2019
DOI: 10.1155/2019/5483918
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HeteMSD: A Big Data Analytics Framework for Targeted Cyber-Attacks Detection Using Heterogeneous Multisource Data

Abstract: In the current enterprise network environment, multistep targeted cyber-attacks with concealment and advanced characteristics have become the main threat. Multisource security data are the prerequisite of targeted cyber-attacks detection. However, these data have characters of heterogeneity and semantic diversity, and existing attack detection methods do not take comprehensive data sources into account. Identifying and predicting attack intention from heterogeneous noisy data can be meaningful work. In this pa… Show more

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Cited by 17 publications
(10 citation statements)
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References 13 publications
(13 reference statements)
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“…A total of 1512 papers published in journals and conferences were downloaded using keywords search in Google scholar. The downloaded papers were screened through several stages, and the final selected papers (140) were reviewed based on a proposed taxonomy. Based on the analysis we have presented in previous subsections and the summarised information in Tables 2 and A1 and Figs.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…A total of 1512 papers published in journals and conferences were downloaded using keywords search in Google scholar. The downloaded papers were screened through several stages, and the final selected papers (140) were reviewed based on a proposed taxonomy. Based on the analysis we have presented in previous subsections and the summarised information in Tables 2 and A1 and Figs.…”
Section: Discussionmentioning
confidence: 99%
“…[139] NS Developed a multiple BDA platform with rapid response NA 66. [140] Cybersecurity A BDA framework for detecting targeted cyber-attacks NA Note: NA = Not Applicable; NS = Not Specified (authors did not make known the industry where their data came from).…”
Section: No Reference Application Areamentioning
confidence: 99%
“…After checking the hash's value below the target value, the PoW is verified as a successful transaction and then added to the block [65]. Subsequently, an update notification concerning this change of the blockchain size is broadcasted to the whole network for the ledger to inform every connected nodes [66].…”
Section: Blockchain Standardizationsmentioning
confidence: 99%
“…Caspian State Univ,KZ & European Univ,UA [80] Nash Equilibrium Univ Sydney,AU & Univ New South Wales,AU [113]; Hong-Kong Univ,CN & Zhejiang Univ,CN & Univ. Newcastle,UK [94]; Univ Bristol, UK [64] Two-stage Min-Max ETH,CH & Univ Tech Sydney,AU [75] Continued on next page [23]; Macquarie Univ,AU [31] Security Objectives Beijing Univ,CN [133] Taxonomy & Propagation Univ Oxford,UK [51] Machine General NUST,PK & Fontbonne Univ,US & IIUI,PK [38]; Zhengzhou Int Informat Sci & Tech,CN [56]; UTP Univ Sci Technol,PL & Fern Univ,DE [134]; Thapar Univ,IN [79]; Northeastern Univ, CN [128] Learning Data Mining and Classification Univ Tun Hussein Onn,MY [68] Deep Learning Illinois State Univ, US & Univ Texas, US [135] Robust Regression Takyo Inst Tech,JP [17] Text Analysis -Nat. Lang.…”
Section: Bi-linear Differential Qualitymentioning
confidence: 99%