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      • Intelligent & Predictive Security Deployment in IOT Environments

        Abdul ghani, ansari,Irfana, Memon,Fayyaz, Ahmed,Majid Hussain, Memon,Kelash, Kanwar,fareed, Jokhio International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.12

        The Internet of Things (IoT) has become more and more widespread in recent years, thus attackers are placing greater emphasis on IoT environments. The IoT connects a large number of smart devices via wired and wireless networks that incorporate sensors or actuators in order to produce and share meaningful information. Attackers employed IoT devices as bots to assault the target server; however, because of their resource limitations, these devices are easily infected with IoT malware. The Distributed Denial of Service (DDoS) is one of the many security problems that might arise in an IoT context. DDOS attempt involves flooding a target server with irrelevant requests in an effort to disrupt it fully or partially. This worst practice blocks the legitimate user requests from being processed. We explored an intelligent intrusion detection system (IIDS) using a particular sort of machine learning, such as Artificial Neural Networks, (ANN) in order to handle and mitigate this type of cyber-attacks. In this research paper Feed-Forward Neural Network (FNN) is tested for detecting the DDOS attacks using a modified version of the KDD Cup 99 dataset. The aim of this paper is to determine the performance of the most effective and efficient Back-propagation algorithms among several algorithms and check the potential capability of ANN- based network model as a classifier to counteract the cyber-attacks in IoT environments. We have found that except Gradient Descent with Momentum Algorithm, the success rate obtained by the other three optimized and effective Back- Propagation algorithms is above 99.00%. The experimental findings showed that the accuracy rate of the proposed method using ANN is satisfactory.

      • Exploring Pseudonymous based Schemes for Safegaurding Location Privacy in Vehicular Adhoc Network (VANET)

        Arslan Akhtar Joyo,Fizza Abbas Alvi,Rafia Naz Memon,Irfana Memon,Sajida Parveen International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.2

        Vehicular Ad Hoc Network (VANET) is considered to be a subclass of Mobile Ad Hoc Networks (MANET). It has some challenges and issues of privacy which require to be solved before practical implementation of the system i.e., location preservation privacy. Many schemes have been proposed. The most prominent is pseudonym change based location preservation scheme. Safety message can be compromised when it sends via a wireless medium, consequently, an adversary can eavesdrop the communication to analyze and track targeted vehicle. The issue can be counter by use of pseudo identity instead of real and their change while communication proves to be a sufficient solution for such problems. In this context, a large amount of literature on pseudonym change strategies has been proposed to solve such problems in VANET. In this paper, we have given details on strategies proposed last two decades on pseudonym change based location preservation along with issues that they focus to resolve and try to give full understanding to readers.

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