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Research focused on training and testing of dataset after Optimizing Software Component with the help of deep neural network mechanism. Optimized components are selected for training and testing to improve the accuracy at the time of software selection. Selected components are required to be attuned and accommodating as per requirement. Soft computing mechanism such as…

The Anopheles gambiae’s CYP6Z3 protein belongs to the Cytochrome P450 family and functions in oxidation-reduction processes, many studies including our previous work on elucidating insecticide resistance genes of the Anopheles also implicated her in pyrethroid insecticide resistance. Model prediction, functional analysis, and enrichment of the target gene with triplex binding sites may become a useful…

Rated a high-risk cyber-attack type, Advanced Persistent Threat (APT) has become a cause for concern to cyber security experts. Detecting the presence of APT in order to mitigate this attack has been a major challenge as successful attacks to large organizations still abound. Our approach combines static rule anomaly detection through pattern recognition and machine…

Android Operating system (OS) has been used much more than all other mobile phone’s OS turning android OS to a major point of attack. Android Application installation serves as a major avenue through which attacks can be perpetrated. Permissions must be first granted by the users seeking to install these third-party applications. Some permissions can…

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…

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…

This paper proposes a computationally intelligent algorithm for extracting relevant features from a training set. An optimal subset of features is extracted from training examples of network intrusion datasets. The Support Vector Machine (SVM) algorithm is used as the cost function within the thermal equilibrium loop of the Simulated Annealing (SA) algorithm. The proposed fusion…

It is high time to control and prevent power theft by manipulating the meter reading and tampering of the meter. It is possible to deal power theft by developing Advanced Metering Infrastructure (AMI) and smart grids. For most of the distribution companies, utility smart meters’ data is serving as wealthy source of information beyond billing.…

This paper is an extension of work originally presented in WITS-2017 CONF. We extend our previous works by improving the Risk calculation formula, and risk assessment of an alert cluster instead of every single alert. Also, we presented the initial results of the implementation of our model based on risk assessment and alerts prioritization. The…

A wormhole attack is one of the most critical and challenging security threats for wireless sensor networks because of its nature and ability to perform concealed malicious activities. This paper proposes an innovative wormhole detection scheme to detect wormhole attacks using computational intelligence and an artificial neural network (ANN). Most wormhole detection schemes reported in…