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Cybersecurity-Lab-at-CEN

Cybersecurity group at CEN

(Cybersecurity lab @ CEN)

Centre for Excellence in Computational Engineering and Networking (CEN)

Amrita Vishwa Vidyapeetham.

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

Cybersecurity group at CEN understand the underlying mathematics knowledge required to apply Machine learning to Cyber Security tasks at Scale.

The ability to digitize our lives has outpaced our ability to stay safe. One of the biggest challenges is to understand the volume, velocity and complexity of threatening activity inside the network. We call this cyber intelligence. We have been developing a self-learning intelligence system by understanding the mathematics and using the most advanced machine learning technologies such as deep learning. A self-learning intelligence system learns a unique pattern of normal and abnormal activities of every device and user on a network, and correlates these insights in order to spot emerging threats that would otherwise go unnoticed. Cybersecurity group is fortunate to have Cyber Security experts and Researchers who have constantly smell the developments in Natural language processing, Image processing, Speech recognition and many other areas and incorporate those novel approaches to self-learning system to enhance the system detection rate of malicious activities. We are involved in developing large scale Security projects that involves Big-data Security Intelligence, Cyber-Physical systems security, Machine learning for Security, Complex Binary analysis, IoT, SCADA and Hardware security, Application & Network security, Advanced Forensics and Incident handling. Some of the tasks that we think and solve daily are to apply various Data mining, Machine learning and Deep learning approaches to various Cyber Security tasks such as Traffic Analysis, Intrusion detection, Malware Analysis, Botnet Analysis, Anonymity Services, Domain Generation Algorithms, Advanced mathematics to Crypto Systems.

We strongly believe in open science and reproducible research and actively publish tool and code on Github

Mentors specialized in Data science

Dr. Soman K P

Mentors specialized in Cybersecurity

Dr. Prabaharan Poornachandran Center for Cyber Security Systems and Networks, Amrita Vishwa Vidyapeetham, Coimbatore, India

Mentors specialized in Complex systems for Cybersecurity

Dr. E. A. Gopalakrishnan

Mentors specialized in NLP for Cybersecurity

Dr. Anand Kumar M

Dr. Govind D.

Mentors specialized in Big data Analytics for Cybersecurity

Mr. Vijay Krishna Menon

Mentors specialized in Signal and Image processing for Cybersecurity

Sowmya V

Mentors specialized in IOT Security

Mr. Sajith Variyar V. V.

Mentors specialized in Malware Analysis

Mr. Pradeep Menon

Mr. K.K.Senthil Velan

Research Scholars specialized in Cognitive security - Natural Language Processing, signal and image processing, Machine Learning and Deep Learning for Cybersecurity

Mr. Vinayakumar R

Mr. Akarsh S

Mr. Sriram S

Simran K

Vysakh S Mohan

Mohammed Harun Babu R

Mr. Amara Dinesh Kumar, Master’s student

Mr. Barathi Ganesh HB

Anu V, Research Assistant

Mr. Harikrishnan N B, MTech student

[Mr. Akarsh S, MTech student]

Publications

Bookchapters

Vinayakumar R, Soman KP, Prabaharan Poornachandran, Pradeep Menon “A deep-dive on Machine learning for Cybersecurity use cases, MLCCS 2018 “[under review]

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

Journals

Vinayakumar R, Soman KP, Prabaharan Poornachandran and Sachin Kumar S “Detecting Android Malware using Long Short-term Memory-LSTM” Journal of Intelligent and Fuzzy Systems - IOS Press

Vinayakumar R, Soman KP, Prabaharan Poornachandran and Sachin Kumar S “Evaluating Deep Learning Approaches to Characterize and Classify the DGAs at Scale” Journal of Intelligent and Fuzzy Systems - IOS Press

Vinayakumar R, Soman KP and Prabaharan Poornachandran “Evaluating Deep learning Approaches to Characterize, Signalize and Classify malicious URLs” Journal of Intelligent and Fuzzy Systems - IOS Press

Vinayakumar R, Soman KP and Prabaharan Poornachandran “Detecting Malicious Domain Names using Deep Learning Approaches at Scale” Journal of Intelligent and Fuzzy Systems - IOS Press

Vinayakumar R, Soman KP and Prabaharan Poornachandran “Evaluation of Recurrent Neural Network and its variants for Intrusion Detection System (IDS)” IJISMD [under print]

Conference papers

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)

Harikrishnan Nb, Vinayakumar R and Soman Kp, “Deep Learning based Phishing URL Detection”,, RCDDS 2018 [under print]

Anu Vazhayil, Vinayakumar R and Soman Kp, “Comparative study of the detection of malicious URLs using Shallow and Deep Networks”,, RCDDS 2018 [under print]

Vinayakumar R, Barathi Ganesh H B, Prabaharan Poornachandran, Anand Kumar M and Soman Kp, “Deep-Net: Deep Neural Network for Cyber Security Use Cases”, RCDDS 2018 [under print]

Harikrishnan Nb, Vinayakumar R, Soman Kp and Pradeep Menon, “Shallow and Deep Neural Network Intrusion Detection System”,, RCDDS 2018. [under print]

Harikrishnan Nb, Vinayakumar R, Soman Kp and Pradeep Menon, “Performance comparison of Deep learning and classical Machine learning in Network traffic intrusion detection system”,, RCDDS 2018 [under print]

Vinayakumar R, Soman KP and Prabaharan Poornachandran, “Evaluating Shallow and Deep Networks for Secure Shell (SSH)Traffic Analysis”

Vinayakumar R, Soman KP and Prabaharan Poornachandran, “Evaluating Effectiveness of Shallow and Deep Networks to Intrusion Detection System”

Vinayakumar R, Soman KP and Prabaharan Poornachandran, “Deep Android Malware Detection and Classification.”

Vinayakumar R, Soman KP and Prabaharan Poornachandran, “Long Short-Term Memory based Operation Log Anomaly Detection.”

Vinayakumar R, Soman KP and Prabaharan Poornachandran, “Deep Encrypted Text Categorization.”

Vinayakumar R, Soman KP and Prabaharan Poornachandran, “Applying Convolutional Neural Network for Network Intrusion Detection.”

Vinayakumar R, Soman KP and Prabaharan Poornachandran, “Secure Shell (SSH) Traffic Analysis with Flow based Features Using Shallow and Deep networks.”

Vinayakumar R, Soman KP and Prabaharan Poornachandran, “Applying Deep Learning Approaches for Network Traffic Prediction.”

Vinayakumar R, Soman KP, K.K.Senthil Velan and Shaunak Ganorkar, “Evaluating Shallow and Deep Networks for Ransomware Detection and Classification.”

B. Ashwini, Vijay Krishna Menon, KP Soman “Prediction of Malicious Domains Using Smith Waterman Algorithm”

M. Jocelyn Babu V.Sowmya KP Soman “Fast Fourier Transform and Nonlinear Circuits Based Approach for Smart Meter Data Security”

R K Rahul T Anjali Vijay Krishna Menon KP Soman “Deep Learning for Network Flow Analysis and Malware Classification”

Shared task working notes

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

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

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

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

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

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

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

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

Team names in IWSPA-AP Shared Task

  1. CEN-Security@IWSPA 2018- Authors: Harikrishnan Nb, Vinayakumar R, Soman KP and Pradeep Menon

  2. CEN-AISecurity@IWSPA-2018- Authors: Vinayakumar R, Barathi Ganesh HB, Prabaharan Poornachandran, Anand Kumar M andSoman KP

  3. NLP_CEN_AMRITA @ IWSPA 2018- Authors: Barathi Ganesh HB, Vinayakumar R, Anand Kumar M and Soman KP

  4. CENSec@Amrita- Authors: Anu Vazhayil, Vinayakumar R and Soman KP

  5. Security-CEN@Amrita- Authors: Akarsh S, Harikrishnan NB, Vinayakumar R and Soman KP

  6. CEN-DeepSpam- Authors: Hiransha M, Nidhin Unnithan, Vinayakumar R and Soman KP

  7. Crypt Coyotes- Authors: Vysakh Mohan, Vinayakumar R and Soman KP

  8. CEN-SecureNLP- Authors: Sai Sundarakrishna, Vinayakumar R and Soman KP

Shared tasks participated in 2017

  1. WASSA-2017 Emotion Intensity Task - Mr. Vinayakumar R

  2. Stance and Gender Detection in Tweets on Catalan Independence@Ibereval 2017 - Mr. Vinayakumar R

  3. DEFT 2017 Text Search @ TALN / RECITAL 2017 Opinion analysis and figurative language in tweets in French - Mr. Vinayakumar R

  4. VarDial 2017 - Fourth Workshop on NLP for Similar Languages, Varieties and Dialects - Mr. Vinayakumar R

  5. 2nd Social Media Mining for Health Applications Shared Task at AMIA 2017 - Vinayakumar R and Mr. Barathi Ganesh HB

  6. The 8th International Cybersecurity Data Mining Competition 2017 - Mr. VinayaKumar R and Mr. Barathi Ganesh HB

  7. The 8th International Cybersecurity Data Mining Competition 2017 - Mr. Harikrishnan NB, Anu V and Mr. VinayaKumar R

  8. The 8th International Cybersecurity Data Mining Competition 2017 - Mr. VinayaKumar R

Invited Talks

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

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

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

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

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Title: Deep learning for Cyber Security In Deep learning Workshop organized by Amrita University, Coimbatore.

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

[Workshops conducted by Cybersecurity group at CEN]

  1. AISec 2017 Workshop: Modern Artificial Intelligence (AI) and Natural Language Processing (NLP) Techniques for Cyber Security

  2. Blockchain 2017 Workshop: Blockchain and Machine Learning

  3. DeepSci 2017 Workshop: Deep Learning for Healthcare and Financial Data Analytics

  4. DeepChem 2017: Deep Learning & NLP for Computational Chemistry, Biology & Nano-materials