It is known to all that mobile ad hoc network (MANET) is more vulnerable to all sorts of malicious attacks which affects the reliability of data transmission because the network has the characteristics of wireless, multi-hop, etc. We put forward novel approach of distributed & adaptive trust metrics for MANET in this paper. Firstly, the method calculates the communication trust by using the number of data packets between nodes, and predicts the trust based on the trend of this value, and calculates the comprehensive trust by considering the history trust with the predict value; then calculates the energy trust based on the residual energy of nodes and the direct trust based on the communication trust and energy trust. Secondly, the method calculates the recommendation trust based on the recommendation reliability and the recommendation familiarity; adopts the adaptive weighting, and calculates the integrate direct trust by considering the direct trust with recommendation trust. Thirdly, according to the integrate direct trust, considering the factor of trust propagation distance, the indirect trust between nodes is calculated. The feature of the proposed method is its ability to discover malicious nodes which can partition the network by falsely reporting other nodes as misbehaving and then proceeds to protect the network. Simulation experiments and tests of the practical applications of MANET show that the proposed approach can effectively avoid the attacks of malicious nodes, besides, the calculated direct trust and indirect trust about normal nodes are more conformable to the actual situation.

Novel approach of distributed & adaptive trust metrics for MANET

Statistical vertical reduction‐based data abridging technique for big network traffic dataset

Wireless sensor networks (WSNs) have been vastly employed in the collection and transmission of data via wireless networks. This type of network is nowadays used in many applications for surveillance activities in various environments due to its low cost and easy communications. In these networks, the sensors use a limited power source which after its depletion, since it is non-renewable, network lifetime ends. Due to the weaknesses in sensor nodes, they are vulnerable to many threats. One notable attack threating WSN is Denial of Sleep (DoS). DoS attacks denotes the loss of energy in these sensors by keeping the nodes from going into sleep and energy-saving mode. In this paper, the Abnormal Sensor Detection Accuracy (ASDA-RSA) method is utilised to counteract DoS attacks to reducing the amount of energy consumed. The ASDA-RSA schema in this paper consists of two phases to enhancement security in the WSNs. In the first phase, a clustering approach based on energy and distance is used to select the proper cluster head and in the second phase, the RSA cryptography algorithm and interlock protocol are used here along with an authentication method, to prevent DoS attacks. Moreover, ASDA-RSA method is evaluated here via extensive simulations carried out in NS-2. The simulation results indicate that the WSN network performance metrics are improved in terms of average throughput, Packet Delivery Ratio (PDR), network lifetime, detection ratio, and average residual energy.

Securing Wireless Sensor Networks Against Denial‐of‐Sleep Attacks Using RSA Cryptography Algorithm and Interlock Protocol

Electronic commerce or e-commerce includes the service and good exchange through electronic support like the Internet It plays a crucial role in today's business and users' experience Also, e-commerce platforms produce a vast amount of information So, Recommender Systems (RSs) are a solution to overcome the information overload problem They provide personalized recommendations to improve user satisfaction The present article illustrates a comprehensive and Systematic Literature Review (SLR) regarding the papers published in the field of e-commerce recommender systems We reviewed the selected papers to identify the gaps and significant issues of the RSs' traditional methods, which guide the researchers to do future work So, we provided the traditional techniques, challenges, and open issues concerning traditional methods of the field of review based on the selected papers This review includes five categories of the RSs' algorithms, including Content-Based Filtering (CBF), Collaborative Filtering (CF), Demographic-Based Filtering (DBF), hybrid filtering, and Knowledge-Based Filtering (KBF) Also, the salient points of each selected paper are briefly reported The publication time of the selected papers ranged from 2008 to 2019 Also, we provided a comparison table of important issues of the selected papers as well as the tables of advantages and disadvantages Moreover, we provided a comparative table of metrics and review issues for the selected papers And finally, the conclusions can, to a great extent, provide valuable guidelines for future studies

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A Systematic Study on the Recommender Systems in the E-Commerce

In WSN-assisted IoT, energy efficiency and security which play pivotal role in Quality of Service (QoS) are still challenging due to its open and resource constrained nature Although many research works have been held on WSN-IoT, none of them is able to provide high-level security with energy efficiency This paper resolves this problem by designing a novel Secure Deep Learning (SecDL) approach for dynamic cluster-based WSN-IoT networks To improve energy efficiency, the network is designed to be Bi-Concentric Hexagons along with Mobile Sink technology Dynamic clusters are formed within Bi-Hex network and optimal cluster heads are selected by Quality Prediction Phenomenon (QP2) that ensure QoS and also energy efficiency Data aggregation is enabled in each cluster and handled with a Two-way Data Elimination then Reduction scheme A new One Time-PRESENT (OT-PRESENT) cryptography algorithm is designed to achieve high-level security for aggregated data Then, the ciphertext is transmitted to mobile sink through optimal route to ensure high-level QoS For optimal route selection, a novel Crossover based Fitted Deep Neural Network (Co-FitDNN) is presented This work also concentrates on IoT-user security since the sensory data can be accessed by IoT users This work utilizes the concept of data mining to authenticate the IoT users All IoT users are authenticated by Apriori based Robust Multi-factor Validation algorithm which maps the ideal authentication feature set for each user In this way, the proposed SecDL approach achieves security, QoS and energy efficiency Finally, the network is modeled in ns-326 and the results show betterment in network lifetime, throughput, packet delivery ratio, delay and encryption time

SecDL: QoS-Aware Secure Deep Learning Approach for Dynamic Cluster-Based Routing in WSN Assisted IoT

Summary
Social network sites (SNS) presently face the task of grouping users into small subsets within themselves. In this study, an organizing scheme for single-topic user groups is proposed for facilitating user sharing and communicating under common interests. The main rationales of the proposed scheme are (1) only an influential single topic is selected through its impact evaluation to attract users; (2) only the users having high degree of interest, explicit or implicit, on the topic should be grouped; and (3) trustworthy relationships among users are taken into consideration to enlarge the scale of user group. The proposed organizing scheme comprises 3 features: topic impact evaluation, interest degree measurement, and trust chain-based organizing. The main structure of our proposed scheme is (1) an overview of the proposed scheme and its formal related definitions; (2) a topic impact evaluation method, ie, an importance evaluation and a popularity calculation; (3) a user interest degree measurement method, ie, explicit and implicit interest evaluation with dynamic factors included; (4) a trust chain calculation method based on the topology features of the trust chain; (5) an organizing algorithm for single topic user group, and finally, some experimental results and discussions to illustrate the effectiveness and feasibility of our scheme.

Fazhuan Wei

Papers

A novel organizing scheme of single topic user group based on trust chain model in social network