Nicholas Cariello

About Me

Nicholas Cariello in the research lab at New York Institute of Technology

Education

Ph.D. in Computer Science New York Institute of Technology 2022 – 2026 (Defending April 2026)
M.S. in Computer Science New York Institute of Technology 2018 – 2019
B.S. in Computer Science New York Institute of Technology 2015 – 2018

Certifications

Certified Information Systems Security Professional (CISSP)
IBM Enterprise Design Thinking Practitioner
IBM Developer Profession – Level 3 Expert

I am a Ph.D. candidate in Computer Science at the New York Institute of Technology, preparing to defend my dissertation in April 2026. My research focuses on the intersection of cybersecurity, behavioral biometrics, and machine learning. I am a member of the LAMP (Laboratory for behavioral Authentication, Machine learning, and Privacy) research lab, working under the advisement of Dr. Paolo Gasti and Dr. Kiran S. Balagani.

In parallel with my academic research, I bring over seven years of industry experience at IBM, where I currently serve as a Technical Lead and Team Lead for GRC Tooling in CISO. I architect and deliver AI-powered security and compliance platforms, including tools that leverage semantic search, vector databases, and large language models to automate third-party risk assessments and compliance validation. My doctoral research in behavioral biometrics and machine learning directly informs my professional work — bridging cutting-edge academic methods with enterprise-scale security challenges. I am rated as a Top Performer and hold the IBM Developer Profession Level 3 (Expert) certification.

In 2022, I was honored with the Ingenium Rising Star Award from the NYIT College of Engineering and Computing Sciences, which recognizes alumni who have demonstrated a commitment to the college by serving as a speaker, mentor, and resource to current students. I have also been featured by NYIT for my contributions to the Ph.D. program. As a (almost) triple alum (B.S. '18, M.S. '19, Ph.D. '26), my deep roots at New York Tech combined with hands-on industry experience at IBM give me a unique perspective on solving real-world security challenges.

"If I could give one piece of advice to current students, it would be to get involved outside of class whenever possible, network as much as you can, and always carry gratitude." — Ingenium Awards acceptance speech, 2022

Research

My research sits at the intersection of behavioral biometrics, continuous authentication, and machine learning. I investigate how the ways people physically interact with their smartphones can be used to verify identity — continuously and transparently — without relying on traditional credentials.

Continuous Smartphone Authentication

Developing methods that continuously verify a user's identity based on behavioral patterns while they interact with their mobile device, enabling seamless security without interrupting the user experience.

Behavioral Biometrics

Studying how human behavioral traits — such as touch dynamics, gait patterns, and device interaction habits — can serve as robust biometric identifiers, including the impact of posture and body movement on these signals.

Change of Possession Detection

Researching novel approaches to detect when a smartphone changes hands between users, enabling real-time security responses that protect sensitive data from unauthorized access.

Privacy-Preserving Security

Exploring how machine learning and cryptographic techniques can be combined to deliver strong authentication while preserving user privacy — a core mission of the LAMP research lab.

LAMP Research Lab

The Laboratory for behavioral Authentication, Machine learning, and Privacy at NYIT is co-directed by Dr. Paolo Gasti and Dr. Kiran S. Balagani. Our lab brings together faculty, PhD and Master's students, and visiting researchers who work on problems in machine learning and cryptography applied to privacy and authentication.

Visit LAMP Lab

Dissertation

Defending April 2026

Interaction-Anchored Behavioral Biometrics for Continuous Authentication on Smartphones

This dissertation proposes an interaction-anchored framework for continuous authentication that re-centers the problem around natural user events such as swipes, keystrokes, and possession changes. By extracting and aggregating features within short event windows, the framework can reliably authenticate a user in 1–2 seconds, sharply reducing vulnerability without sacrificing accuracy. Across four empirical studies, this work demonstrates that smartphone dynamics — including swiping, typing, and motion features — yield competitive performance at sub-five-second windows, including the first evidence that keystroke-based continuous authentication can achieve error rates below two percent at one-second intervals. The dissertation will be available here following the defense.

Advisors: Dr. Paolo Gasti & Dr. Kiran S. Balagani

Publications

My published work focuses on advancing the field of continuous authentication on mobile devices through behavioral biometrics and machine learning.

2026

Keystroke-Aligned Body Motion Patterns for Short-Burst Continuous Smartphone Authentication: A Proof-of-Concept Study Using Motion Capture

Nicholas Cariello, Lam Nguyen, Rosemary Gallagher, Isaac Kurtzer, Kiran S. Balagani, and Paolo Gasti

IEEE Transactions on Biometrics, Behavior, and Identity Science (T-BIOM), 2026 (Accepted)

This proof-of-concept study investigates a multimodal approach combining traditional keystroke dynamics with laboratory-grade 3D motion capture body movement data and smartphone motion features for short-burst continuous authentication. The integration of phone motion and body motion features with keystroke dynamics achieves an equal error rate (EER) of 1.5% over 1-second authentication windows — a 77% improvement over keystroke-only approaches and the first to achieve reliable authentication during common short textual interactions on smartphones.

View on IEEE

2025

Posture and Body Movement Effects on Behavioral Biometrics for Continuous Smartphone Authentication

Nicholas Cariello, Robert Eslinger, Rosemary Gallagher, Isaac Kurtzer, Paolo Gasti, and Kiran S. Balagani

IEEE Transactions on Biometrics, Behavior, and Identity Science (T-BIOM), vol. 7, no. 1, January 2025

This study investigates how different user postures and body movements affect the performance of behavioral biometric systems for continuous smartphone authentication. Understanding these factors is critical for building authentication systems that work reliably across diverse real-world usage conditions.

View on IEEE PDF

2024

Smartcope: Smartphone Change Of Possession Evaluation for Continuous Authentication

Nicholas Cariello, Seth Levine, Gang Zhou, Blair Hoplight, Paolo Gasti, and Kiran Balagani

Elsevier Pervasive and Mobile Computing, vol. 97, pp. 101873, 2024

Smartcope presents a novel framework for evaluating whether a smartphone has changed possession between users. This approach enhances continuous authentication by detecting handoff events, enabling timely security measures when a device is accessed by an unauthorized individual.

View on ScienceDirect PDF

Professional Experience

Oct 2024 – Present

Technical Lead & Team Lead, GRC Tooling

IBM CISO · New York, NY

Lead architect and team lead delivering AI-powered security and compliance platforms. Designed and delivered a platform leveraging semantic search over vector databases and large language models to automate third-party risk assessments — reducing completion time by 60% and increasing throughput by 15%. Architected an automated compliance analysis engine that transforms manual security validation into data-driven, automated results across multiple data sources. Serve as an AI consultant across the cybersecurity organization, influencing automation strategies and responsible AI adoption. Rated as a Top Performer.

Nov 2023 – Oct 2024

Technical Lead, AI Governance

IBM CIO BISO & Cybersecurity Assurance · New York, NY

Led IBM's client zero adoption of the enterprise AI governance platform. Drove the initiative from proof-of-concept through production deployment, coordinating across product, platform, and application teams. Applied deep knowledge of AI and governance to architect integration solutions and establish deployment patterns for responsible AI adoption across the enterprise.

Apr 2021 – Nov 2023

Software Developer / Cybersecurity Specialist

IBM CIO BISO & Cybersecurity Assurance · Armonk, NY

Core developer and SME for IBM's enterprise endpoint compliance platform, serving 392,000+ endpoints used in audits and internal compliance validation. Led the design and development of a compliance API adopted by 10+ teams, saving an estimated 250 hours per team annually. Led the effort to enforce DMARC on IBM.com, resulting in a drastic decrease in domain abuse across 10,000+ owned domains. Mentored multiple intern cohorts, leading them from architecture through production deployment.

Jan 2019 – Apr 2021

Cybersecurity Engineer / Software Developer

IBM CISO · Armonk, NY

Thought leader for enterprise cybersecurity education and cultural transformation. Designed and launched quarterly phishing simulations based on real threats, engineered full-stack applications for Cybersecurity Awareness Month competitions, and contributed to enterprise security policies aligned with NIST, ISO 27001, PCI-DSS, and HIPAA. Coordinated the CISO internship program for a cohort of 21 interns, resulting in 12 full-time offer extensions.

Jun 2018 – Sep 2018

Software Development Intern