Military Communications and Information Technology: A Trusted ...

Military Communications and Information Technology: A Trusted ... Military Communications and Information Technology: A Trusted ...

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264 Military Communications and Information Technology... [9] M. Harren, J.M. Hellerstein, R. Huebsch, Boon Thau Loo, S. Shenker, and I. Stoica, Complex queries in dht-based peer-to-peer networks. In Revised Papers from the First International Workshop on Peer-to-Peer Systems, IPTPS ’01, pp. 242-259, London, UK, 2002. Springer-Verlag. [10] A. Herbert, What happened to pastry. SIGOPS Oper. Syst. Rev., 41:10-16, April 2007. [11] R. Jimenez, F. Osmani, and B. Knutsson, Sub-second lookups on a large-scale kademlia-based overlay. In Peer-to-Peer Computing (P2P), 2011 IEEE International Conference on, pp. 82-91, September 2011. [12] D. Kato and T. Kamiya, Evaluating DHT implementations in complex environments by network emulator. In International Workshop on Peer-to-Peer Systems (IPTPS ’07), February 2007. [13] J. Li, J. Stribling, R. Morris, M. Frans Kaashoek, and T.M. Gil, A performance vs. cost framework for evaluating DHT design tradeoffs under churn. In INFOCOM, pp. 225-236. IEEE, 2005. [14] Maymounkov and Mazieres, Kademlia: A peer-to-peer information system based on the XOR metric. In International Workshop on Peer-to-Peer Systems (IPTPS), LNCS, vol. 1, 2002. [15] PPLive. PPTV. http://www.pptv.com. accessed on 2011-03-11. [16] S. Ratnasamy, J.M. Hellerstein, and S. Shenker, Range queries over DHTs. Technical report, Intel Corporation, 2003. [17] S. Rhea, B.-G. Chun, J. Kubiatowicz, and S. Shenker, Fixing the embarrassing slowness of opendht on planetlab. In WORLDS ’05: Proceedings of the 2nd conference on Real, Large Distributed Systems, pp. 25-30, Berkeley, CA, USA, 2005. USENIX Association. [18] A. Rowstron, P. Druschel, Pastry: Scalable, distributed object location and routing for large-scale peer-to-peer systems. In IFIP/ACM International Conference on Distributed Systems Platforms (Middleware), pp. 329-350, November 2001. [19] C. Schmidt, M. Parashar, Enabling flexible queries with guarantees in p2p systems. IEEE Internet Computing, 8:19-26, 2004. [20] D. Stutzbach, R. Rejaie, Understanding churn in peer-to-peer networks. In Jussara M. Almeida, Virg´ılio A.F. Almeida, and Paul Barford, editors, Internet Measurement Conference, pages 189-202. ACM, 2006. [21] A. Varga, OMNeT++ discrete event simulation system. http://www.omnetpp.org, April 2009.

Automatic Exploitation of Multilingual Information for Military Intelligence Purposes Sandra Noubours, Matthias Hecking Fraunhofer Institute for Communication, Information Processing and Ergonomics FKIE, D-53343Wachtberg, Germany, {sandra.noubours, matthias.hecking}@fkie.fraunhofer.de Abstract: Intelligence plays an important role in supporting military operations. In the course of military intelligence a vast amount of textual data in different languages needs to be analyzed. In addition to information provided by traditional military intelligence, nowadays the internet offers important resources of potential militarily relevant information. However, we are not able to manually handle this vast amount of data. The science of natural language processing (NLP) provides technology to efficiently handle this task, in particular by means of machine translation and text mining. In our research project ISAF-MT we created a statistical machine translation (SMT) system for Dari to German. In this paper we describe how NLP technologies and in particular SMT can be applied to different intelligence processes. We therefore argue that multilingual NLP technology can strongly support military operations. Keywords: Statistical machine translation, natural language processing, open source intelligence, military intelligence I. Introduction Military operations strongly depend on up-to-date information. This is necessary to be able to act in the most effective and coordinated way possible at any given time. Therefore relevant information must be provided by military intelligence cells operating according to a specific process. This process includes collection, processing and analysis of information. Information which is important for military purposes can come in a variety of forms, e.g., signals, geospatial data, audio and video files or textual data. In this paper we will focus on the processing of text. In addition to intelligence provided by humans (HUMINT), nowadays open source intelligence (OSINT), particularly in terms of exploiting the internet, has become an essential source of potentially relevant information [1]. Live information from global news sites and user-generated content can now provide us with important knowledge. Terrorist organizations present in the web make the internet even more interesting from a military point of view. Consequently, we have access to a vast amount of data, which imposes great challenges to information processing

Automatic Exploitation of Multilingual <strong>Information</strong><br />

for <strong>Military</strong> Intelligence Purposes<br />

S<strong>and</strong>ra Noubours, Matthias Hecking<br />

Fraunhofer Institute for Communication, <strong>Information</strong> Processing <strong>and</strong> Ergonomics FKIE,<br />

D-53343Wachtberg, Germany, {s<strong>and</strong>ra.noubours, matthias.hecking}@fkie.fraunhofer.de<br />

Abstract: Intelligence plays an important role in supporting military operations. In the course<br />

of military intelligence a vast amount of textual data in different languages needs to be analyzed.<br />

In addition to information provided by traditional military intelligence, nowadays the internet offers<br />

important resources of potential militarily relevant information. However, we are not able to manually<br />

h<strong>and</strong>le this vast amount of data. The science of natural language processing (NLP) provides technology<br />

to efficiently h<strong>and</strong>le this task, in particular by means of machine translation <strong>and</strong> text mining.<br />

In our research project ISAF-MT we created a statistical machine translation (SMT) system for Dari<br />

to German. In this paper we describe how NLP technologies <strong>and</strong> in particular SMT can be applied<br />

to different intelligence processes. We therefore argue that multilingual NLP technology can strongly<br />

support military operations.<br />

Keywords: Statistical machine translation, natural language processing, open source intelligence,<br />

military intelligence<br />

I. Introduction<br />

<strong>Military</strong> operations strongly depend on up-to-date information. This is necessary<br />

to be able to act in the most effective <strong>and</strong> coordinated way possible at any given<br />

time. Therefore relevant information must be provided by military intelligence cells<br />

operating according to a specific process. This process includes collection, processing<br />

<strong>and</strong> analysis of information. <strong>Information</strong> which is important for military purposes<br />

can come in a variety of forms, e.g., signals, geospatial data, audio <strong>and</strong> video files<br />

or textual data. In this paper we will focus on the processing of text.<br />

In addition to intelligence provided by humans (HUMINT), nowadays open<br />

source intelligence (OSINT), particularly in terms of exploiting the internet, has become<br />

an essential source of potentially relevant information [1]. Live information<br />

from global news sites <strong>and</strong> user-generated content can now provide us with important<br />

knowledge. Terrorist organizations present in the web make the internet<br />

even more interesting from a military point of view. Consequently, we have access<br />

to a vast amount of data, which imposes great challenges to information processing

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