Journal ArticleDOI
A Distributed Intrusion Detection System with Protection from an Internal Intruder
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TLDR
A model of data processing in the DIDS and method of using of hidden agents to protect from an internal intruder and a method of hiding of presence of the agent from the system user while retaining control of it from the part of the operator are described.Abstract:
The protection of modern distributed information networks from external and internal intruders continues to be of great importance due to the development of data transmission and processing technology. The article describes a model of data processing in the distributed intrusion detection system (DIDS) and method of using of hidden agents to protect from an internal intruder. The distribution of the functions on data processing between the DIDS local agent and central data processing node is presented. We describe a method of hiding of presence of the agent from the system user while retaining control of it from the part of the operator.read more
Citations
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Journal ArticleDOI
Classifier Performance Evaluation for Lightweight IDS Using Fog Computing in IoT Security
Belal Sudqi Khater,Ainuddin Wahid Abdul Wahab,Mohd Yamani Idna Idris,Mohammed Hussain,Ashraf Ahmed Ibrahim,Mohammad Arif Amin,Hisham A. Shehadeh +6 more
TL;DR: A Host-Based Intrusion Detection System (HIDS) using a Modified Vector Space Representation N-gram and Multilayer Perceptron (MLP) model for securing the Internet of Things (IoT), based on lightweight techniques and using Fog Computing devices, is proposed.
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Big Data Management System Security Threat Model
TL;DR: The article describes changes in the intruder model and new vulnerabilities in data management systems and presents new problems of information security in a distributed Big Data processing and storage system.
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Comparative Review of the Intrusion Detection Systems Based on Federated Learning: Advantages and Open Challenges
TL;DR: The architecture of the proposed intrusion detection systems and the approaches used to model data partition across the clients are analyzed, and their advantages as well as open challenges still facing them are studied.
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An Approach for Stego-Insider Detection Based on a Hybrid NoSQL Database
TL;DR: The paper provides a review of the related works in terms of insider models and methods of their identification, including techniques for handling insider attacks in WSN, as well methods of embedding and detection of stego-embeddings.
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A Consistent Approach to Building Secure Big Data Processing and Storage Systems
TL;DR: This article considers the solution to the problem of building secure Big Data management systems using a consistent approach using the principles of a new, consistent approach and the security subsystem architecture is proposed.
References
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Deep learning applications and challenges in big data analytics
Maryam M. Najafabadi,Flavio Villanustre,Taghi M. Khoshgoftaar,Naeem Seliya,Randall Wald,Edin Muharemagic +5 more
TL;DR: This study explores how Deep Learning can be utilized for addressing some important problems in Big Data Analytics, including extracting complex patterns from massive volumes of data, semantic indexing, data tagging, fast information retrieval, and simplifying discriminative tasks.
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Intrusion detection systems and multisensor data fusion
TL;DR: The vast majority of security professionals would agree that real-time ID systems are not technically advanced enough to detect sophisticated cyberattacks by trained professionals, but these systems have not matured to a level where sophisticated attacks are reliably detected, verified, and assessed.
Proceedings ArticleDOI
An architecture for intrusion detection using autonomous agents
TL;DR: This paper reviews the architecture for a distributed intrusion detection system based on multiple independent entities working collectively, and calls these entities autonomous agents, which solves some of the problems previously mentioned.
Journal ArticleDOI
Anomaly-based intrusion detection system through feature selection analysis and building hybrid efficient model
TL;DR: A new hybrid model can be used to estimate the intrusion scope threshold degree based on the network transaction data’s optimal features that were made available for training and revealed that the hybrid approach had a significant effect on the minimisation of the computational and time complexity involved when determining the feature association impact scale.
Book
DIDS (distributed intrusion detection system)—motivation, architecture, and an early prototype
Steven R. Snapp,James Brentano,Gihan Dias,Terrance L. Goan,L. Todd Heberlein,Che-Lin Ho,Karl Levitt,Biswanath Mukherjee,Stephen E. Smaha,Tim Grance,Daniel M. Teal,Doug Mansur +11 more
TL;DR: An overview of the motivation behind DIDS, the system architecture and capabilities, and a discussion of the early prototype of the DIDS is provided.
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