Matt Troglia : Curriculum Vitae

Matthew David-Kristofer Troglia

1332 Houghtailing Street, Honolulu. Hawaii, 96817

 (808) 364.8809 · mtroglia@hawaii.edu

Electrical Engineer and Cyber Security Operations

Personal Information

Citizenship: U.S.A. ° No Veterans Preference ° Highest Federal grade held: N/A ° 

Objective

Seeking a challenging position as a Cyber Security Specialist where a highly motivated and skilled employee is needed with a post-graduate degree. To defend and secure our nations critical infrastructure, sensitive network environments, and safeguard our vulnerable data with exceptional technical expertise.

Education & Certifications

CompTIA Security+ Awarded March 12, 2018.

  • License Number F8YEYLXF3P141Z3V.

University of Hawaii, Honolulu, HI 96817 – Aug 2018-Present.

  • PhD in Electrical Engineering: GPA 4.00 on a 4.00 scale.
  • CyberCorps Scholarship for Service Awardee Aug 2018- Present.
  • Thesis: “Distributed Sensing, Learning, and Enforcement for Spectrum Sharing Environments
  • Research interests/topics:
    • “Characterizing Location-based Mobile Tracking in Mobile Ad Networks” IEEE CNS 2019,
    • “Protocol Reverse Engineering in Application for Drone Security and Exploitation”,
    • “Physical Security with Reconfigurable Antennas”
  • 2019 College of Engineering Student Award for Excellence in Research.

University of Hawaii, Honolulu, HI 96817 – Aug 2014-Dec 2016.

  • Master of Science in Electrical Engineering: GPA 3.83 on a 4.00 scale.
  • Master’s Project “Decentralized Anonymous Authentication for Cloud Data Sharing”.

Hawaii Pacific University, Honolulu, HI, 96813. – Sept 2011-May 2014.

  • Bachelor of Science in Applied Mathematics: GPA 3.7. Graduated with high honors, Cum Laude.
  • Dean’s List (2011-2013), Capstone Symposium Award (2014)

Training

Cyber Corps Scholarship for Service Conference, Cal Poly Pomona, CA. Sept 14-16 2018.

  • Hands-on training in Digital forensics. Preservation of evidence using write blockers for data acquisition. Analysis of evidence using software EndCase and FTK. Wrote incident reports.
  • Hands-on training in a simulated security operations center and incident response using log analysis and SIEM tools, Splunk and QRadar.
  • Participated in cyber-ops capture the flag event and code breaker challenge.

Skills

Computer Skills.

  • Proficient in the following applications: Microsoft Office, AutoCAD, Matlab/Python/R, and Wireshark.
  • Experience with programming languages Java, Matlab, C, C++, and Python.
  • Operating systems experience in OSX, Linux and Windows 7/8/10. Frequent use of Linux OS distributions for electrical engineering works including network configurations, firewall testing, and computer network and security analysis. Familiarity with Linux/MAC terminal operations. Experience with virtual environment configurations with VMware.
  • Network analysis tools such as tcpdump, dumpcap, tshark/wireshark, capinfos, editcap, and python/scapy.

 

Mathematics.

  • Advanced mathematical techniques in model analysis including numerical methods for high order differential equation, kinematic analysis, dynamic systems, linear/nonlinear analysis, controllability and observability in linear systems theory, statistical modeling and analysis, circuit analysis techniques, and other applied mathematics topics.

Machine Learning/Neural Networks/AI.

  • Theory and application of machine learning via EE 445 Machine Learning course at University of Hawaii. Sentiment analysis final project, predicting review scores from text.
  • Deep Learning, a 5-course specialization by deeplearning.ai on Coursera led by Stanford University Adjunct Professor of Computer Science Andrew Ng. Specialization Certificate earned on February 25, 2018.
    • Neural Networks and Deep Learning by deeplearning.ai on Coursera. Certificate earned at Friday, September 15, 2017.
    • Improving Deep Neural Networks: Hyper-parameter tuning, Regularization and Optimization by deeplearning.ai on Coursera. Certificate earned at Friday, October 6, 2017.
    • Structuring Machine Learning Projects by deeplearning.ai on Coursera. Certificate earned at Wednesday, September 20, 2017.
    • Convolutional Neural Networks by deeplearning.ai on Coursera. Certificate earned at Tuesday, February 20, 2018.
    • Sequence Models by deeplearning.ai on Coursera. Certificate earned at Sunday, February 25, 2018.

Laboratory

  • Experience with test hardware:
    • General lab equipment (Electrical Engineering, Chemistry, Physics).
  • Ability to work with various types of instrumentation:
    • Oscilloscopes, multi-meters, voltage generator.

Task Handling and Other Skills

  • Excellent teamwork skills, very organized, strong leadership, strong communication skills, easily adaptable, can handle multiple tasks well, critical thinking, self-motivated, and tutoring/lecturing experience.

Leadership and Professional Affiliations

Club and Honor Society Supervisor: Tara Davis, tdavis@hpu.edu, 808-544-0856

Hawaii Pacific University’s Kappa Mu Epsilon Honors Society, President 2012-2014.

  • Lead role and co-organized STEM related community events, including tutoring sessions.
  • Allocated over $1500 from Student Activity Committee for Biostatistics, Alzheimer’s project.

Hawaii Pacific University’s Math club, President 2012-2013.

  • Lead and organized Math club events, including tutoring sessions.
  • Budgeted finances of Math club.

Hawaii Pacific University’s STEM club, Vice President and Treasurer 2013-2014.

  • Co-coordinated task for STEM related events and budgeted finances.

IEEE Student Member Number 93670663

  • IEEE INFOCOM 2019 “Location-based Privacy Leakage Study in Mobile Ad Networks” Submitted July 31st 2018

Employment History

Design Engineer  January 2016- August 2018. 40hrs/week

 Resurgo 2800 Woodlawn Drive, Honolulu, Hawaii. Pay: $92,000/yr.

Supervisor: Eamon Jordan Eamon.jordan@resurgo.net, 808-784-0562

  • Network communication analysis (service loss, service downtime, latency), software design for network analysis tools, and design of experiment and test planning for network operations analysis.
  • Frequent use of network tools for data analysis such as tcpdump, dumpcap, tshark/wireshark, capinfos, and python/scapy.
  • Familiar with SIEM software tools Splunk and ELK for security threat analysis and network situational awareness monitoring.
  • Wrote and enforced company security policy for secure data handling procedures.
  • Install, setup, and configure virtual environments on VMWare ESXi servers.
  • Survey and analyze network architectures to provide defense-in-depth solutions to enhance performance and provide suggestions for enhancement to hardware and software advancement.
  • Experimental design and test planning for the Department of Defense demonstration sponsored by the Environmental Security Technology Certification Program (ESTCP) entitled Critical Energy Infrastructure Cyber Defense-in-Depth Project.
  • Developed a machine learning sensor for industrial control systems security under the Critical Energy Infrastructure Cyber Defense-in-Depth Project.
  • Written contract proposals, white papers, and letters of interest for various government contract announcements including research fields for situational awareness and machine learning applications of industrial control systems security, high-performance computing systems security, computer network security, and RNA modification detection.

Lighting and Electrical Quotations  June 2014- October 2015. 20hrs/week.

 Gexpro, 560 N Nimitz Hwy #119a, Honolulu, Hawaii. Pay: $18/hour.

Supervisor: Nathan Nielson Nathan.nielson@gexpro.com, 808-852-6810

  • Preform detailed analysis of electrical diagrams and blueprints.
  • Familiarity with electrical panel boards, breakers, wire gauges, light fixtures, occupancy sensors

and various other electrical components.

  • Supply Electrical contractors with quoted materials from analysis of panel schedules, luminaire schedules, lighting control specifications, and other pertinent electrical prints/material.
  • Write up return on investment analysis between cost saving initiative products.

Student Assistant to Student Life and First Year ProgramsOctober 2011- May 2015. 19hrs/week.

 Hawaii Pacific University, 1188 Fort Street, Honolulu, HI, 96817. Pay: $7.50/hour.

Supervisor: Gleanne Dimson gdimson@hpu.edu, 808-544-9340.

  • Data entry/organization, advertise events, create posters, institutional knowledge and guidance.
  • Awards: Light Up The Night Award, HPU student worker excellence recognition, April 2011, Nov & April 2012.

Home Depot Cashier July 2011 –October 2011. 20hrs/week.

421 Alakawa St, Honolulu, HI 96817. Pay $8.50/hr.

Supervisor: William M. 808-521-7355.

  • Outstanding customer service, engage in conversation with customer upon checkout.
  • General store knowledge, basic product knowledge in hardware.

Walmart CashierNovember 2010 – June 201. 20-40 hrs/week.

11350 Wickersham Blvd Gretna, NE 68028. Pay $8.00/hr.

Supervisor: Linda Stenzel, 402-881-3530.

  • Outstanding customer service, engage in frequent conversation about various products.
  • General store knowledge of product placement.

Kmart Sales Associate– June 2009 – November 2010. 20-40hrs/week.

5808 S 144th St, Omaha, NE 68173. Pay $7.25/hr.

Supervisor: Pat Skinner, 402-895-2244.

  • Sufficient knowledge in gardening department, and high knowledge in electronic services.
  • Engage in frequent customer interaction to provide outstanding customer service.

 

Research Works/Projects

 M.S. in Computer Electrical Engineering, University of Hawaii at Manoa (2014-2016)

Advanced course projects/presentations include:

EE 609 Computer and Network Security.

  • Zero Knowledge Proofs of Knowledge (ZKPoK). Presentation and research on proofs that mathematically prove a statement true or false with high probability without revealing any contents of the statement. Explored the protocol ZKPoK in order to understand a valuable application, anonymous authentication. Implemented and analyzed the Fiat-Shamir Identification Protocol.
  • Decentralized Anonymous Authentication through ZKPoK and analysis of the Zerocoin application. Presentation and research on authentication schemes, especially those used in developing crypto-currencies. Research included regions of authentication from certificate authorities, to webs-of-trust, decentralized Electronic Cash schemes, and applied anonymous authentication.

EE 660 Computer Architecture.

  • Architecture for a Secure Searchable Cloud Storage and Blind Storage (Lecture). Presentation and research on cloud storage schemes and techniques that keep the transfer and privacy of these items secure. Detail the potential data leakage or untrustworthiness of cloud storage providers. Lecture on others proposed works for solution which contains securely encrypted data and which can efficiently maintain all operations of the stored data, like search, insert, and delete.

EE 607 Advanced Network Algorithms.

  • Central Control Over Distributed Routing (Lecture). Provided a lecture to introduce distributed and centralized routing protocols and explain the novel solution detailed as the Fibbing architecture; A software defined network management approach to distributed routing which provides more flexibility and robustness than traditional dynamic routing protocols.

 

EE 650 Linear Systems Theory.

  • Fundamentals on the modern theory of dynamical systems and control. Control theory with emphasizes state space techniques for the analysis of dynamical systems and the synthesis of control laws meeting given design specifications. Optimal control and parameter tuning for dynamic systems. Application to nuclear, power and conventional control systems, autopilots, navigation and telecommunications, and manufacturing.

 

EE 626 Rapid Prototyping EP Devices.

  • TrogBox - Mobile Effects Pedal (prototyped). Implemented techniques for rapid prototyping to develop an inline guitar-strap distortion box including online circuit design/simulators, Cura for 3D design, and Makerbot for 3D printing. Use of voltage generators and oscilloscopes to tune the circuit for desired distorted sound by varying the voltage/audio clipping.

EE 445 Machine Learning.

  • Given labeled data sets that contain the real-valued score of food reviews, models were developed that can predict accurate ratings given written words (review) about a food product. Text classification tools, such as bag-of-words, were used as well as known kernels that are useful to text classification problems. Investigated the best performing algorithms for such a task and investigated the underlying cause of performance by comparison of each model. The performance was quantitatively analyzed by comparing mean squared error (MSE).

 

EE 438, Renewable Energy.

  • Evaluating Residential Off-grid & On-grid Capabilities in Hawaii. Works and analysis include use of simulation software Polysun, electrical load profiles, load diagram graphs, and load sizing for battery, inverter, and panels. Programming in Matlab to produce load diagrams and importing load profiles.

 

B.S. in Mathematics, Applied Mathematics, Hawaii Pacific University (2011-2014)

Advanced course projects/presentations include:

MATH 4470/4471 Applied Mathematics I & II.

  • Are you safe in your apartment building? External force analysis on an N-story building (Capstone Group Project). Award for Hawaii Pacific University Capstone Symposium, 2nd Place http://www.hpu.edu/CAIT/capstone.html. Evaluated the effectiveness, to a high probability, of a targeted force on a structure that is placed geographically close to target points, such as fault lines and predicted epicenters. Modeled analysis of different modes, natural frequency, and harmonics to predict quality of strike on an N-story building and reaction to a given an outside force, including earth quakes and inertial impact of highly target-specific systems. Analysis of added dampening constants and methods of adding dampening forces. Implemented advanced second order linear algebra techniques to model such a building. Utilized Matlab to graph projected results of second order differential after a period of time given.
  • Kinematic Analysis of Rigid Body Dynamics. Analysis of solid bodied object with given parameters falling through earths atmospheres with a given time varying air resistance. Implementation of numerical methods and special case differential equation (Riccati equation). Utilized Matlab for numerical approximations for first order differential equation distance, landing time, and impact velocity.

MATH 3110 Foundations of Math Logic & Application.

  • Halting Problem Presentation. Research and course lecturer on the work of Alonzo Church and Alan Turing’s Halting Problem. Informative to prove that an arbitrary computer program with a given input is found undecidable whether the program will terminate or continue to run forever. Proven by the use of Turning Machines and a diagonalization argument.

MATH 3500 Numerical Methods.

  • Applied appropriate numerical methods to various types of engineering problems. Utilized and explored various Matlab commands to demonstrate approximations, finding roots of equations, curve fitting, interpolation, and solutions to various ordinary differential equations.

CSCI 2911/2912/2916 Computer Science I & II with Lab.

  • Object Oriented Programming for Casino Games and Interactive Maps. Used object-oriented programming in Java and randomization processes to create simulated games with probability analysis. Implemented sorting and search algorithms. Utilized large sets of earthquake data to produce an interactive map using Google Maps API and Unfolding Maps API detailing the location of earthquake epicenters and their magnitudes. Provide interactive information based on user input requests on the image and distance from the epicenter. Used Maps API to provide elevated satellite imagery (cartographic data) for a variety of task such as navigation, incident impact overlays, and population overlays.

 

cleverhans-blog. “Privacy and Machine Learning: Two Unexpected Allies?,” April 29, 2018. http://cleverhans.io/privacy/2018/04/29/privacy-and-machine-learning.html.
Library for Training Machine Learning Models with Privacy for Training Data: Tensorflow/Privacy. 2018. Reprint, tensorflow, 2019. https://github.com/tensorflow/privacy.
Library for Training Machine Learning Models with Privacy for Training Data: Tensorflow/Privacy. 2018. Reprint, tensorflow, 2019. https://github.com/tensorflow/privacy.
McMahan, H. Brendan, Galen Andrew, Ulfar Erlingsson, Steve Chien, Ilya Mironov, Nicolas Papernot, and Peter Kairouz. “A General Approach to Adding Differential Privacy to Iterative Training Procedures,” December 15, 2018. https://arxiv.org/abs/1812.06210v2.
Papernot, Nicolas, Martín Abadi, Úlfar Erlingsson, Ian Goodfellow, and Kunal Talwar. “Semi-Supervised Knowledge Transfer for Deep Learning from Private Training Data,” October 18, 2016. https://arxiv.org/abs/1610.05755v4.
Pathak, Manas A, Shantanu Rane, and Bhiksha Raj. “Multiparty Differential Privacy via Aggregation of Locally Trained Classifiers,” n.d., 12.
secML. “Class 4: Differential Privacy In Action · SecML.” Accessed April 20, 2019. https://secml.github.io/class4/.
Simulate a Federated Setting and Run Differentially Private Federated Learning.: SAP/Machine-Learning-Diff-Private-Federated-Learning. 2018. Reprint, SAP, 2019. https://github.com/SAP/machine-learning-diff-private-federated-learning.
Steephenson, Benjamin. “Implementing Differential Privacy Using Randomized Response Algorithms,” n.d., 7.