The Experts below are selected from a list of 30 Experts worldwide ranked by ideXlab platform
Marti Une - One of the best experts on this subject based on the ideXlab platform.
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theory of mind in schizophrenia a review of the literature
Schizophrenia Bulletin, 2005Co-Authors: Marti UneAbstract:The term theory of mind (ToM) refers to the capacity to inferone’sownandother persons’mentalstates. Asubstantial body of research has highlighted the evolution of ToM in nonhuman primates, its emergence during human ontogeny,and impaired ToMin avarietyof neuropsychiatric disorders, including schizophrenia. There is good empirical evidence that ToM is specifically impaired in schizophrenia andthatmanypsychoticsymptoms—forinstance,delusions ofaliencontrolandpersecution,thepresenceofthoughtand language disorganization, and other Behavioral symptoms—maybestbeunderstoodinlightofadisturbedcapacity in patients to relate their own intentions to Executing Behavior, and to monitor others’ intentions. However, it is still under debate how an impaired ToM in schizophrenia isassociatedwithotheraspectsofcognition,howtheimpairmentfluctuateswithacuityorchronicityoftheschizophrenic disorder, and how this affects the patients’ use of language and social Behavior. In addition to these potential research areas,futurestudiesmayalsoaddresswhetherpatientscould benefit from cognitive training in this domain.
Wenke Lee - One of the best experts on this subject based on the ideXlab platform.
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ACSAC - PolyUnpack: Automating the Hidden-Code Extraction of Unpack-Executing Malware
2006 22nd Annual Computer Security Applications Conference (ACSAC'06), 2006Co-Authors: Paul Royal, Mitch Halpin, David Dagon, Robert Edmonds, Wenke LeeAbstract:Modern malware often hide the malicious portion of their program code by making it appear as data at compile-time and transforming it back into executable code at runtime. This obfuscation technique poses obstacles to researchers who want to understand the malicious Behavior of new or unknown malware and to practitioners who want to create models of detection and methods of recovery. In this paper we propose a technique for automating the process of extracting the hidden-code bodies of this class of malware. Our approach is based on the observation that sequences of packed or hidden code in a malware instance can be made self-identifying when its runtime execution is checked against its static code model. In deriving our technique, we formally define the unpack-Executing Behavior that such malware exhibits and devise an algorithm for identifying and extracting its hidden-code. We also provide details of the implementation and evaluation of our extraction technique; the results from our experiments on several thousand malware binaries show our approach can be used to significantly reduce the time required to analyze such malware, and to improve the performance of malware detection tools.
Paul Royal - One of the best experts on this subject based on the ideXlab platform.
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ACSAC - PolyUnpack: Automating the Hidden-Code Extraction of Unpack-Executing Malware
2006 22nd Annual Computer Security Applications Conference (ACSAC'06), 2006Co-Authors: Paul Royal, Mitch Halpin, David Dagon, Robert Edmonds, Wenke LeeAbstract:Modern malware often hide the malicious portion of their program code by making it appear as data at compile-time and transforming it back into executable code at runtime. This obfuscation technique poses obstacles to researchers who want to understand the malicious Behavior of new or unknown malware and to practitioners who want to create models of detection and methods of recovery. In this paper we propose a technique for automating the process of extracting the hidden-code bodies of this class of malware. Our approach is based on the observation that sequences of packed or hidden code in a malware instance can be made self-identifying when its runtime execution is checked against its static code model. In deriving our technique, we formally define the unpack-Executing Behavior that such malware exhibits and devise an algorithm for identifying and extracting its hidden-code. We also provide details of the implementation and evaluation of our extraction technique; the results from our experiments on several thousand malware binaries show our approach can be used to significantly reduce the time required to analyze such malware, and to improve the performance of malware detection tools.
Mitch Halpin - One of the best experts on this subject based on the ideXlab platform.
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ACSAC - PolyUnpack: Automating the Hidden-Code Extraction of Unpack-Executing Malware
2006 22nd Annual Computer Security Applications Conference (ACSAC'06), 2006Co-Authors: Paul Royal, Mitch Halpin, David Dagon, Robert Edmonds, Wenke LeeAbstract:Modern malware often hide the malicious portion of their program code by making it appear as data at compile-time and transforming it back into executable code at runtime. This obfuscation technique poses obstacles to researchers who want to understand the malicious Behavior of new or unknown malware and to practitioners who want to create models of detection and methods of recovery. In this paper we propose a technique for automating the process of extracting the hidden-code bodies of this class of malware. Our approach is based on the observation that sequences of packed or hidden code in a malware instance can be made self-identifying when its runtime execution is checked against its static code model. In deriving our technique, we formally define the unpack-Executing Behavior that such malware exhibits and devise an algorithm for identifying and extracting its hidden-code. We also provide details of the implementation and evaluation of our extraction technique; the results from our experiments on several thousand malware binaries show our approach can be used to significantly reduce the time required to analyze such malware, and to improve the performance of malware detection tools.
David Dagon - One of the best experts on this subject based on the ideXlab platform.
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ACSAC - PolyUnpack: Automating the Hidden-Code Extraction of Unpack-Executing Malware
2006 22nd Annual Computer Security Applications Conference (ACSAC'06), 2006Co-Authors: Paul Royal, Mitch Halpin, David Dagon, Robert Edmonds, Wenke LeeAbstract:Modern malware often hide the malicious portion of their program code by making it appear as data at compile-time and transforming it back into executable code at runtime. This obfuscation technique poses obstacles to researchers who want to understand the malicious Behavior of new or unknown malware and to practitioners who want to create models of detection and methods of recovery. In this paper we propose a technique for automating the process of extracting the hidden-code bodies of this class of malware. Our approach is based on the observation that sequences of packed or hidden code in a malware instance can be made self-identifying when its runtime execution is checked against its static code model. In deriving our technique, we formally define the unpack-Executing Behavior that such malware exhibits and devise an algorithm for identifying and extracting its hidden-code. We also provide details of the implementation and evaluation of our extraction technique; the results from our experiments on several thousand malware binaries show our approach can be used to significantly reduce the time required to analyze such malware, and to improve the performance of malware detection tools.