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El-Rabaie, El-Sayed M.
- Statistical Behavior of Packet Counts for Network Intrusion Detection
Authors
1 Department of Electronics and Communications, Menoufia University, Menouf, EG
2 Department of Electronics and Communications, Menoufia University, Menouf-32952, EG
3 Department of Electronics and Communications, Menoufia University, Menouf-32952, EG
Source
Networking and Communication Engineering, Vol 6, No 6 (2014), Pagination: 249-252Abstract
Intrusions and attacks have become a very serious problem in network world. This paper presents a statistical characterization of packet counts that can be used for network intrusion detection. The main idea is based on detecting any suspicious behavior in computer networks depending on the comparison between the correlation results of control and data planes in the presence and absence of attacks using histogram analysis. Signal processing tools such as median filtering, moving average filtering, and local variance estimators are exploited to help in developing network anomaly detection approaches. Therefore, detecting dissimilarity can indicate an abnormal behavior.Keywords
Anomaly Detection, Statistics, Network Intrusion Detection Systems (NIDS).
- On the Estimation of Attacks in Computer Networks with an AR Approach
Authors
1 Menoufia University, Menouf, EG
2 Department of Electronics and Communications, Menoufia University, Menouf-32952, EG
Source
Networking and Communication Engineering, Vol 6, No 1 (2014), Pagination: 12-15Abstract
This Paper proposes a network based intrusion detection approach using anomaly detection in the presence of Denial of Service attacks (DoS). Flood based attacks are a common class of DoS attacks. DoS detection mechanisms that aim at detecting floods mainly look for sudden changes in the traffic and mark them anomalous. In this approach, network traffic is decomposed into control and data planes to study the relationship between them. As the data traffic generation is based on control traffic, the behavior of the two planes is expected to be similar during normal behavior. Therefore, detecting dissimilarity between the traffic of the two planes can indicate an abnormal behavior. Toward that objective, an Auto Regressive (AR) model has been used. Simulation results show that both the accuracy of the detection and less false positives.Keywords
Auto Regressive (AR), Denial-of-Service (DoS), Network Intrusion Detection Systems (NIDS).- Enhanced PF Scheduling Algorithm for LTE Downlink System
Authors
1 Department of Electronics and Electrical Communications, Menoufia University, Menouf, 32952, EG
Source
Networking and Communication Engineering, Vol 5, No 12 (2013), Pagination: 505-509Abstract
A key feature of Long Term Evolution (LTE) system is the adoption of advanced Radio Resource Management (RRM) procedures in order to increase the system performance. Packet scheduling mechanisms play a fundamental role, because they are responsible for choosing how to distribute radio resources among different stations. In this paper a modified Proportional Fair (PF) scheduling algorithm is proposed for capacity enhancement for LTE system and compared with the PF downlink scheduler, which is characterized by high fairness but with low spectral efficiency. Simulation results show that the proposed algorithm enhances the overall system capacity and also provides fairness in the distribution of the resources. The proposed algorithm improves the average cell throughput by more than 10.3 %, with approximately the same fairness level (2.6 % reduction) as compared with the conventional PF scheduling algorithm.