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Keyword: Network trafficEnhancing the Network Anomaly Detection using CNN-Bidirectional LSTM Hybrid Model and Sampling Strategies for Imbalanced Network Traffic Data
The cybercriminal utilized the skills and freely available tools to breach the networks of internet-connected devices by exploiting confidentiality, integrity, and availability. Network anomaly detection is crucial for ensuring the security of information resources. Detecting abnormal network behavior poses challenges because of the extensive data, imbalanced attack class nature, and the abundance of features in…
Read MoreOptimizing the Performance of Network Anomaly Detection Using Bidirectional Long Short-Term Memory (Bi-LSTM) and Over-sampling for Imbalance Network Traffic Data
Cybercriminal exploits integrity, confidentiality, and availability of information resources. Cyberattacks are typically invisible to the naked eye, even though they target a wide range of our digital assets, such as internet-connected smart devices, computers, and networking devices. Implementing network anomaly detection proves to be an effective method for identifying these malicious activities. The traditional anomaly…
Read MoreInsight into the IEEE 802.1 Qcr Asynchronous Traffic Shaping in Time Sensitive Network
TSN is an attractive solution for latency-critical frame transmission built upon IEEE 802 architecture. Traffic scheduling and shaping in TSN aim to achieve bounded low latency and zero congestion loss. However, the most widespread solution (i.e. Time-Aware Shaper) requires a networkwide precision clock reference and only targets on cyclical traffic flows. This paper focuses on…
Read MoreNonlinear \(\ell_{2,p}\)-norm based PCA for Anomaly Network Detection
Intrusion detection systems are well known for their ability to detect internal and external intrusions, it usually recognizes intrusions through learning the normal behaviour of users or the normal traffic of activities in the network. So, if any suspicious activity or behaviour is detected, it informs the users of the network. Nonetheless, intrusion detection system…
Read MoreFuzzy Logic Implementation for Enhanced WCDMA Network Using Selected KPIs
The paper focused on the implementation of fuzzy logic technology for improved Wideband Code Division Multiple Access (WCDMA) network using selected Key Performance Indicators (KPIs). Empirical and analytical methods were principally deployed for the study analyses. Empirical analyses were conducted on two designated networks which are MTN and AIRTEL observed with high network traffic to…
Read MoreEffectiveness of Routing Protocols for Different Networking Scenarios
Selection of a routing protocol is vital for modern arena of Internet communication as network traffic and network complexities are rapidly increasing. This paper evaluates the effectiveness of three routing protocols namely routing information protocol version 2 (RIPv2), open shortest path first (OSPF), enhanced interior gateway routing protocol (EIGRP), and hybrid protocols based on these…
Read MoreAnalysis of Wireless Traffic Data through Machine Learning
The paper presents an analytical study on a wireless traffic dataset carried out under the different approaches of machine learning including the backpropagation feedforward neural network, the time-series NARX network, the self-organizing map and the principal component analyses. These approaches are well-known for their usefulness in the modeling and in transforming a high dimensional data…
Read MoreNetwork Intrusion Detection System using Apache Storm
Network security implements various strategies for the identification and prevention of security breaches. Network intrusion detection is a critical component of network management for security, quality of service and other purposes. These systems allow early detection of network intrusion and malicious activities; so that the Network Security infrastructure can react to mitigate these threats. Various…
Read MoreImproved Nonlinear Fuzzy Robust PCA for Anomaly-based Intrusion Detection
Among the most popular tools in security field is the anomaly based Intrusion Detection System (IDS), it detects intrusions by learning to classify the normal activities of the network. Thus if any abnormal activity or behaviour is recognized it raises an alarm to inform the users of a given network. Nevertheless, IDS is generally susceptible…
Read MoreSecured Multi-Layer Blockchain Framework for IoT Aggregate Verification
Technologies designed for digital provenance, especially the Internet of Things (IoT) and blockchain, may allow for security, transparency, and traceability in the global supply chain. However, upstream nodes in the supply chain that work for large-scale production suppliers are not considered. In addition, most IoT blockchain systems adopt an ID-based signature scheme that may affect…
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