Journal of Cybersecurity and Information Management

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2690-6775ISSN (Online) 2769-7851ISSN (Print)

Intelligent Feature Subset Selection with Machine Learning based Risk Management for DAS Prediction

Mohamed Abdel-Basset , Mohamed Elhoseny

In the current epidemic situations, people are facing several mental disorders related to Depression, Anxiety, and Stress (DAS). Numerous scales are developed for computing the levels for DAS, and DAS-21 is one among them. At the same time, machine learning (ML) models are applied widely to resolve the classification problem efficiently, and feature selection (FS) approaches can be designed to improve the classifier results. In this aspect, this paper develops an intelligent feature selection with ML-based risk management (IFSML-RM) for DAS prediction. The IFSML-RM technique follows a two-stage process: quantum elephant herd optimization-based FS (QEHO-FS) and decision tree (DT) based classification. The QEHO algorithm utilizes the input data to select a valuable subset of features at the primary level. Then, the chosen features are fed into the DT classifier to determine the existence or non-existence of DAS. A detailed experimentation process is carried out on the benchmark dataset, and the experimental results showcased the betterment of the IFSML-RM technique in terms of different performance measures. 

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Vol. 8 Issue. 1 PP. 08-16, (2021)

Modeling of Deep Learning based Intrusion Detection System in Internet of Things Environment

Mohammad Hammoudeh , Saeed M. Aljaberi

The Internet of Things (IoT) has become a hot popular topic for building a smart environment. At the same time, security and privacy are treated as significant problems in the real-time IoT platform. Therefore, it is highly needed to design intrusion detection techniques for accomplishing security in IoT. With this motivation, this study designs a novel flower pollination algorithm (FPA) based feature selection with a gated recurrent unit (GRU) model, named FPAFS-GRU technique for intrusion detection in the IoT platform. The proposed FPAFS-GRU technique is mainly designed to determine the presence of intrusions in the network. The FPAFS-GRU technique involves the design of the FPAFS technique to choose an optimal subset of features from the networking data. Besides, a deep learning based GRU model is applied as a classification tool to identify the network intrusions. An extensive experimental analysis takes place on KDDCup 1999 dataset, and the results are investigated under different dimensions. The resultant simulation values demonstrated the betterment of the FPAFS-GRU technique with a higher detection rate of 0.9976.

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Vol. 8 Issue. 1 PP. 17-25, (2021)

Deep Learning Model for Digital Sales Increasing and Forecasting: Towards Smart E-Commerce

Ahmad Freij, Khalid Walid, Mohammad Mustafa

In this paper, we have proposed a system that will be able to forecast the sales of the e-commerce systems by using the techniques of the deep learning, the main goal of this paper is to help the business and the top management level of the company in decision making in order to provide the workplace the effectiveness and the efficiency in the workplace and to provide an efficient and effective system that it is intelligence to forecast and increase the sales of an e-commerce system, this paper will start with building an e-commerce website using different programming languages which are HTML, CSS, Django, JavaScript Bootstrap, and it this e-commerce website will have a specific database that contains different tables for the product list, the orders, and for the user information and many other tables, then the deep learning algorithms such as Deep Belief Networks and Convolutional Neural Networks will be applied in order to provide an effective system for digital marketing usage, so, it will be able to function as a marketing manager. 

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Vol. 8 Issue. 1 PP. 26-34, (2021)

Cybersecurity in Networking Devices

Afroj Jahan Badhon , Dr. Shruti Aggarwal

Cybersecurity is training defensive arrangements, systems, and plans to save the information from cyber outbreaks. These virtual outbreaks are typically intended to retrieve, alter, or otherwise extinguish delicate data, extracting currency from manipulators, or disturb usual commercial procedures. System Security defends one’s system and information from breaks, interruptions also other intimidations. Network Security contains admission controller, computer virus and defiant computer virus software program, system safety, system analytics, system-connected protection categories, firewalls, and VPN encoding. System substructure strategies stand the mechanisms of a net that conveyance transportations desired intended for information, submissions, facilities, and multimedia. In this paper, we reflect on Cybersecurity in Networking Devices. 

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Vol. 8 Issue. 1 PP. 35-41, (2021)

An Improved Image Encryption Consuming Fusion Transmutation and Edge Operator

Vandana Roy

The field of cryptography oversees the development of methods for transforming information between coherent and incoherent formats. Encryption and decryption techniques controlled by keys maintain the privacy of the substance and who can access it. Private key cryptography refers to methods of encryption and decryption that employ the same secret key. The alternative is public key cryptography, wherever the encryption and decryption keys are different. It is essential for the sanctuary of any crypto scheme that the confusion and diffusion properties be met. While the diffusion property rearranges the pixels in an image, the confusion property simply replaces the pixel values. In-depth discussion of a genetic-algorithm-based hybrid approach to secure and complex three-dimensional chaos-based image encryption (SCIE) has been presented. Here, we use mathematics edge, multipoint edges operator, and coupled transmutation operatives to accomplish permutation. In this method, a key stream is created using a 3D CSI (Compound Sine and ICMIC) map. Using a private key, hybrid operators are used to encrypt data. Several metrics were considered while evaluating the suggested algorithm's efficacy, including the UACI (Unified Average Change Intensity), correlation constant, NPCR (Net Pixel Change Rate). Experiments with the same have shown promising results in protecting real-time photos.

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Vol. 8 Issue. 1 PP. 42-52, (2021)