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received 20 packets from node B and forwarded 20 packets to node D (even though it only forwarded 15), or it will need to report that it received 15 packets from node B (even though it actually received 20) and forwarded 15 packets to node D In the rst case Node D s report will contradict node C s report because node D will report that it only received 15 packets In the second case node B s report will contradict node C s report because node B will report that it sent 20 packets to node C In either case the coordinator can detect that there is a malicious node and also the pair of nodes in which one is malicious The coordinator may not necessarily be able to detect which of this pair of nodes is malicious Assuming that there are enough ows in the network and that the number of well-behaved nodes is suf ciently high, the coordinator can gure out which nodes are malicious because there will be multiple pairs of suspicious nodes The nodes that are common across multiple pairs will be the malicious nodes For example, let us assume in our previous example that there is another ow originating in node F, traveling through node C and terminating at node G (see Figure 512) If node C starts lying in its reports, contradictions will arise with the reports of multiple nodes Therefore the coordinator will be able to clearly identify the malicious node The scheme is not necessarily foolproof because the coordinator may not have suf cient information in all cases to decide about the lying node Some such cases are when there are not enough ows, when there are no other nodes in the neighborhood, or when a node decides to drop packets only from a subset of nodes For example, if node C only drops packets destined for node D and tries to contradict only node D s reports, then the coordinator will not be able to decide whether node C or node D is lying The advantage of this technique is that the detection algorithm does not rely on promiscuous monitoring The algorithm has its own signi cant limitations, however Reports of nodes to the coordinator may contradict each other on account of the lossy nature of the links rather than malicious behavior In the example discussed earlier, node A may report the correct number of packet that it forwarded to node B, and node B may report the packets it actually received from node A, but the reports may differ Node B may not receive all of the packets sent by node A Some of the packets may be lost due to the lossy link between the two nodes In that case reports from nodes A and B will be inconsistent and may result in a false positive The scheme tolerates such.



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Bucik, V, & Neubauer, A C (1996) Bimodality in the Berlin Model of Intelligence Structure (BIS): A replication study Personality and Individual Differences, 21:987 1005 Dorner, D, Kreuzig, H W, Reither, F & Staudel, T (1983) Lohhausen Vom Umgang mit t Unbestimmtheit und Komplexita [Lohhausen On dealing with uncertainty and complexity] Bern: Huber Fishbein, M, & Ajzen, I (1974) Attitudes towards objects as predictors of single and multiple behavioral criteria Psychological Review, 81:59 74 Funke, J (1991) Solving complex problems: Exploration and control of complex systems In R J Sternberg & P A Frensch (Eds), Complex problem solving: Principles and mechanisms (pp 185 222) Hillsdale, NJ: Erlbaum Funke, J (1998) Computer-based testing and training with scenarios from complex problem solving research: Advantages and disadvantages International Journal of Selection and Assessment, 6:90 96 Funke, U (1995) Using complex problem solving tasks in personnel selection and training In P A Frensch & J Funke (eds), Complex problem solving: The European perspective (pp 219 240) Hillsdale, NJ: Erlbaum Jager, A O (1982) Mehrmodale Klassi kation von Intelligenzleistungen: Experimentell kontrollierte Weiterentwicklung eines deskriptiven Intelligenzstrukturmodells [Multimodal classi cation of intelligence tests: Experimentally controlled development of a descriptive model of intelligence structure] Diagnostica, 28:195 225 Jager, A O (1984) Intelligenzstrukturforschung: Konkurrierende Modelle, neue Entwicklungen, Perspektiven [Research on intelligence structure: Competing models, new developments, perspectives] Psychologische Rundschau, 35:21 35 Kersting, M (1998) Differentielle Aspekte der sozialen Akzeptanz von Intelligenztests und Problemloseszenarien als Personalauswahlverfahren [Differential-psychological aspects of applicants acceptance of intelligence tests and problem solving scenarios r as diagnostic tools for personnel selection] Zeitschrift fu Arbeits- und Organisations psychologie, 42:61 75 tzten Problemlo sesKersting, M (1999) Diagnostik und Personalauswahl mit computergestu zenarien [Assessment and personnel selection with computer-simulated problem solving scenarios ] Gottingen: Hogrefe Kersting, M (2001) Zur Konstrukt- und Kriteriumsvaliditat von Problemloseszenarien anhand der Vorhersage von Vorgesetztenurteilen uber die beru iche Bewahrung [On the construct and criterion validity of problem solving scenarios based on the prediction of supervisor assessment of job performance] Diagnostica, 47:67 76 Koller, O, Strau , B, & Sievers, K (1995) Zum Zusammenhang von (selbst eingeschatz ter) Kompetenz und Problemloseleistungen in komplexen Situationen [Correlation of (self assessed) competence and performance of problem solving in complex situations] Sprache & Kognition, 14:210 220 Locke, S D, & Gilbert, B O (1995) Method of psychological assessment, self disclosure, and experiential differences: A study of computer, questionnaire, and interview assessment formats Journal of Social Behaviour and Personality, 10:187 192 sen: Reliabilita und Wissen [Complex problem solving: t Muller, H (1993) Komplexes Problemlo Reliability and knowledge] Bonn: Holos Pressey, S L (1926) A simple apparatus which gives tests and scores and teaches School and Society, 23:373 376 Reynolds, D H, Sinar, E F, Scott, D R, & McClough, A C (2000) Evaluation of a Webbased selection procedure In N Mondragon (Chair), Beyond the demo: The empirical nature of technology-based assessments Symposium conducted at the 15th Annual Society for Industrial and Organizational Psychology Conference, New Orleans, LA Sands, W A, Waters, B K, & McBride, J R (1997) Computerized Adaptive Testing Washington, DC: American Psychological Association Shotland, A, Alliger, G M, & Sales, T (1998) Face validity in the context of personnel selection: A multimedia approach International Journal of Selection and Assessment, 6:124 130.

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