Journal ArticleDOI
Big Data Analytics for Security
Alvaro A. Cardenas,Pratyusa K. Manadhata,Sreeranga P. Rajan +2 more
- Vol. 11, Iss: 6, pp 74-76
TLDR
Big data is changing the landscape of security tools for network monitoring, security information and event management, and forensics; however, in the eternal arms race of attack and defense, security researchers must keep exploring novel ways to mitigate and contain sophisticated attackers.Abstract:
Big data is changing the landscape of security tools for network monitoring, security information and event management, and forensics; however, in the eternal arms race of attack and defense, security researchers must keep exploring novel ways to mitigate and contain sophisticated attackers.read more
Citations
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Journal ArticleDOI
Techniques and countermeasures for preventing insider threats
TL;DR: A unified classification model is proposed to classify the insider threat prevention approaches into two categories (biometric-based and asset-based metric), which is validated with empirical results utilizing the grounded theory method for rigorous literature review.
Proceedings ArticleDOI
DeapSECURE: Empowering Students for Data- and Compute-Intensive Research in Cybersecurity through Training
TL;DR: The project developed six non-degree training modules to expose cybersecurity students to advanced CI platforms and techniques rooted in big data, machine learning, neural networks, and high-performance programming, which will facilitate widespread adoption, adaptations, and contributions in the cybersecurity community.
Proceedings ArticleDOI
Real time cyber attack analysis on Hadoop ecosystem using machine learning algorithms
TL;DR: An alternative view of "Big Data Cloud" is offered to make this complex technology easy to understand for new researchers and identify gaps efficiently and detected cyber-attacks on Hadoop with 94.0187% accuracy using modern machine learning algorithms.
Journal ArticleDOI
Closing the loop: Network and in-host monitoring tandem for comprehensive cloud security visibility
Stefan Berger,Yangyi Chen,Xin Hu,Dimitrios Pendarakis,Josyula R. Rao,Reiner Sailer,Douglas Lee Schales,Marc Ph. Stoecklin +7 more
TL;DR: This paper proposes a comprehensive approach towards monitoring cloud computing environments by building an awareness framework combining passive network monitoring principles with in-host monitoring, and devised a system using a big data approach combining analytics on both levels.
Journal ArticleDOI
Intrusion Detection for Network Based on Elite Clone Artificial Bee Colony and Back Propagation Neural Network
TL;DR: Wang et al. as discussed by the authors combined back propagation neural network (BPNN) and elite clone artificial bee colony (ECABC) to propose a new ECABC-BPNN, which updates and optimizes the settings of traditional BPNN weights and thresholds.
References
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Proceedings ArticleDOI
Beehive: large-scale log analysis for detecting suspicious activity in enterprise networks
Ting-Fang Yen,Alina Oprea,Kaan Onarlioglu,Todd Leetham,William Robertson,Ari Juels,Engin Kirda +6 more
TL;DR: A novel system, Beehive, that attacks the problem of automatically mining and extracting knowledge from the dirty log data produced by a wide variety of security products in a large enterprise, and is able to identify malicious events and policy violations which would otherwise go undetected.
Proceedings ArticleDOI
Toward a standard benchmark for computer security research: the worldwide intelligence network environment (WINE)
Tudor Dumitras,Darren Shou +1 more
TL;DR: The unique characteristics of the WINE data are reviewed, why rigorous benchmarking will provide fresh insights on the security arms race is discussed, and a research agenda for this area is proposed.
Proceedings ArticleDOI
BotCloud: Detecting botnets using MapReduce
TL;DR: This paper proposes a distributed computing framework that leverages a host dependency model and an adapted PageRank algorithm and reports experimental results from an open-source based Hadoop cluster and highlights the performance benefits when using real network traces from an Internet operator.
Journal Article
Using Large Scale Distributed Computing to Unveil Advanced Persistent Threats
Paul Giura,Wei Wang +1 more
TL;DR: This paper proposes a model of the APT detection problem as well as a methodology to implement it on a generic organization network and shows that this approach is feasible to process very large data sets and is flexible enough to accommodate any context processing algorithm, even to detect sophisticated attacks such as APT.