P. Rajesh Kanna

15 papers Journal 15

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	An efficient optimized deep learning model for the risk prediction of arterial stiffness in diabetes patients. Biomed. Signal Process. Control. A. Mohana Priya, P. Rajesh Kanna, S. Vanithamani, G. Sathish Kumar
2025	J	`jnl`	Scalable hierarchical balanced clustering-based routing with multipath authentication for secured data transmission in large-scale multicast group communications. Expert Syst. Appl. K. Somasundaram, P. Rajesh Kanna
2024	J	`jnl`	An Enhanced Hybrid Intrusion Detection Using Mapreduce-Optimized Black Widow Convolutional LSTM Neural Networks. Wirel. Pers. Commun. P. Rajesh Kanna, P. Santhi
2024	J	`jnl`	Differential privacy scheme using Laplace mechanism and statistical method computation in deep neural network for privacy preservation. Eng. Appl. Artif. Intell. G. Sathish Kumar, K. Premalatha, G. Uma Maheshwari, P. Rajesh Kanna, G. Vijaya, Mathappan Nivaashini
2024	J	`jnl`	Enhancing speech emotion detection with Windowed Long-Term Average Spectrum and Logistic-Rectified Linear Unit. Eng. Appl. Artif. Intell. P. Rajesh Kanna, V. Kumararaja
2024	J	`jnl`	Exploring the landscape of network security: a comparative analysis of attack detection strategies. J. Ambient Intell. Humaniz. Comput. P. Rajesh Kanna, P. Santhi
2024	J	`jnl`	Multi-modal emotion recognition through adaptive normalization fusion with alpha Gaussian dropout in MCNN architecture. Signal Image Video Process. M. Murugesan, P. Dhivya, P. Rajesh Kanna, G. Sathish Kumar
2024	J	`jnl`	TB-MFCC multifuse feature for emergency vehicle sound classification using multistacked CNN - Attention BiLSTM. Biomed. Signal Process. Control. T. M. Nithya, P. Dhivya, S. N. Sangeethaa, P. Rajesh Kanna
2023	J	`jnl`	An Efficient PM - Multisampling Image Filtering with Enhanced CNN Architecture for Pneumonia Classfication. Biomed. Signal Process. Control. T. M. Nithya, P. Rajesh Kanna, S. Vanithamani, P. Santhi
2023	J	`jnl`	No more privacy Concern: A privacy-chain based homomorphic encryption scheme and statistical method for privacy preservation of user's private and sensitive data. Expert Syst. Appl. G. Sathish Kumar, K. Premalatha, G. Uma Maheshwari, P. Rajesh Kanna
2022	J	`jnl`	Hybrid Intrusion Detection using MapReduce based Black Widow Optimized Convolutional Long Short-Term Memory Neural Networks. Expert Syst. Appl. P. Rajesh Kanna, P. Santhi
2021	J	`jnl`	An experimental inquisition of waste heat recovery in electronic component system using concentric tube heat pipe heat exchanger with different working fluids under gravity assistance. Microprocess. Microsystems P. Ramkumar, M. Sivasubramanian, P. Raveendiran, P. Rajesh Kanna
2021	J	`jnl`	Unified Deep Learning approach for Efficient Intrusion Detection System using Integrated Spatial-Temporal Features. Knowl. Based Syst. P. Rajesh Kanna, P. Santhi
2018	J	`jnl`	A numerical simulation on the flow field and the heat transfer of water jet impingement on a solid block. Int. J. Comput. Aided Eng. Technol. Marimuthu Muthukannan, P. Rajesh Kanna, P. Ganesan, S. Jeyakumar
2018	J	`jnl`	Three dimensional numerical investigation of forced convection heat transfer from offset square cylinders placed in a confined channel. Int. J. Comput. Aided Eng. Technol. P. Rajesh Kanna, M. Sivasubramanian, P. Maheandera Prabu, M. Uthayakumar

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

In 2025, he co-authored Assessing the Effectiveness of the Tigress Obfuscator Against MOPSA and BinaryNinja, published at CheckMATE. The paper evaluates the effectiveness of obfuscation techniques and their impact on source-level static analysis and binary-level decompilation.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.