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Detecting Asks in SE attacks: Impact of Linguistic and Structural Knowledge ...
Abstract: Social engineers attempt to manipulate users into undertaking actions such as downloading malware by clicking links or providing access to money or sensitive information. Natural language processing, computational sociolinguistics, and media-specific structural clues provide a means for detecting both the ask (e.g., buy gift card) and the risk/reward implied by the ask, which we call framing (e.g., lose your job, get a raise). We apply linguistic resources such as Lexical Conceptual Structure to tackle ask detection and also leverage structural clues such as links and their proximity to identified asks to improve confidence in our results. Our experiments indicate that the performance of ask detection, framing detection, and identification of the top ask is improved by linguistically motivated classes coupled with structural clues such as links. Our approach is implemented in a system that informs users about social engineering risk situations. ... : Accepted at AAAI 2020 ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.2002.10931
https://arxiv.org/abs/2002.10931
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2
Adaptation of a Lexical Organization for Social Engineering Detection and Response Generation ...
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3
Modeling Leadership Behavior of Players in Virtual Worlds
In: Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment; Vol. 11 No. 1 (2015): Eleventh Artificial Intelligence and Interactive Digital Entertainment Conference ; 2334-0924 ; 2326-909X (2015)
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4
Modeling Sociocultural phenomena in discourse
In: Natural language engineering. - Cambridge : Cambridge University Press 19 (2013) 2, 213-257
OLC Linguistik
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5
HITIQA: high-quality intelligence through interactive question answering
In: Natural language engineering. - Cambridge : Cambridge University Press 15 (2009) 1, 31-54
BLLDB
OLC Linguistik
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6
Information retrieval
In: The Oxford handbook of computational linguistics (New York, 2009), p. 529-544
MPI für Psycholinguistik
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7
The AMITIÉS system : data-driven techniques for automated dialogue
In: Speech communication. - Amsterdam [u.a.] : Elsevier 48 (2006) 3-4, 354-373
BLLDB
OLC Linguistik
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8
Advances in open domain question answering
Strzalkowski, Tomek (Hrsg.); Harabagiu, Sanda. - Dordrecht : Springer, 2006
IDS Mannheim
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9
Advances in open domain question answering
Harabagiu, Sanda M. (Hrsg.); Strzalkowski, Tomek (Hrsg.). - Dordrecht : Springer, 2006
BLLDB
UB Frankfurt Linguistik
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10
HITIQA: A Data Driven Approach to Interactive Analytical Question Answering
In: DTIC (2004)
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11
HITIQA: Towards Analytical Question Answering
In: DTIC (2004)
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12
HITIQA: An Interactive Question Answering System. A Preliminary Report
In: DTIC (2003)
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13
Dialogue Management for an Automated Multilingual Call Center
In: DTIC (2003)
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14
Book Reviews - Natural Language Information Retrieval
In: Computational linguistics. - Cambridge, Mass. : MIT Press 26 (2000) 3, 460-462
OLC Linguistik
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15
Natural language information retrieval
Strzalkowski, Tomek (Hrsg.). - Dordrecht ; Boston [u.a.] : Kluwer, 1999
IDS Mannheim
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16
Natural language information retrieval
Kupiec, Julian (Mitarb.); Leistensnider, James (Mitarb.); Riloff, Ellen (Mitarb.). - Dordrecht [u.a.] : Kluwer, 1999
BLLDB
UB Frankfurt Linguistik
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17
Building Effective Queries in Natural Language Information Retrieval
In: DTIC (1997)
BASE
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18
Recent advances in parsing technology
Raaijmakers, Stephan (Mitarb.); Rönnquist, Ralph (Mitarb.); Strzalkowski, Tomek (Mitarb.). - Dordrecht [u.a.] : Kluwer, 1996
BLLDB
UB Frankfurt Linguistik
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19
NLP Track at TREC-5
In: DTIC (1996)
BASE
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20
Natural Language Information Retrieval: Tipster-2 Final Report
In: DTIC (1996)
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