anomaly-based detection systems
DETECTION ENVIRONMENT FORMATION METHOD FOR ANOMALY DETECTION SYSTEMS
... high detection rate with low false positive and false negative alarms, are major success factors for security ...applied based social relations model and the socio-technical design paradigm ...[1]. ...
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DETECTION ENVIRONMENT FORMATION METHOD FOR ANOMALY DETECTION SYSTEMS
... The current KMS is built in a web-based and supported with cloud infrastructure. The KMS is maintained in operation since it fits with the needs of the company needs. It has advance features to support the work of ...
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A Text Mining-Based Anomaly Detection Model in Network Security
... Abstract- Anomaly detection systems are extensively used security tools to detect cyber-threats and attack activities in computer systems and ...Mining-Based Anomaly ...
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Prevention of Attacks for Key Recovery Using Role Based Access Permissions
... avoid detection, ...intrusion detection systems (IDS) without compromising the functionality of the ...few detection schemes introduced since from few last ...a systems without any ...
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A Survey on Intrusion Detection Systems Prof. Shivendu Dubey, Neha Tripathi
... intrusion detection systems (NIDS) are most efficient way of defending against network-based attacks aimed at computer systems [13, ...These systems are used in almost all large-scale ...
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DETECTION ENVIRONMENT FORMATION METHOD FOR ANOMALY DETECTION SYSTEMS
... IoT. Based on the findings, the ECC algorithm outperforms RSA in a constrained environment in terms of memory requirements, energy consumption, key sizes, signature generation time, key generation and execution ...
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Applying Machine Learning to Anomaly-Based Intrusion Detection Systems
... effective anomaly Intrusion Detection System based on a new hybrid algorithm named neural network with Indicator Variable and Rough Set for attribute Reduction (NNIV-RS) ...
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DETECTION ENVIRONMENT FORMATION METHOD FOR ANOMALY DETECTION SYSTEMS
... Mathematical epidemiology has a long history in the study of infectious diseases. Starting with daniel bernoulli in 1760 when he developed a model for the spread of smallpoxand and established a new analysis of smallpox ...
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Big Data Security Analysis in Network Intrusion Detection System
... intrusion detection system being used and how huge volume of the dataset, its specialized features that are heterogeneous in nature and what will happen if big data is processed at real ...intrusion ...
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An Online Anomaly-Detection Neural Networks-based Clustering for Adaptive Intrusion Detection Systems
... sion detection systems can be of two types of anomaly-based and ...signature-based. Anomaly-based IDSs try to find the abnormal patterns of activities in a system by ...
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Anomaly behaviour detection based on the meta-Morisita index for large scale spatio-temporal data set
... Map algebra [54] is a basic set-based algorithm that manipulates the geospatial data. Several algebraic operations like addition, subtraction, etc. can be performed on two or more raster layers of similar ...
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Research on the Anomaly Detection Method in Intelligent Patrol Based on Big Data Analysis
... DOI: 10.4236/jcc.2019.78001 2 Journal of Computer and Communications has become a key problem to be solved in different industries. In order to meet the needs of daily network patrol work, a large number of intelligent ...
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Explainable Neural Networks based Anomaly Detection for Cyber-Physical Systems
... The development in physical resources and the ability to seamlessly connect with the rapid growth in networking technologies have created opportunities for CPSs in every stratum of modern society. Smart grids, traffic ...
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Network anomaly detection for railway critical infrastructure based on autoregressive fractional integrated moving average
... of the transmission, as well as protection of nodes and data transferred with their use. While developing mecha- nisms, algorithms, or protocols that increase transmis- sion security in WSN, one also needs to consider ...
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Anomaly-Based – Intrusion Detection System using User Profile Generated from System Logs Roshan Pokhrel*, Prabhat Pokharel**, Arun Kumar Timalsina, PhD*
... Intrusion detection is a process of monitoring the events from the computer-based system and investigating them for possible signs of incidents which are violationss of security policies, guideliness, or ...
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Network Intrusion Detection Using Machine Learning Techniques
... traffic anomaly indicates a possible intrusion in the network and therefore anomaly detection is important to detect and prevent the security ...Intrusion Detection Systems (IDS) they ...
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DETECTING SYBIL ATTACK USING HYBRID FUZZY K-MEANS ALGORITHM IN WSN
... researches, anomaly-based intrusion detection systems (ADSs) are well suited to wireless sensor network due to its flexibility and resource friendly ...Further, Anomaly-based ...
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DETECTION ENVIRONMENT FORMATION METHOD FOR ANOMALY DETECTION SYSTEMS
... Artificial bee colony algorithm ABC is a swarm-based metaheuristic algorithm, developed by [55] for numerical problems optimization. The algorithm is interested by the intelligent behavior of honeybees, that is, ...
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A Survey on Anomaly-Based Network Intrusion Detection Systems
... In a flooding attack, an attacker simply sends more requests to a target that it can handle. Such attacks can either exhaust the processing capability of the target or exhaust the network bandwidth of the target, either ...
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DETECTION ENVIRONMENT FORMATION METHOD FOR ANOMALY DETECTION SYSTEMS
... The term e-learning is a new thing, so that it is still actual in the development of education. The term e-learning appears along with the development of the advancement of the world of science and technology and its use ...
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