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Saad Khan 0001
Person information
- affiliation: University of Huddersfield, UK
Other persons with the same name
- Saad Khan 0002 — King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia
- Saad Khan 0003 — Educational Testing Service R&D, Princeton, NJ, USA
- Saad Khan 0004
— Albert Einstein College of Medicine, New York, NY, USA
- Saad Khan 0005
- Saad Khan 0006 — Rochester Institute of Technology, NY, USA
- Saad Khan 0007 — Sarhad University of Science and Information Technology, Peshawar, Pakistan
- Saad Khan 0008 — FineTune Learning, Boston, MA, USA
- Saad Khan 0009 — Amazon, USA
- Saad Khan 0010 — Nokia
- Saad Khan 0011
- Saad Khan 0012 — St. Cloud State University, MN, USA
- Saad Khan 0013 — University of Applied Sciences Stuttgart, Germany
- Saad Khan 0014 — Indian Institute of Technology Bombay, India
- Saad Ullah Khan 0002
- Saad Ullah Khan 0003 — University of Science and Technology, Bannu, Pakistan
- Saad Ullah Khan 0004 — Amity University Rajasthan, Jaipur, India
- Saad Ullah Khan 0005 — National University of Sciences & Technology, Islamabad, Pakistan
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2020 – today
- 2024
- [j18]Mohamed Ayyash
Cybersecurity Education and Awareness Among Parents and Teachers: A Survey of Bahrain. IEEE Access 12: 86596-86617 (2024) - [j17]Omar Alshaikh
Exploring perceptions of decision-makers and specialists in defensive machine learning cybersecurity applications: The need for a standardised approach. Comput. Secur. 139: 103694 (2024) - [j16]Khalid Al Ajlan, Tariq Alsboui, Omar Alshaikh, Isa Inuwa-Dutse, Saad Khan, Simon Parkinson:
The Emerging Challenges of Wearable Biometric Cryptosystems. Cryptogr. 8(3): 27 (2024) - 2023
- [j15]Rami Mubarak
A Survey on the Detection and Impacts of Deepfakes in Visual, Audio, and Textual Formats. IEEE Access 11: 144497-144529 (2023) - [j14]Simon Parkinson
A Survey on Empirical Security Analysis of Access-control Systems: A Real-world Perspective. ACM Comput. Surv. 55(6): 123:1-123:28 (2023) - [j13]Monika Roopak
Comparison of deep learning classification models for facial image age estimation in digital forensic investigations. Forensic Sci. Int. Digit. Investig. 47: 301637 (2023) - [j12]Saad Khan
Context-based irregular activity detection in event logs for forensic investigations: An itemset mining approach. Expert Syst. Appl. 233: 120991 (2023) - [j11]Simon Parkinson
An empirical analysis of keystroke dynamics in passwords: A longitudinal study. IET Biom. 12(1): 25-37 (2023) - [c7]Saad Khan
Automated Planning to Prioritise Digital Forensics Investigation Cases Containing Indecent Images of Children. ICAPS 2023: 500-508 - 2022
- [j10]Simon Parkinson
Identifying high-risk over-entitlement in access control policies using fuzzy logic. Cybersecur. 5(1): 6 (2022) - [c6]Saad Khan
Multi-Mobile Agent Security by Design Itinerary Planning Approach in Wireless Sensor Network. UbiSec 2022: 534-544 - [c5]Omar Alshaikh
On the Variability in the Application and Measurement of Supervised Machine Learning in Cyber Security. UbiSec 2022: 545-555 - 2021
- [j9]Saad Khan
Biometric Systems Utilising Health Data from Wearable Devices: Applications and Future Challenges in Computer Security. ACM Comput. Surv. 53(4): 85:1-85:29 (2021) - [j8]Simon Parkinson
Password policy characteristics and keystroke biometric authentication. IET Biom. 10(2): 163-178 (2021) - [j7]Iffat Gheyas
OCEAN: A Non-Conventional Parameter Free Clustering Algorithm Using Relative Densities of Categories. Int. J. Pattern Recognit. Artif. Intell. 35(5): 2150017:1-2150017:31 (2021) - 2020
- [j6]Saad Khan
Low-cost fitness and activity trackers for biometric authentication. J. Cybersecur. 6(1) (2020)
2010 – 2019
- 2019
- [b1]Saad Ullah Khan:
Discovering and utilising expert knowledge from security event logs. University of Huddersfield, UK, 2019 - [j5]Simon Parkinson
Creeper: a tool for detecting permission creep in file system access controls. Cybersecur. 2(1): 14 (2019) - [j4]Saad Khan
Discovering and utilising expert knowledge from security event logs. J. Inf. Secur. Appl. 48 (2019) - 2018
- [j3]Saad Khan
Eliciting and utilising knowledge for security event log analysis: An association rule mining and automated planning approach. Expert Syst. Appl. 113: 116-127 (2018) - [j2]Simon Parkinson
Identifying irregularities in security event logs through an object-based Chi-squared test of independence. J. Inf. Secur. Appl. 40: 52-62 (2018) - [p2]Saad Khan
Review into State of the Art of Vulnerability Assessment using Artificial Intelligence. Guide to Vulnerability Analysis for Computer Networks and Systems 2018: 3-32 - [p1]Saad Khan
Automated Planning of Administrative Tasks Using Historic Events: A File System Case Study. Guide to Vulnerability Analysis for Computer Networks and Systems 2018: 159-182 - 2017
- [j1]Saad Khan, Simon Parkinson, Yongrui Qin:
Fog computing security: a review of current applications and security solutions. J. Cloud Comput. 6: 19 (2017) - [c4]Saad Khan, Simon Parkinson:
Towards A Multi-Tiered Knowledge-Based System for Autonomous Cloud Security Auditing. AAAI Workshops 2017 - [c3]Simon Parkinson
Security auditing in the fog. ICC 2017: 191:1-191:9 - [c2]Saad Khan
Causal Connections Mining Within Security Event Logs. K-CAP 2017: 38:1-38:4 - [c1]Saad Khan
A Multi-layered Cloud Protection Framework. UCC (Companion") 2017: 233-238
Coauthor Index
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last updated on 2024-11-20 20:59 CET by the dblp team
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