Aruna Jamdagni

Western Sydney University

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Priyadarsi Nanda

University of Technology Sydney

Xiangjian He

University of Nottingham Ningbo China

Zhiyuan Tan

Edinburgh Napier University

Ren Ping Liu

University of Technology Sydney

Ashish Nanda

St. Clare Hospital in Lakewood

Deepak Puthal

Khalifa University of Science and Technology

Wenjing Jia

University of Technology Sydney

Wei‐Chang Yeh

National Tsing Hua University

Neelam Sinha

Santosh Kumar Nanda

Wipro (India)

Cooperative Institutions

Indian Institute of Technology Bhubaneswar

KIIT University

Indian Institute of Technology Kharagpur

National Institute of Technology Rourkela

International Institute of Information Technology

University of Technology Sydney

Siksha O Anusandhan University

Biju Patnaik University of Technology

Veer Surendra Sai University of Technology

CMR University

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Denial-of-Service Attack Detection Based on Multivariate Correlation Analysis

Lecture notes in computer science (2011)

Zhiyuan Tan Aruna Jamdagni Xiangjian He Priyadarsi Nanda Ren Ping Liu

Correlative

10.1007/978-3-642-24965-5_85

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Citations (50)

Secure-GLOR: An Adaptive Secure Routing Protocol for Dynamic Wireless Mesh Networks

Ashish Nanda Priyadarsi Nanda Xiangjian He Aruna Jamdagni Deepak Puthal

With the dawn of a new era, digital security has become one of the most essential part of any network. Be it a physical network, virtual network or social network, the demand for secure data transmission is ever increasing. Wireless mesh networks also stand the same test of security as the legacy networks. This paper presents a secure version of the Geo-Location Oriented Routing (GLOR) protocol for wireless mesh networks, incorporating a multilevel security framework. It implements authentication using the new features of the network model and enables encryption throughout the network to provide high levels of security.

10.1109/trustcom/bigdatase/icess.2017.247

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A System for Denial-of-Service Attack Detection Based on Multivariate Correlation Analysis

IEEE Transactions on Parallel and Distributed Systems (2013)

Zhiyuan Tan Aruna Jamdagni Xiangjian He Priyadarsi Nanda Ren Ping Liu

Interconnected systems, such as Web servers, database servers, cloud computing servers and so on, are now under threads from network attackers. As one of most common and aggressive means, denial-of-service (DoS) attacks cause serious impact on these computing systems. In this paper, we present a DoS attack detection system that uses multivariate correlation analysis (MCA) for accurate network traffic characterization by extracting the geometrical correlations between network traffic features. Our MCA-based DoS attack detection system employs the principle of anomaly based detection in attack recognition. This makes our solution capable of detecting known and unknown DoS attacks effectively by learning the patterns of legitimate network traffic only. Furthermore, a triangle-area-based technique is proposed to enhance and to speed up the process of MCA. The effectiveness of our proposed detection system is evaluated using KDD Cup 99 data set, and the influences of both non-normalized data and normalized data on the performance of the proposed detection system are examined. The results show that our system outperforms two other previously developed state-of-the-art approaches in terms of detection accuracy.

10.1109/tpds.2013.146

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Citations (292)

Pattern Recognition Approach for Anomaly Detection of Web-based Attacks

Aruna Jamdagni Zhiyuan Tan Ren Ping Liu Priyadarsi Nanda Xiangjian He

The universal use of the Internet has made it more difficult to achieve a high security level. Attackers target web applications instead of Telnet ports. Cyber-attacks and breaches of information security are increasing in frequency. The goal of Intrusion Detection Systems (IDSs) is to monitor and detect webbased attacks. The commonly used IDSs are: signature based IDSs and anomaly based IDSs. Signature based IDS is unable to detect novel attack (i.e., zero-day) or polymorphic attacks, until the signature database is updated. On the other hand, an anomaly-based IDS can detect new attacks and polymorphic attacks. However, anomaly based system has a relatively high number of false positives.

Telnet

Signature (topology)

Anomaly (physics)

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Citations (2)

A Nonlinear Correlation Measure for Intrusion Detection

MA Ambu Saidi Liangfu Lu Tianyu Tan Shaoming He Aruna Jamdagni

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An Intrusion Detection System Based on Polynomial Feature Correlation Analysis

Qingru Li Zhiyuan Tan Aruna Jamdagni Priyadarsi Nanda Xiangjian He

This paper proposes an anomaly-based Intrusion Detection System (IDS), which flags anomalous network traffic with a distance-based classifier. A polynomial approach was designed and applied in this work to extract hidden correlations from traffic related statistics in order to provide distinguishing features for detection. The proposed IDS was evaluated using the well-known KDD Cup 99 data set. Evaluation results show that the proposed system achieved better detection rates on KDD Cup 99 data set in comparison with another two state-of-the-art detection schemes. Moreover, the computational complexity of the system has been analysed in this paper and shows similar to the two state-of-the-art schemes.

10.1109/trustcom/bigdatase/icess.2017.340

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Citations (14)

A Two-Tier System for Web Attack Detection Using Linear Discriminant Method

Lecture notes in computer science (2010)

Zhiyuan Tan Aruna Jamdagni Xiangjian He Priyadarsi Nanda Ren Ping Liu

Identification

Signature (topology)

Feature vector

Feature (linguistics)

10.1007/978-3-642-17650-0_32

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Citations (6)

RePIDS: A multi tier Real-time Payload-based Intrusion Detection System

Computer Networks (2012)

Aruna Jamdagni Zhiyuan Tan Xiangjian He Priyadarsi Nanda Ren Ping Liu

Mahalanobis distance

Payload (computing)

Feature (linguistics)

10.1016/j.comnet.2012.10.002

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Citations (81)

A Secure Routing Scheme for Wireless Mesh Networks

Lecture notes in computer science (2016)

Ashish Nanda Priyadarsi Nanda Xiangjian He Aruna Jamdagni

Mesh networking

Wireless WAN

10.1007/978-3-319-49806-5_21

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Citations (5)

An Efficient Approach for Advanced Malware Analysis Using Memory Forensic Technique

Chathuranga Rathnayaka Aruna Jamdagni

Static analysis in malware analysis has been complex due to string searching methods. Forensic investigation of the physical memory or memory forensics provides a comprehensive analysis of malware, checking traces of malware in malware dumps that have been created while running in an operating system. In this study, we propose efficient and robust framework to analyse complex malwares by integrating both static analysis techniques and memory forensic techniques. The proposed framework has evaluated two hundred real malware samples and achieved a 90% detection rate. These results have been compared and verified with the results obtained from www.virustotal.com, which is online malware analysis tool. Additionally, we have identified the sources of many malware samples.

Malware analysis

Computer forensics

10.1109/trustcom/bigdatase/icess.2017.365

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Citations (48)