Kemp Security

Dr. Clifford A. Kemp

| cliffkempfl@gmail.com  | Jensen Beach, FL

LinkedIn Profile: www.linkedin.com/in/dr-cliff-kemp-30ba39145

Website: https://kempsecurity.com/

Educational Background

• Doctor of Philosophy (Ph.D.) in College of Engineering and Computer Science
  Florida Atlantic University
• Master of Science (M.S.) in Computer Science
  Florida Atlantic University
• Master of Education (M.Ed.) in Instructional Technology
  Florida Atlantic University
• Bachelor of Arts (B.A.) in Economics
  Florida Atlantic University

Employment History

Professor in Information Technology

Indian River State College, Fort Pierce, Florida

Adjunct Instructor, Information Technology

Indian River State College, Fort Pierce, Florida

IT Tech Support

St. Lucie County School Board, Fort Pierce, Florida

Responsible for maintaining school networks, troubleshooting hardware and software issues and training.

Teaching Experience

Professor in Computer Science and Engineering

Indian River State College, Fort Pierce, Florida

• Core Courses Taught; Computer Hardware and Software, Introduction to Wireless Technology, Introduction to Wireless Security, Security Fundamentals, Linux Fundamentals, Network Forensics, Windows Professional, Windows Server, Network Administration, Security Essentials, Data Mining & Warehousing, Applications in Informational Security, and Network Security & Cryptography.
• Developed and implemented innovative curricula focusing on modern trends such as AI, networking, cybersecurity, and virtual machines.
• Completed my Ph.D. at Florida Atlantic University; The collecting and analyzing various cyber-attacks such as slow denial of service attacks implementing machine learning algorithms to find patterns in network traffic by distinguishing between attacks and normal traffic.

Certifications

• Microsoft: Microsoft Certified Network Engineer (MCSE) 
• Cisco: Cisco Certified Network Associate (CCNA) 
• CompTIA: Network+ and A+
• CWNP: Certified Wireless Technology Specialist (CWTS) 
• SANS GIAC Certified Enterprise Defender (GCED)
• Google: AI Essentials

Skills

• Expertise in cybersecurity, Linux, cloud computing, and big data technologies. 
• Proficiency in networking protocols, security mechanisms, and virtual machines. 
• Knowledge of machine learning frameworks like TensorFlow and PyTorch. 
• Programming skills in Bash scripting and Python.
• Experience with three different LMS’s; Angel, Blackboard, and Canvas.

Professional Affiliations

• SANS Technology Institute
• CompTIA Member
• The National Centers of Academic Excellence in Cybersecurity
• National Science Foundation Cyber Security Researcher
• Regional Center for Nuclear Education and Training (RCNET)

Research Interests

• Network Security and Defense
• Hardware and Software for Computer Systems
• Virtual Machine Systems
• Wireless Network Administration and Security
• AI: Machine Learning

Research Experience

I have extensively contributed to cybersecurity research, including:

• Detecting various cyber-attacks using machine learning algorithms.
• Analyzing network traffic for patterns in cyber-attacks.
• Developing Frameworks for hands-on labs for students using virtual machine servers.

Grants and Awards

• Cyber Defense Two-Year Education (CAE2Y) / NSA Grant (2018) 
• Cyber Defense Four-Year Education (CAE4Y) Grant (2020) 
• iConnect/NSF Grant (2019)

Professional Publications and Research Papers

I have over six first author and thirteen co-author peer reviewed published research papers.  Below I have listed five of those papers.

1. C. Kemp, C. Calvert, and T. M. Khoshgoftaar and J. L. Leevy. An approach to application-layer DoS detection. Journal of Big Data 10, no. 1 (2023): 22.
2. C. Kemp, C. Calvert, and T. Khoshgoftaar. “Netflow feature evaluation for the detection of slow read HTTP attacks.”  CRC Press, 2020.
3. C. Kemp, C. Calvert, and T. M. Khoshgoftaar. “Detection methods of slow read DoS using full packet capture data.”  IEEE International Conference on Information Reuse and Integration for Data Science (IRI), 2020. 
4. C. Kemp, C. Calvert, and T. M. Khoshgoftaar, Detection methods of slow read dos using full packet capture data, in 2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science (IRI). IEEE, 2020, pp. 9–16.
5. C. Kemp, C. Calvert, and T. Khoshgoftaar, utilizing NetFlow data to detect slow read attacks, in 2018 IEEE International Conference on Information Reuse and Integration (IRI). IEEE, 2018, pp. 108–116.