M
Muttukrishnan Rajarajan
Researcher at City University London
Publications - 279
Citations - 5737
Muttukrishnan Rajarajan is an academic researcher from City University London. The author has contributed to research in topics: Cloud computing & Encryption. The author has an hindex of 32, co-authored 267 publications receiving 4817 citations. Previous affiliations of Muttukrishnan Rajarajan include Universities UK & University College London.
Papers
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Proceedings ArticleDOI
Activity Recognition in Smart Homes Using Clustering Based Classification
TL;DR: This paper proposes a two level classification approach for activity recognition by utilizing the information obtained from the sensors deployed in a smart home, and applies a computationally less expensive learning algorithm Evidence Theoretic K-Nearest Neighbor.
Journal ArticleDOI
Survey of approaches and features for the identification of HTTP-based botnet traffic
TL;DR: A survey of approaches to characterising or detecting HTTP-based bots, many of which use network communication features as identifiers of botnet behaviour, and the relationships between features at the application, transport and network layers is presented.
Journal ArticleDOI
Characterization of Silver/Polystyrene (PS)-Coated Hollow Glass Waveguides at THz Frequency
Christos Themistos,B. M. A. Rahman,Muttukrishnan Rajarajan,Kenneth T. V. Grattan,Bradley Bowden,James A. Harrington +5 more
TL;DR: In this article, the authors used the perturbation technique to calculate the complex propagation characteristics of hollow glass waveguides for terahertz frequency radiation, and the formation of the coupled supermodes and the effect of the polystyrene (PS) coating thickness on the attenuation characteristics were investigated.
Proceedings ArticleDOI
Evaluation of Android Anti-malware Techniques against Dalvik Bytecode Obfuscation
Parvez Faruki,Ammar Bharmal,Vijay Laxmi,Manoj Singh Gaur,Mauro Conti,Muttukrishnan Rajarajan +5 more
TL;DR: The resilience of anti-malware techniques against transformations for Android is explored and low resilience of Androguard's code similarity and AndroSimilar's robust statistical feature signature against code obfuscated malware is evaluated.
Proceedings ArticleDOI
Investigating the android intents and permissions for malware detection
TL;DR: This work is first of its kind which is investigating the combined effects of permissions and intent filters to distinguish between the malware and benign apps and proposed approach is supplemented with the machine learning algorithms for further classification of apps.