The application of cloud computing has increased tremendously in both public and private organizations. However, attacks on cloud computing pose a serious threat to confidentiality and data integrity. Therefore, there is a need for a proper mechanism for detecting cloud intrusions. In this paper, we have proposed a cloud intrusion detection system (IDS) that is focused on boosting the classification accuracy by improving feature selection and weighing the ensemble model with the crow search algorithm (CSA). The feature selection is handled by combining both filter and automated models to obtain improved feature sets. The ensemble classifier is made up of machine and deep learning models such as long short-term memory (LSTM), support vector machine (SVM), XGBoost, and a fast learning network (FLN). The proposed ensemble model’s weights are generated with the CSA to obtain better prediction results. Experiments are executed on the NSL-KDD, Kyoto, and CSE-CIC-IDS-2018 datasets. The simulation shows that the suggested system attained more satisfactory results in terms of accuracy, recall, precision, and F-measure than conventional approaches. The detection rate and false alarm rate (FAR) of different attack types was more efficient for each dataset. The classifiers’ performances were also compared individually to the ensemble model in terms of the false positive rate (FPR) and false negative rate (FNR) to demonstrate the ensemble model’s robustness.
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This paper presents a detailed study of the mechanism to design a compiler of Smali language to generate optimized Android applications. Smali language; which includes the dex bytecode; is the assembly language under Android OS, it is generated from the Java source code. The phases of designing the target compiler are described and the structure of files that are the input and output of the compiler are explained.
Routing in Mobile Ad Hoc Networks (MANETs) is very important because they are infrastructure-less, so the routing protocol in these networks works on each node. If routing protocols do not work properly, the network will stop. In these networks, there is no centralized control or server to control the activities of nodes, so they are more vulnerable to many security risks and attacks such as the black hole attack and the gray hole attack. In this paper, the proposed Defensive AODV protocol (DAODV) is used to defend against these attack using the V-Detector algorithm which is an artificial immune system algorithm. The results show that the proposed DAODV provides much better performance than the normal AODV in the presence of malicious nodes in the network.
In this paper, a Stable, Thermal-aware and Energy-efficient routing Protocol (STEP) is proposed for Wireless Body Area Networks (WBANs) that not only deals with the thermal aspects and hot-spots problem but also saves energy and extends the stability period and network lifetime. Direct communication is used for real-time traffic (critical data) while multi-hop communication is used for normal data delivery. In multi-hop communication to achieve minimum power consumption and minimum temperature rise, the proposed protocol has a new cost function using multi-criteria decision making MCDM methods to determine the parent node or the forwarder. These methods provide a flexible decision-making process for selecting the next hop by considering different criteria at the same time. The proposed cost function has three criteria: residual energy, distance to the sink node and temperature. Residual energy criterion balances the energy consumption among the sensor nodes while distance criterion ensures successful packet delivery to the sink node and minimize the energy that will be consumed, the temperature criterion will avoid routing across hot nodes to protect the tissues. The simulation results show that the proposed protocol preserves the energy and increases the network lifetime & stability period so nodes stay alive for a longer period. A longer stability period contributes significantly to the delivery of packets, which is very important for continuous patient monitoring. Results also depict that the proposed protocol can achieve a better balance of the temperature rise comparing to the previous protocols.
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