritt Baer Report of the Defense
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Ivan Burke and Renier van Heerden F
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Ivan Burke and Renier van Heerden a
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Ivan Burke and Renier van Heerden F
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Page 81 and 82: Mecealus Cronkrite et al. trivial.
Page 83 and 84: Mecealus Cronkrite et al. socially
Page 85 and 86: Mecealus Cronkrite et al. The views
Page 87 and 88: Vincent Garramone and Daniel Likari
Page 95 and 96: Stephen Groat et al. Sections 4 and
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Page 103 and 104: Marthie Grobler et al. leadership,
Page 105 and 106: Marthie Grobler et al. apply to sta
Page 107 and 108: Marthie Grobler et al. 6. Working t
Page 109 and 110: Cyber Strategy and the Law of Armed
Page 111 and 112: Ulf Haeussler Alliance and Allies r
Page 113 and 114: Ulf Haeussler following the invocat
Page 115 and 116: Ulf Haeussler NCSA (2009) NCSA Supp
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Page 119 and 120: Karim Hamza and Van Dalen From a mi
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Page 123 and 124: Intelligence-Driven Computer Networ
Page 125 and 126: Eric Hutchins et al. of defensive a
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Page 135 and 136: Eric Hutchins et al. U.S.-China Eco
Page 137 and 138: Saara Jantunen and Aki-Mauri Huhtin
Page 145 and 146: Brian Jewell and Justin Beaver In t
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Page 149 and 150: 4. Evaluation Brian Jewell and Just
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Brian Jewell and Justin Beaver othe
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Detection of YASS Using Calibration
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Kesav Kancherla and Srinivas Mukkam
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M M M Su−2 Sv ∑∑ u= 1 v= 1 h(
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5.2 ROC curves Kesav Kancherla and
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Developing a Knowledge System for I
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Louise Leenen et al. We distinction
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Louise Leenen et al. There is growi
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3.1 Needs analysis Louise Leenen et
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Louise Leenen et al. Kroenke, D.M.
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Jose Mas y Rubi et al. As we can se
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Figure 2: CALEA forensic model (Pel
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Jose Mas y Rubi et al. Table 2: Com
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Jose Mas y Rubi et al. Another pend
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Tree of Objectives Acknowledgements
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Secure Proactive Recovery - a Hardw
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Ruchika Mehresh et al. implementing
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Ruchika Mehresh et al. The coordina
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Ruchika Mehresh et al. multiplicati
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Ruchika Mehresh et al. Table 2: App
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2. Network infiltration detection D
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David Merritt and Barry Mullins on
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David Merritt and Barry Mullins Ess
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David Merritt and Barry Mullins Dev
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Muhammad Naveed Pakistan Computer E
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Muhammad Naveed response could also
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Muhammad Naveed Table 10: Aggressiv
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Muhammad Naveed 2006 Tcp Open Mysql
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Muhammad Naveed 8009 Tcp Open Ajp13
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Muhammad Naveed Austalian Taxation
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Alexandru Nitu world and bring it i
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Alexandru Nitu Article 51 restricts
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Alexandru Nitu As IW strategy and t
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Cyberwarfare and Anonymity Christop
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Christopher Perr attacks again help
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Christopher Perr about the current
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Catch me if you can: Cyber Anonymit
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David Rohret and Michael Kraft reve
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David Rohret and Michael Kraft sary
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Data (Evidence) Removal Shield Davi
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Neutrality in the Context of Cyberw
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Julie Ryan and Daniel Ryan 18th cen
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Julie Ryan and Daniel Ryan “Decla
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Julie Ryan and Daniel Ryan von Glah
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Harm Schotanus et al. In the remain
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Harm Schotanus et al. 2.3.1 Secure
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Harm Schotanus et al. In this setup
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Harm Schotanus et al. the label (by
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Harm Schotanus et al. these aspects
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Maria Semmelrock-Picej et al. they
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Maria Semmelrock-Picej et al. User
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Maria Semmelrock-Picej et al. SPIKE
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Maria Semmelrock-Picej et al. A cl
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Maria Semmelrock-Picej et al. in co
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Maria Semmelrock-Picej et al. In th
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Maria Semmelrock-Picej et al. Fuchs
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Madhu Shankarapani and Srinivas Muk
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Figure 1: UPX packed Trojan Figure
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Trojan.Zb ot- 1342.mal Trojan.Sp y.
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Madhu Shankarapani and Srinivas Muk
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Namosha Veerasamy and Marthie Grobl
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4. Conclusion Namosha Veerasamy and
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Tanya Zlateva et al. Computer Infor
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Tanya Zlateva et al. security and v
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Tanya Zlateva et al. court opinions
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Tanya Zlateva et al. 5. Pedagogy, e
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PhD Research Papers 277
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Shada Alsalamah et al. Level 3 all
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Shada Alsalamah et al. assure the a
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Shada Alsalamah et al. for Health I
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3. Hematology Laboratory System Who
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Shada Alsalamah et al. Pirnejad, H.
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Michael Bilzor a diverse base of U.
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Michael Bilzor In our current exper
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5. Execution monitor theory Michael
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Michael Bilzor design was run in si
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Michael Bilzor over testbench metho
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Evan Dembskey and Elmarie Biermann
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Theoretical Offensive Cyber Militia
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Rain Ottis Last, but not least, it
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Rain Ottis an infantry battalion, w
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Rain Ottis Ottis, R. (2008) “Anal
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Work in Progress Papers 315
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Large-Scale Analysis of Continuous
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References William Acosta Abadi, D.
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Natarajan Vijayarangan top box unit
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Natarajan Vijayarangan The proposed
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