A Type-Aware Approach to Message Clustering for Protocol Reverse Engineering

Protocol Reverse Engineering (PRE) is crucial for information security of Internet-of-Things (IoT), and message clustering determines the effectiveness of PRE. However, the quality of services still lags behind the strict requirement of IoT applications as the results of message clustering are often...
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Autor*in:	Xin Luo [verfasserIn] Dan Chen [verfasserIn] Yongjun Wang [verfasserIn] Peidai Xie [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	message clustering protocol reverse engineering Internet of Things information security

Übergeordnetes Werk:	In: Sensors - MDPI AG, 2003, 19(2019), 3, p 716
Übergeordnetes Werk:	volume:19 ; year:2019 ; number:3, p 716

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/s19030716

Katalog-ID:	DOAJ085315435

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allfieldsSound	10.3390/s19030716 doi (DE-627)DOAJ085315435 (DE-599)DOAJebe61806f8a045ac8185e0334efc7021 DE-627 ger DE-627 rakwb eng TP1-1185 Xin Luo verfasserin aut A Type-Aware Approach to Message Clustering for Protocol Reverse Engineering 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Protocol Reverse Engineering (PRE) is crucial for information security of Internet-of-Things (IoT), and message clustering determines the effectiveness of PRE. However, the quality of services still lags behind the strict requirement of IoT applications as the results of message clustering are often coarse-grained with the intrinsic type information hidden in messages largely ignored. Aiming at this problem, this study proposes a type-aware approach to message clustering guided by type information. The approach regards a message as a combination of n-grams, and it employs the Latent Dirichlet Allocation (LDA) model to characterize messages with types and n-grams via inferring the type distribution of each message. The type distribution is finally used to measure the similarity of messages. According to this similarity, the approach clusters messages and further extracts message formats. Experimental results of the approach against Netzob in terms of a number of protocols indicate that the correctness and conciseness can be significantly improved, e.g., figures 43.86% and 3.87%, respectively for the CoAP protocol. message clustering protocol reverse engineering Internet of Things information security Chemical technology Dan Chen verfasserin aut Yongjun Wang verfasserin aut Peidai Xie verfasserin aut In Sensors MDPI AG, 2003 19(2019), 3, p 716 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:19 year:2019 number:3, p 716 https://doi.org/10.3390/s19030716 kostenfrei https://doaj.org/article/ebe61806f8a045ac8185e0334efc7021 kostenfrei https://www.mdpi.com/1424-8220/19/3/716 kostenfrei https://doaj.org/toc/1424-8220 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2111 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 19 2019 3, p 716
language	English
source	In Sensors 19(2019), 3, p 716 volume:19 year:2019 number:3, p 716
sourceStr	In Sensors 19(2019), 3, p 716 volume:19 year:2019 number:3, p 716
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topic_facet	message clustering protocol reverse engineering Internet of Things information security Chemical technology
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container_title	Sensors
authorswithroles_txt_mv	Xin Luo @@aut@@ Dan Chen @@aut@@ Yongjun Wang @@aut@@ Peidai Xie @@aut@@
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callnumber-first	T - Technology
author	Xin Luo
spellingShingle	Xin Luo misc TP1-1185 misc message clustering misc protocol reverse engineering misc Internet of Things misc information security misc Chemical technology A Type-Aware Approach to Message Clustering for Protocol Reverse Engineering
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topic_title	TP1-1185 A Type-Aware Approach to Message Clustering for Protocol Reverse Engineering message clustering protocol reverse engineering Internet of Things information security
topic	misc TP1-1185 misc message clustering misc protocol reverse engineering misc Internet of Things misc information security misc Chemical technology
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title	A Type-Aware Approach to Message Clustering for Protocol Reverse Engineering
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title_full	A Type-Aware Approach to Message Clustering for Protocol Reverse Engineering
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title_auth	A Type-Aware Approach to Message Clustering for Protocol Reverse Engineering
abstract	Protocol Reverse Engineering (PRE) is crucial for information security of Internet-of-Things (IoT), and message clustering determines the effectiveness of PRE. However, the quality of services still lags behind the strict requirement of IoT applications as the results of message clustering are often coarse-grained with the intrinsic type information hidden in messages largely ignored. Aiming at this problem, this study proposes a type-aware approach to message clustering guided by type information. The approach regards a message as a combination of n-grams, and it employs the Latent Dirichlet Allocation (LDA) model to characterize messages with types and n-grams via inferring the type distribution of each message. The type distribution is finally used to measure the similarity of messages. According to this similarity, the approach clusters messages and further extracts message formats. Experimental results of the approach against Netzob in terms of a number of protocols indicate that the correctness and conciseness can be significantly improved, e.g., figures 43.86% and 3.87%, respectively for the CoAP protocol.
abstractGer	Protocol Reverse Engineering (PRE) is crucial for information security of Internet-of-Things (IoT), and message clustering determines the effectiveness of PRE. However, the quality of services still lags behind the strict requirement of IoT applications as the results of message clustering are often coarse-grained with the intrinsic type information hidden in messages largely ignored. Aiming at this problem, this study proposes a type-aware approach to message clustering guided by type information. The approach regards a message as a combination of n-grams, and it employs the Latent Dirichlet Allocation (LDA) model to characterize messages with types and n-grams via inferring the type distribution of each message. The type distribution is finally used to measure the similarity of messages. According to this similarity, the approach clusters messages and further extracts message formats. Experimental results of the approach against Netzob in terms of a number of protocols indicate that the correctness and conciseness can be significantly improved, e.g., figures 43.86% and 3.87%, respectively for the CoAP protocol.
abstract_unstemmed	Protocol Reverse Engineering (PRE) is crucial for information security of Internet-of-Things (IoT), and message clustering determines the effectiveness of PRE. However, the quality of services still lags behind the strict requirement of IoT applications as the results of message clustering are often coarse-grained with the intrinsic type information hidden in messages largely ignored. Aiming at this problem, this study proposes a type-aware approach to message clustering guided by type information. The approach regards a message as a combination of n-grams, and it employs the Latent Dirichlet Allocation (LDA) model to characterize messages with types and n-grams via inferring the type distribution of each message. The type distribution is finally used to measure the similarity of messages. According to this similarity, the approach clusters messages and further extracts message formats. Experimental results of the approach against Netzob in terms of a number of protocols indicate that the correctness and conciseness can be significantly improved, e.g., figures 43.86% and 3.87%, respectively for the CoAP protocol.
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title_short	A Type-Aware Approach to Message Clustering for Protocol Reverse Engineering
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