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2020-06-29
Sultana, Subrina, Nasrin, Sumaiya, Lipi, Farhana Kabir, Hossain, Md Afzal, Sultana, Zinia, Jannat, Fatima.  2019.  Detecting and Preventing IP Spoofing and Local Area Network Denial (LAND) Attack for Cloud Computing with the Modification of Hop Count Filtering (HCF) Mechanism. 2019 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2). :1–6.
In today's world the number of consumers of cloud computing is increasing day by day. So, security is a big concern for cloud computing environment to keep user's data safe and secure. Among different types of attacks in cloud one of the harmful and frequently occurred attack is Distributed Denial of Service (DDoS) attack. DDoS is one type of flooding attack which is initiated by sending a large number of invalid packets to limit the services of the victim server. As a result, server can not serve the legitimate requests. DDoS attack can be done by a lot of strategies like malformed packets, IP spoofing, smurf attack, teardrop attack, syn flood attack, local area network denial (LAND) attack etc. This paper focuses on IP spoofing and LAND based DDoS attack. The objective of this paper is to propose an algorithm to detect and prevent IP spoofing and LAND attack. To achieve this objective a new approach is proposed combining two existing solutions of DDoS attack caused by IP spoofing and ill-formed packets. The proposed approach will provide a transparent solution, filter out the spoofed packets and minimize memory exhaustion through minimizing the number of insertions and updates required in the datatable. Finally, the approach is implemented and simulated using CloudSim 3.0 toolkit (a virtual cloud environment) followed by result analysis and comparison with existing algorithms.
2015-05-06
Mukaddam, A., Elhajj, I., Kayssi, A., Chehab, A..  2014.  IP Spoofing Detection Using Modified Hop Count. Advanced Information Networking and Applications (AINA), 2014 IEEE 28th International Conference on. :512-516.

With the global widespread usage of the Internet, more and more cyber-attacks are being performed. Many of these attacks utilize IP address spoofing. This paper describes IP spoofing attacks and the proposed methods currently available to detect or prevent them. In addition, it presents a statistical analysis of the Hop Count parameter used in our proposed IP spoofing detection algorithm. We propose an algorithm, inspired by the Hop Count Filtering (HCF) technique, that changes the learning phase of HCF to include all the possible available Hop Count values. Compared to the original HCF method and its variants, our proposed method increases the true positive rate by at least 9% and consequently increases the overall accuracy of an intrusion detection system by at least 9%. Our proposed method performs in general better than HCF method and its variants.