Vinayakumar R
Ph.D. Student (Cyber Security) & Cognitive Security Practitioner
Computational Engineering and Networking
Amrita Vishwa Vidyapeetham
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CV

I am a third-year Ph.D. student at the Amrita Vishwa Vidyapeetham in Computational Engineering and Networking (CEN). I am with the Cybersecurity-Lab-at-CEN and advised by Prof. Soman KP on Artificial intelligence and most specifically, Machine Learning, Data mining and Deep learning, Big Data Analytics, Natural language processing and Signal and Image processing for Cyber Security. I spent the first two years of my Ph.D. working on traditional machine learning for various use-cases of Cyber Security and now I am working on deep learning for network traffic analysis, android malware detection, spam detection, log analysis, insider threat detection and ransomware detection. I am particularly interested in improving the malicious detection rate through the use of Artificial Intelligence (AI), including machine learning, data mining, deep learning and natural language processing.

Cybersecurity group at CEN is organizing a shared task in Cybersecurity domain. More details avilable at DMD2018

I strongly believe in open science and reproducible research and actively publish code on my Github profile.

I am on the job market!!

News

Mar 2018 Book chapter - "A deep-dive on Machine learning for Cybersecurity use cases" MLCCS 2018 (InPress)
Feb 2018 Our paper titled S.P.O.O.F Net: Syntactic Patterns for identification of Ominous Online Factors has accepted in BioSTAR 2018
Jan 2018 Registered for IWSPA-AP Shared Task at IWSPA 2018.
Nov 2017 Our book chapter "Scalable Framework for Cyber Threat Situational Awareness based on Domain Name Systems Data Analysis" got accepted and appear in Big data in Engineering Applications.

Under-Review

  • Harikrishnan Nb, Vinayakumar R and Soman Kp, “CEN-Security@IWSPA 2018: A Machine learning approach towards Spam Detection” IWSPA-AP (Accepted)

  • Vinayakumar R, Barathi Ganesh H B, Prabaharan Poornachandran, Anand Kumar M and Soman Kp, “DeepAnti-PhishNet: Applying Deep Neural Networks for E-mail Spam Detection” IWSPA-AP (Accepted)

  • Barathi Ganesh Hb, Vinayakumar R, Soman Kp and Anand Kumar M, “Distributed Representation using Target Classes: Bag of Tricks for Security and Privacy Analytics Amrita-NLP@IWSPA 2018” IWSPA-AP (Accepted)

  • Anu Vazhayil, Vinayakumar R and Soman Kp, “CENSec@Amrita: Spam Detection using classical Machine learning techniques” IWSPA-AP (Accepted)

  • Nidhin Unnithan, Harikrishnan Nb, Akarsh S, Vinayakumar R and Soman Kp, “Security-CEN@Amrita Machine learning based Spam E-mail detection” IWSPA-AP (Accepted)

  • Vysakh S Mohan, Naveen J R, Vinayakumar R and Soman K P, “A.R.E.S: Automatic Rogue Email Spotter” IWSPA-AP (Accepted)

  • Hiransha M, Nidhin Unnithan, Vinayakumar R and Soman Kp, “CEN-DeepSpam: Deep learning based spam detection” IWSPA-AP (Accepted)

  • Vinayakumar R, Harikrishnan Nb, Nidhin Unnithan, Soman Kp and Sai Sundarakrishna, “CEN-SecureNLP Detecting E-mail spam using Machine learning techniques” IWSPA-AP

  • Vysakh S Mohan, Vinayakumar R, Soman Kp and Prabaharan Poornachandran, “S.P.O.O.F Net: Syntactic Patterns for identification of Ominous Online Factors”, BioSTAR 2018 (Accepted)

  • Swapna G, Soman KP and Vinayakumar R, “Automated detection of cardiac arrhythmia using deep learning techniques”, ICCIDS 2018 (Accepted)

  • Swapna G, Soman KP and Vinayakumar R, “Diabetes: Automated detection of diabetes using CNN and CNN-LSTM network and heart rate signals”, ICCIDS 2018 (Accepted)

  • Athira V, Geetha P, Soman Kp and Vinayakumar R, “DeepAirNet: Applying Recurrent networks for Air Quality Prediction”, ICCIDS 2018 (Accepted)

  • Aswin S, Geetha P and Vinayakumar R, “Deep Learning Models for the Prediction of Rainfall”, ICCSP 2018 (Accepted)

  • Anson Simon, Vinayakumar R, Sowmya V and Soman K P, “Shallow CNN with LSTM Layer for Tuberculosis Detection in Microscopic Images”, RCDDS 2018 (Accepted)

  • Mohammed Harun Babu R, Sai Bhanuja B, Vinayakumar R, Sowmya V, “DEEP NEURAL NETWORK FOR PHONOCARDIOGRAM SIGNAL CLASSIFICATION”, RCDDS 2018 (Accepted)

  • Naren Babu R, Saiprasath G, Arunpriyan J, Vinayakumar R, Sowmya V and Soman K P, “PERFORMANCE COMPARISON OF MACHINE LEARNING ALGORITHMS FOR MALARIA DETECTION USING MICROSCOPIC IMAGES”, RCDDS 2018 (Accepted)

  • Swapna G, Vinayakumar R and Soman Kp, “Automated detection of Atrial Fibrillation using deep learning techniques”,, RCDDS 2018 (Accepted)

  • Anson simon, Mr Vinayakumar R, Sowmya V, Soman KP, “A Deep Learning Approach for Patch Based Disease Diagnosis from Microscopic Images”

Education

Aug 2015 - Present Ph.D. in Computer Science
Amrita Vishwa Vidyapeetham, Coimbatore
June 2011 - May 2014 Masters of Computer Application
Amrita Vishwa Vidyapeetham, Mysore
June 2008 - May 2011 Bachelor of Computer Application
JSS College, Mysore

Research Experience

Aug 2015 - Present Research Associate, Prof. Soman KP
Data mining, Machine learning, Deep learning, Cyber Security, Natural language processing
Jun 2014 - Jul 2015 Research Assistant, Prof. Soman KP
Block-based programming development for Indian K-12 Schools

PhD Coursework

  • MA607 - Linear Algebra
  • CN613 - Computational optimization theory- linear and non-linear methods
  • CY603 - Pattern Recognition and Machine Learning
  • CN624 - Scientific Computing
  • CN703 - Computational Methods for Cryptography
  • CN733 - Neural network & Deep learning
  • CY800 - Research Methodology
  • Foundation Mathematics
  • Computational Thinking

Skills

Languages

C, C++, Java, Scala, Python, Basics of R, Basics of Julia

Web development

Html, CSS, JavaScript, JSON, JQuery, Php, Bootstrap, XML, Jsp

Educational Platforms

MIT Scratch, Snap Berkley, BYOB, Scribble, Beetle Blocks

Frameworks

Spark Mllib, Apache Mahout, XG-boost, Scikit-learn, Dato, Hpelm, Gurls, LibSVM, TensorFlow, Theano, Keras, Deeplearning4j, Torch, Basics of Caffe, DeepChem, DragoNN, Hadoop, Apache Spark, Weka and Matlab

Database

MySQL, Introduction to Oracle, Apache Cassandra

Documentation Tool

LibreOffice, Microsoft Office, and Latex

Participation in NLP and Cyber Security Shared Tasks

  • Named Entity rEcognition and Linking (#Micropost2015 NEEL): Named Entity Recognition and Linking.

  • International Cybersecurity Data Mining Competition CDMC 2016.

  • VarDial 2017 - Fourth Workshop on NLP for Similar Languages, Varieties, and Dialects.

  • Stance and Gender Detection in Tweets on Catalan Independence@Ibereval 2017.

  • WASSA-2017 Emotion Intensity Task.

  • DEFT 2017 Text Search @ TALN / RECITAL 2017 Opinion analysis and figurative language in tweets in French.

  • International Cybersecurity Data Mining Competition CDMC 2017.

  • 2nd Social Media Mining for Health Applications Shared Task at AMIA 2017.

Co-organized the following events in the department of Computational Engineering and Networking, Amrita Vishwa Vidyapeetham

Invited Talks

  • Title: Deep Learning in IEEE (3451) at Kalasalingam Academy of Research and Education, Virudhunagar, Saturday, 3 February 2018. [ Tutorial]

  • Title: Deep Learning for Bio-medical Applications in ICMR sponsored Faculty Development Program (FDP) at Mepco Schlenk Engineering College, Sivakasi, Wednesday, 17 January 2018. [ Tutorial]

  • Title: Deep Learning for Bio-medical Applications in TEQUIP sponsored Faculty Development Program (FDP) at TKM College of Engineering, Kollam, 14 December 2017. [ Tutorial]

  • Title: Deep Learning for Cyber Security use cases in Bharathiar University at the University conference hall on 21/11/17. [ Tutorial]

  • Title: Deep Learning for Chemistry in DeepChem 2017: Deep Learning & NLP for Computational Chemistry, Biology & Nano-materials, Conducted by the Department of Computational Engineering and Networking, Amrita Vishwa Vidyapeetham, December 22-24, 2017. [ Tutorial]

  • Title: Deep learning for Healthcare and financial data analytics in DeepSci 2017 Workshop: Deep Learning for Healthcare and Financial Data Analytics, Conducted by the Department of Computational Engineering and Networking, Amrita Vishwa Vidyapeetham, Saturday, December 16, 2017. [ Tutorial]

  • Title: Deep Learning for Blockchain in Blockchain 2017 Workshop: Blockchain and Machine Learning, Conducted by the Department of Computational Engineering and Networking, Amrita Vishwa Vidyapeetham, Saturday, December 16, 2017. [ Tutorial]

  • Title: Deep Learning for Cyber Security use cases in AISec 2017 Workshop: Modern Artificial Intelligence (AI) and Natural Language Processing (NLP) Techniques for Cyber Security, Conducted by the Department of Computational Engineering and Networking, Amrita Vishwa Vidyapeetham, Saturday, October 28, 2017. [ Tutorial]

  • Title: Deep learning for Cyber Security In Deep learning Workshop organized by Amrita University, Coimbatore. [ Tutorial]

  • Demo on LSTM based Android Malware classification in TEQIP II sponsored research workshop on deep learning, PSG Tech, Coimbatore. [ Tutorial]

Certifications acquired from Online Coursework

  • Neural Networks and Deep Learning, Coursera, Aug. 2017 [certificate]
  • Deep Learning with Tensorflow, Big Data University, Dec. 2016 [certificate]
  • Deep Learning Prerequisites: The Numpy Stack in Python [certificate]
  • Big Data, Big Data University, Jul. 2016 [certificate]
  • Big Data Foundations, IBM, Jul. 2016[certificate]
  • Functional Programming Principles in Scala, Coursera, Jul. 2016 [certificate]
  • Hadoop, Big Data University, Jul. 2016 [certificate]
  • Spark Fundamentals, Big Data University, Jul. 2016 [certificate]
  • HTML and CSS, Udemy, Jan. 2015 [certificate]

Certificates acquired from paper presentation in conference

  • Detecting Android Malware using Long Short-term Memory-LSTM
  • Evaluating Deep Learning Approaches to Characterize and Classify the DGAs at Scale
  • Evaluating Deep learning Approaches to Characterize, Signalize and Classify malicious URLs
  • Detecting Malicious Domain Names using Deep Learning Approaches at Scale
  • Evaluating Shallow and Deep networks for SSH Traffic Analysis using Flow-based mechanisms
  • Evaluating Effectiveness of Shallow and Deep Networks to Intrusion Detection System
  • Deep Android Malware Detection and Classification
  • Long Short-Term Memory based Operation Log Anomaly Detection
  • Deep Encrypted Text Categorization
  • Applying Convolutional Neural Network for Network Intrusion Detection
  • Secure Shell (SSH) Traffic Analysis with Flow-based Features Using Shallow and Deep networks
  • Applying Deep Learning Approaches for Network Traffic Prediction
  • Evaluating Shallow and Deep Networks for Ransomware Detection and Classification
  • Real-time Detection of Atrial Fibrillation from Short time single lead ECG traces using Recurrent neural networks

Certificates acquired from participating in workshops

  • Web Application And Mobile Data Security
  • Data mining for Healthcare
  • Software Testing

All Publications

Google Scholar

Book Chapter

Scalable Framework for Cyber Threat Situational Awareness based on Domain Name Systems Data Analysis
Vinayakumar R, Prabaharan Poornachandran and Soman KP
Big data in Engineering Applications Springer
[under print] [code]

Journal Papers

Detecting Android Malware using Long Short-term Memory-LSTM
Vinayakumar R, Soman KP, Prabaharan Poornachandran and Sachin Kumar S
Journal of Intelligent and Fuzzy Systems - IOS Press
[under print] [code]
Evaluating Deep Learning Approaches to Characterize and Classify the DGAs at Scale
Vinayakumar R, Soman KP, Prabaharan Poornachandran and Sachin Kumar S
Journal of Intelligent and Fuzzy Systems - IOS Press
[under print] [code]
Evaluating Deep learning Approaches to Characterize, Signalize and Classify malicious URLs
Vinayakumar R, Soman KP and Prabaharan Poornachandran
Journal of Intelligent and Fuzzy Systems - IOS Press
[under print] [code]
Detecting Malicious Domain Names using Deep Learning Approaches at Scale
Vinayakumar R, Soman KP and Prabaharan Poornachandran
Journal of Intelligent and Fuzzy Systems - IOS Press
[under print] [code]

Conference Papers

Evaluating Shallow and Deep Networks for Secure Shell (SSH) Traffic Analysis
Vinayakumar R, Soman KP and Prabaharan Poornachandran IEEE Xplore
[paper] [slides] [code]
Evaluating Effectiveness of Shallow and Deep Networks to Intrusion Detection System
Vinayakumar R, Soman KP and Prabaharan Poornachandran
IEEE Xplore
[paper] [slides] [code]
Deep Android Malware Detection and Classification
Vinayakumar R, Soman KP and Prabaharan Poornachandran
IEEE Xplore
[paper] [slides] [code]
Long Short-Term Memory based Operation Log Anomaly Detection
Vinayakumar R, Soman KP and Prabaharan Poornachandran
IEEE Xplore
[paper] [slides] [code]
Deep Encrypted Text Categorization
Vinayakumar R, Soman KP and Prabaharan Poornachandran
IEEE Xplore
[paper] [slides] [code]
Applying Convolutional Neural Network for Network Intrusion Detection
Vinayakumar R, Soman KP and Prabaharan Poornachandran
IEEE Xplore
[paper] [slides] [code]
Secure Shell (SSH) Traffic Analysis with Flow based Features Using Shallow and Deep networks
Vinayakumar R, Soman KP and Prabaharan Poornachandran
IEEE Xplore
[paper] [slides] [code]
Applying Deep Learning Approaches for Network Traffic Prediction
Vinayakumar R, Soman KP and Prabaharan Poornachandran
IEEE Xplore
[paper] [slides] [code]
Evaluating Shallow and Deep Networks for Ransomware Detection and Classification
Vinayakumar R, Soman KP, K.K.Senthil Velan and Shaunak Ganorkar
IEEE Xplore
[paper] [slides] [code]
Instantaneous Heart Rate as a Robust Feature for Sleep Apnea Severity Detection using Deep Learning
Rahul K. Pathinarupothi, Vinaykumar R, Ekanath Rangan, Gopalakrishnan E., and Soman K. P.
IEEE Xplore
[paper] [slides] [code]
Single Sensor Techniques for Sleep Apnea Diagnosis using Deep Learning
Rahul K. Pathinarupothi, Dhara Prathap J., Ekanath Rangan, Gopalakrishnan E., Vinaykumar R, and Soman K. P.
IEEE Xplore
[paper] [slides] [code]
Real-time Detection of Atrial Fibrillation from Short time single lead ECG traces using Recurrent neural networks
Sujadevi VG., Soman KP., and Vinayakumar R
Intelligent Systems Technologies and Applications (ISTA'17), Springer
[paper] [slides] [code]
Anomaly detection in Phonocardiogram employing Deep learning
Sujadevi VG., Soman KP., Vinayakumar R and Prem Sankar AU.
4th International Conference on Computational Intelligence in Data Mining (ICCIDM-2017), Springer
[paper] [slides] [code]
Deep models for Phonocardiography (PCG) classification
Sujadevi VG., Soman KP., Vinayakumar R and Prem Sankar AU.
IEEE Xplore
[paper] [slides] [code]
Stock Price Prediction Using LSTM, RNN And CNN-Sliding Window Model
Sreelekshmy Selvin., Vinayakumar R, Gopalakrishnan E., Vijay Krishna Menon., Soman K.P.,
6th International Conference on Advances in Computing, Communications and Informatics (ICACCI2017)
IEEE Xplore
[paper] [slides] [code]
AMRITA-CEN@SAIL2015: Sentiment analysis in Indian languages
Shriya Se, Vinayakumar, R., Anand Kumar M., and Soman K.P.
MIKE 2015 Proceedings of the Third International Conference on Mining Intelligence and Knowledge Exploration, Springer
[paper] [slides] [code]
Predicting the Sentimental Reviews in Tamil Movie using Machine Learning Algorithms v Shriya Se, Vinayakumar R, Anand Kumar M., and Soman K.P.
Indian Journal of Science and Technology (IJST)
[paper] [slides] [code]
Deep Power: Deep Learning Architectures for Power Quality Disturbances Classification
Neethu Mohan, Soman K.P, and Vinayakumar R
TAP Energy 2017.
[paper] [slides] [code]

Recent Blog Posts

Malicious Url January 17, 2018
Dga January 17, 2018
Ai For Security January 16, 2018

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Last updated on 2017-12-18