Metamorphic Malware Analysis and Detection Methods. - P. Vinod 001; Vijay Laxmi; Manoj Singh Gaur (Cyber Security, Cyber Crime and Cyber Forensics, 2011)

Scattered Feature Space for Malware Analysis. - P. Vinod 001; Vijay Laxmi; Manoj Singh Gaur (ACC (1), 2011)

Behavioural detection with API call-grams to identify malicious PE files. - Parvez Faruki; Vijay Laxmi; Manoj Singh Gaur; P. Vinod 001 (SECURIT, 2012)

SPADE: Signature based PAcker DEtection. - Smita Naval; Vijay Laxmi; Manoj Singh Gaur; P. Vinod 001 (SECURIT, 2012)

Mining control flow graph as API call-grams to detect portable executable malware. - Parvez Faruki; Vijay Laxmi; Manoj Singh Gaur; P. Vinod 001 (SIN, 2012)

ESCAPE: entropy score analysis of packed executable. - Smita Naval; Vijay Laxmi; Manoj Singh Gaur; P. Vinod 001 (SIN, 2012)

MCF: MultiComponent Features for Malware Analysis. - P. Vinod 001; Vijay Laxmi; Manoj Singh Gaur; Smita Naval; Parvez Faruki (AINA Workshops, 2013)

Discriminant features for metamorphic malware detection. - Jikku Kuriakose; Vinod P. 001 (IC3, 2014)

Linux malware detection using non-parametric statistical methods. - Asmitha KA; Vinod P 001 (ICACCI, 2014)

X-ANOVA and X-Utest features for Android malware analysis. - Rincy Raphael; Vinod P. 001; Bini Omman (ICACCI, 2014)

Framework for design of Graybot in social network. - Silpa Sebastian; Sonal Ayyappan; Vinod P 001 (ICACCI, 2014)

Exploration of robust features for multiclass emotion classification. - Bincy Thomas; Dhanya K. A.; P. Vinod 001 (ICACCI, 2014)

Droid permission miner: Mining prominent permissions for Android malware analysis. - A. M. Aswini; P. Vinod 001 (ICADIWT, 2014)

Towards the Detection of Undetectable Metamorphic Malware. - Jikku Kuriakose; Vinod P. 001 (SIN, 2014)

Linux Malware Detection Using eXtended-Symmetric Uncertainty. - K. A. Asmitha; P. Vinod 001 (SPACE, 2014)

Android Malware Analysis Using Ensemble Features. - A. M. Aswini; P. Vinod 001 (SPACE, 2014)

Detecting malicious files using non-signature-based methods. - P. Vinod 001; Vijay Laxmi; Manoj Singh Gaur; Grijesh Chauhan (Int. J. Inf. Comput. Secur., 2014)

Pruned feature space for metamorphic malware detection using Markov Blanket. - Jithu Raphel; P. Vinod 001 (IC3, 2015)

Heterogeneous feature space for Android malware detection. - Varsha M. V.; P. Vinod 001; Dhanya K. A. (IC3, 2015)

Machine learning approach for filtering spam emails. - Princy George; P. Vinod 001 (SIN, 2015)

Hartley's test ranked opcodes for Android malware analysis. - Meenu Mary John; P. Vinod 001; K. A. Dhanya (SIN, 2015)

Information theoretic method for classification of packed and encoded files. - Jithu Raphel; P. Vinod 001 (SIN, 2015)

Identification of malicious android app using manifest and opcode features. - Varsha M. V.; P. Vinod 001; K. A. Dhanya (J. Comput. Virol. Hacking Tech., 2017)

Malware Signature Generation Using Locality Sensitive Hashing. - Hassan Naderi; P. Vinod 001; Mauro Conti; Saeed Parsa; Mohammad Hadi Alaeiyan (ISEA-ISAP, 2018)

FeatureAnalytics: An approach to derive relevant attributes for analyzing Android Malware. - Deepa K; Radhamani G; Vinod P 001; Mohammad Shojafar; Neeraj Kumar 001; Mauro Conti (CoRR, 2018)

Identification of Android malware using refined system calls. - Deepa K; Radhamani G; Vinod P 001; Mohammad Shojafar; Neeraj Kumar 001; Mauro Conti (Concurr. Comput. Pract. Exp., 2019)

A machine learning based approach to detect malicious android apps using discriminant system calls. - Vinod P 001; Akka Zemmari; Mauro Conti (Future Gener. Comput. Syst., 2019)

Detection of Tor Traffic using Deep Learning. - Debmalya Sarkar; P. Vinod 001; Suleiman Y. Yerima (AICCSA, 2020)

SysDroid: a dynamic ML-based android malware analyzer using system call traces. - A. Ananya; A. Aswathy; T. R. Amal; P. G. Swathy; Vinod P 001; Mohammad Shojafar (Clust. Comput., 2020)

Can machine learning model with static features be fooled: an adversarial machine learning approach. - Rahim Taheri; Reza Javidan; Mohammad Shojafar; P. Vinod 001; Mauro Conti (Clust. Comput., 2020)

Detection of algorithmically-generated domains: An adversarial machine learning approach. - Mohammad Hadi Alaeiyan; Saeed Parsa; Vinod P 001; Mauro Conti (Comput. Commun., 2020)

Secure Brain-to-Brain Communication With Edge Computing for Assisting Post-Stroke Paralyzed Patients. - Sreeja Rajesh; Varghese Paul; Varun G. Menon; Sunil Jacob; P. Vinod 001 (IEEE Internet Things J., 2020)

Downsampling Attack on Automatic Speaker Authentication System. - Asha S 001; P. Vinod 001; Varun G. Menon; Akka Zemmari (AICCSA, 2021)

Secure Static Content Delivery for CDN Using Blockchain Technology. - Mauro Conti; P. Vinod 001; Pier Paolo Tricomi (DPM/CBT@ESORICS, 2021)

Hide and Seek Game: A Machine Learning Approach for Detecting Malicious Samples in Analysis Environment. - Anandaram S.; Ashik Mathew; Jyothish A.; Vinod P. 001; Francesco Mercaldo (IC3, 2021)

Automatic Classification of Vulnerabilities using Deep Learning and Machine Learning Algorithms. - Vishnu Ramesh; Sara Abraham; P. Vinod 001; Isham Mohamed; Corrado Aaron Visaggio; Sonia Laudanna (IJCNN, 2021)

A Study on Misclassification of Software Vulnerabilities when using Deep Learning and Machine Learning Algorithms. - Vishnu Ramesh; Sara Abraham; Vinod P 001; Isham Mohamed; Corrado Aaron Visaggio; Sonia Laudanna (ITASEC, 2021)

Vulnerability Evaluation of Android Malware Detectors against Adversarial Examples. - Ijas Ah; Vinod P. 001; Akka Zemmari; Harikrishnan D; Godvin Poulose; Don Jose; Francesco Mercaldo; Fabio Martinelli; Antonella Santone (KES, 2021)

Malware detection employed by visualization and deep neural network. - Anson Pinhero; Anupama M. L; Vinod P 001; Corrado Aaron Visaggio; Aneesh N; Abhijith S; AnanthaKrishnan S (Comput. Secur., 2021)

Multi-Domain Network Traffic Analysis using Machine Learning and Deep Learning Techniques. - Dincy R. Arikkat; Rafidha Rehiman K. A.; Vinod P. 001; Suleiman Y. Yerima; Manoja W; Pooja S; Shilpa Sekhar; Sohan James; Josna Philomina (IC3, 2022)

On the Influence of Image Settings in Deep Learning-based Malware Detection. - Francesco Mercaldo; Fabio Martinelli; Antonella Santone; Vinod P. 001 (ICISSP, 2022)

Performance evaluation of deep neural network on malware detection: visual feature approach. - V. Anandhi; P. Vinod 001; Varun G. Menon; Korankotte Manoj Aditya (Clust. Comput., 2022)

Evaluation of adversarial machine learning tools for securing AI systems. - S. Asha 001; P. Vinod 001 (Clust. Comput., 2022)

A few-shot malware classification approach for unknown family recognition using malware feature visualization. - Mauro Conti; Shubham Khandhar; Vinod P. 001 (Comput. Secur., 2022)

Cognitive smart cities: Challenges and trending solutions. - Varun G. Menon; Reza Khosravi; Alireza Jolfaei; Akshi Kumar 001; P. Vinod 001 (Expert Syst. J. Knowl. Eng., 2022)

Obfuscation detection in Android applications using deep learning. - Mauro Conti; P. Vinod 001; Alessio Vitella (J. Inf. Secur. Appl., 2022)

A Deep Learning Approach for Classifying Vulnerability Descriptions Using Self Attention Based Neural Network. - P. R. Vishnu; P. Vinod 001; Suleiman Y. Yerima (J. Netw. Syst. Manag., 2022)

GANG-MAM: GAN based enGine for Modifying Android Malware. - Renjith G; Sonia Laudanna; Aji S; Corrado Aaron Visaggio; Vinod P 001 (SoftwareX, 2022)

Detection and robustness evaluation of android malware classifiers. - Anupama M. L; P. Vinod 001; Corrado Aaron Visaggio; M. A. Arya; Josna Philomina; Rincy Raphael; Anson Pinhero; K. S. Ajith; P. Mathiyalagan (J. Comput. Virol. Hacking Tech., 2022)

MMDFD- A Multimodal Custom Dataset for Deepfake Detection. - Asha S 001; Vinod P 001; Varun G. Menon (IC3, 2023)

Interpretable PDF Malware Detector. - Sneha Rajagopal; Avanthika Gaur; P. Vinod 001 (SIN, 2023)

Can Twitter be used to Acquire Reliable Alerts against Novel Cyber Attacks? - Dincy R. Arikkat; P. Vinod 001; Rafidha Rehiman K. A.; Andrea Di Sorbo; Corrado Aaron Visaggio; Mauro Conti (CoRR, 2023)

A smartphone authentication system based on touch gesture dynamics. - Susmi Jacob; Vinod Puthuvath; Muralidharan Akarsh; Jackson George; Jewel Joseph; Jigil Joy (Concurr. Comput. Pract. Exp., 2023)

Sober: Explores for invasive behaviour of malware. - Mohammadhadi Alaeiyan; Saeed Parsa; Vinod P. 001 (J. Inf. Secur. Appl., 2023)

Obfuscated Malware Detection in IoT Android Applications Using Markov Images and CNN. - Dhanya K. A.; P. Vinod 001; Suleiman Y. Yerima; Abul Bashar; David A. Wagner 001; Abhiram T.; Alan Antony; Ashil K. Shavanas; T. Gireesh Kumar (IEEE Syst. J., 2023)

Evading Machine-Learning-Based Android Malware Detector for IoT Devices. - Renjith G; P. Vinod 001; Aji S (IEEE Syst. J., 2023)

A defensive framework for deepfake detection under adversarial settings using temporal and spatial features. - S. Asha 001; P. Vinod 001; Varun G. Menon (Int. J. Inf. Sec., 2023)

Affect sensing from smartphones through touch and motion contexts. - Susmi Jacob; P. Vinod 001; Arjun Subramanian; Varun G. Menon (Multim. Syst., 2023)

A Privacy Preservation Framework Using Integration of Blockchain and Federated Learning. - K. M. Sameera; Rafidha Rehiman K. A.; P. Vinod 001 (SN Comput. Sci., 2023)

SoK: Visualization-based Malware Detection Techniques. - Matteo Brosolo; Vinod Puthuvath; Asmitha KA; Rafidha Rehiman K. A.; Mauro Conti (ARES, 2024)

Beyond Words: Stylometric Analysis for Detecting AI Manipulation on Social Media. - Ubaid Ullah; Sonia Laudanna; P. Vinod 001; Andrea Di Sorbo; Corrado Aaron Visaggio; Gerardo Canfora (ESORICS (1), 2024)

Relation Extraction Techniques in Cyber Threat Intelligence. - Dincy R. Arikkat; P. Vinod 001; Rafidha Rehiman K. A.; Serena Nicolazzo; Antonino Nocera; Mauro Conti (NLDB (1), 2024)

Towards a Malware Family Classification Model Using Static Call Graph Instruction Visualization. - Attila Mester; Zalán Bodó; P. Vinod 001; Mauro Conti (NSS, 2024)

DLShield: A Defense Approach Against Dirty Label Attacks in Heterogeneous Federated Learning. - K. M. Sameera; M. Abhinav; P. P. Amal; T. Babu Abhiram; Raj K. Abishek; Tomichen Amal; P. Anaina; P. Vinod 001; Rafidha Rehiman K. A.; Mauro Conti (SPACE, 2024)

vDefender: An explainable and introspection-based approach for identifying emerging malware behaviour at hypervisor-layer in virtualization environment. - Avantika Gaur; Preeti Mishra; Vinod P. 001; Arjun Singh; Vijay Varadharajan; Uday Kiran Tupakula; Mauro Conti (Comput. Electr. Eng., 2024)

LFGurad: A Defense against Label Flipping Attack in Federated Learning for Vehicular Network. - K. M. Sameera; Vinod P. 001; Rafidha Rehiman K. A.; Mauro Conti (Comput. Networks, 2024)

Privacy-preserving in Blockchain-based Federated Learning systems. - K. M. Sameera; Serena Nicolazzo; Marco Arazzi; Antonino Nocera; Rafidha Rehiman K. A.; Vinod P. 001; Mauro Conti (Comput. Commun., 2024)

OSTIS: A novel Organization-Specific Threat Intelligence System. - Dincy R. Arikkat; P. Vinod 001; Rafidha Rehiman K. A.; Serena Nicolazzo; Antonino Nocera; Georgiana Timpau; Mauro Conti (Comput. Secur., 2024)

Deep Learning Fusion For Effective Malware Detection: Leveraging Visual Features. - Jahez Abraham Johny; Vinod P. 001; K. A. Asmitha; Radhamani G; Rafidha Rehiman K. A.; Mauro Conti (CoRR, 2024)

IntellBot: Retrieval Augmented LLM Chatbot for Cyber Threat Knowledge Delivery. - Dincy R. Arikkat; Abhinav M.; Navya Binu; Parvathi M.; Navya Biju; K. S. Arunima; Vinod P. 001; Rafidha Rehiman K. A.; Mauro Conti (CoRR, 2024)

Indoor localization using device sensors: A threat to privacy. - Hitesh Verma; Smita Naval; Balaprakasa Rao Killi; P. Vinod 001 (Microprocess. Microsystems, 2024)

A defensive attention mechanism to detect deepfake content across multiple modalities. - S. Asha 001; P. Vinod 001; Varun G. Menon (Multim. Syst., 2024)

Effectiveness of machine learning based android malware detectors against adversarial attacks. - Jyothish A.; Ashik Mathew; P. Vinod 001 (Clust. Comput., 2024)

D-Fence layer: an ensemble framework for comprehensive deepfake detection. - Asha S 001; Vinod P 001; Irene Amerini; Varun G. Menon (Multim. Tools Appl., 2024)

Deep learning vs. adversarial noise: a battle in malware image analysis. - K. A. Asmitha; Vinod Puthuvath; Rafidha Rehiman K. A.; S. L. Ananth (Clust. Comput., 2024)

SFC-NIDS: a sustainable and explainable flow filtering based concept drift-driven security approach for network introspection. - Arjun Singh; Preeti Mishra; P. Vinod 001; Avantika Gaur; Mauro Conti (Clust. Comput., 2024)

XAITrafficIntell: Interpretable Cyber Threat Intelligence for Darknet Traffic Analysis. - Dincy R. Arikkat; P. Vinod 001; Rafidha Rehiman K. A.; Rabeeba Abdul Rasheed; Mauro Conti (J. Netw. Syst. Manag., 2024)

Behind Enemy Lines: Strengthening Android Malware Detection with Adversarial Training. - Sonia Laudanna; Mattia Marino; Andrea Di Sorbo; P. Vinod 001; Corrado Aaron Visaggio; Gerardo Canfora (ARES (EU Projects Symposium Workshops 1), 2025)

Sok: Zero Trust as a Strategy to Address Devsecops Challenges. - Anita Nair; Serena Nicolazzo; Antonino Nocera; Rafidha Rehiman K. A.; Vinod P. 001 (EuroS&P (Workshops), 2025)

MoRSE: Bridging the Gap in Cybersecurity Expertise with Retrieval Augmented Generation. - Marco Simoni; Andrea Saracino; Vinod P 001; Mauro Conti (SAC, 2025)

NLP-based techniques for Cyber Threat Intelligence. - Marco Arazzi; Dincy R. Arikkat; Serena Nicolazzo; Antonino Nocera; Rafidha Rehiman K. A.; Vinod P. 001; Mauro Conti (Comput. Sci. Rev., 2025)

SeCTIS: A framework to Secure CTI Sharing. - Dincy R. Arikkat; Mert Cihangiroglu; Mauro Conti; Rafidha Rehiman K. A.; Serena Nicolazzo; Antonino Nocera; P. Vinod 001 (Future Gener. Comput. Syst., 2025)

SecDefender: Detecting low-quality models in multidomain federated learning systems. - K. M. Sameera; Arnaldo Sgueglia; P. Vinod 001; Rafidha Rehiman K. A.; Corrado Aaron Visaggio; Andrea Di Sorbo; Mauro Conti (Future Gener. Comput. Syst., 2025)

DroidTTP: Mapping android applications with TTP for Cyber Threat Intelligence. - Dincy R. Arikkat; P. Vinod 001; Rafidha Rehiman K. A.; Serena Nicolazzo; Marco Arazzi; Antonino Nocera; Mauro Conti (J. Inf. Secur. Appl., 2025)

Through the static: Demystifying malware visualization via explainability. - Matteo Brosolo; Vinod P. 001; Mauro Conti (J. Inf. Secur. Appl., 2025)

Android malware defense through a hybrid multi-modal approach. - K. A. Asmitha; P. Vinod 001; Rafidha Rehiman K. A.; Neeraj Raveendran; Mauro Conti (J. Netw. Comput. Appl., 2025)

Transformer or Autoencoder? Who is the ultimate adversary for attack detectors? - Sonia Laudanna; Andrea Di Sorbo; Vinod Puthuvath; Corrado Aaron Visaggio; Gerardo Canfora (Int. J. Inf. Sec., 2025)

The Road Less Traveled: Investigating Robustness and Explainability in CNN Malware Detection. - Matteo Brosolo; Vinod Puthuvath; Mauro Conti (CoRR, 2025)

How Secure is Forgetting? Linking Machine Unlearning to Machine Learning Attacks. - Muhammed Shafi K. P.; Serena Nicolazzo; Antonino Nocera; Vinod P 001 (CoRR, 2025)

Deep learning fusion for effective malware detection: leveraging visual features. - Jahez Abraham Johny; K. A. Asmitha; P. Vinod 001; G. Radhamani; Rafidha Rehiman K. A.; Mauro Conti (Clust. Comput., 2025)

WeiDetect: Weibull Distribution-Based Defense against Poisoning Attacks in Federated Learning for Network Intrusion Detection Systems. - K. M. Sameera; P. Vinod 001; Anderson Rocha 001; Rafidha Rehiman K. A.; Mauro Conti (CoRR, 2025)

XBreaking: Explainable Artificial Intelligence for Jailbreaking LLMs. - Marco Arazzi; Vignesh Kumar Kembu; Antonino Nocera; Vinod P. 001 (CoRR, 2025)

Security through the Eyes of AI: How Visualization is Shaping Malware Detection. - Matteo Brosolo; Asmitha KA; Rafidha Rehiman K. A.; Muhammed Shafi K. P.; Serena Nicolazzo; Antonino Nocera; Vinod P. 001 (CoRR, 2025)

When Forgetting Triggers Backdoors: A Clean Unlearning Attack. - Marco Arazzi; Antonino Nocera; Vinod P 001 (CoRR, 2025)

Enhancing Android Malware Detection with Retrieval-Augmented Generation. - Saraga S.; Anagha M. S.; Dincy R. Arikkat; Rafidha Rehiman K. A.; Serena Nicolazzo; Antonino Nocera; P. Vinod 001 (CoRR, 2025)

Discerning reliable cyber threat indicators for timely Cyber Threat Intelligence. - Dincy R. Arikkat; P. Vinod 001; Rafidha Rehiman K. A.; Corrado Aaron Visaggio; Andrea Di Sorbo; Mauro Conti (J. Comput. Virol. Hacking Tech., 2025)