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S. Malliga

Researcher at Kongu Engineering College

Publications -  29
Citations -  254

S. Malliga is an academic researcher from Kongu Engineering College. The author has contributed to research in topics: Denial-of-service attack & Spoofing attack. The author has an hindex of 9, co-authored 21 publications receiving 193 citations.

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Journal ArticleDOI

A hybrid scheme using packet marking and logging for IP traceback

TL;DR: This study uses a hybrid approach based on marking and logging to traceback single attack packet with less storage and traceback overhead on routers and demonstrates the effectiveness of this approach through a mathematical analysis.
Journal Article

A proposal for new marking scheme with its performance evaluation for IP traceback

TL;DR: A hybrid packet marking algorithm, along with traceback mechanism to find the true origin of the attack traffic is presented in this study and is able to trace back to single packet, nevertheless it requires logging at very few routers and thus incurring insignificant storage overhead on the routers.
Journal ArticleDOI

Dual layer security of data using LSB inversion image steganography with elliptic curve cryptography encryption algorithm

TL;DR: This new approach intensely tested through several steganalysis attacks and shown that the stego image has delivered the strong opposition force against all attacks and the data embedding capacity has attained at an improved level compared with typical methods.
Journal ArticleDOI

Dual-layer security of image steganography based on IDEA and LSBG algorithm in the cloud environment

TL;DR: The results show that the proposed technique outperforms the existing methodologies and resolves the data security problem in data transmission and storage system of cloud computing services.
Proceedings ArticleDOI

A packet marking approach to protect cloud environment against DDoS attacks

TL;DR: This paper addresses the problem of HX-DoS attacks against cloud web services by using the rule set based detection, called CLASSIE and modulo marking method, and enables the reduction of false positive rate and increase the detection and filtering of DDoS attacks.