Cyber Security Research Group (CSRG)
Unit(s) of assessment: Computer Science and Informatics
School: School of Science and Technology
Cyber Security Research Group (CSRG)
The cyber security research group (CSRG) is a dynamic team of seasoned professionals dedicated to researching and implementing effective solutions to safeguard against cyber threats. Our diverse team comprises experts in various areas of cyber security, including network security, cryptography & Quantum cryptography solutions, threat intelligence & modelling, malware analysis, penetration testing, as well as secure, regulated and trustworthy artificial intelligence systems, among others.
Our group is committed to advancing the field of cyber security through cutting-edge research and development, with a focus on creating innovative and practical solutions to address complex security challenges faced by organisations today. By staying at the forefront of the latest technological advancements and emerging threats, we can provide our clients with tailored solutions that meet their unique needs and requirements.
Our research and development efforts are focused on not only addressing current security challenges but also anticipating future ones. We collaborate with academic institutions, industry partners, and government agencies to share knowledge and resources to drive innovation in the field of cyber security.
Our goal is to provide our clients with the highest level of protection against cyber threats, ensuring their information assets are secure and their operations are uninterrupted. By partnering with CSRG, you can trust that your organisation is in capable hands.
School of Science & Technology
Dr Funminiyi Olajide
School of Science & Technology
Selected Partners and Collaborators
- National Cyber Security Centre NCSC
- De Montfort University, Cyber Security Centre.
- Catapult Company
- University of Ha'il, Saudi Arabia
- Taibah University, Saudi Arabia.
- Horiba - Mira
- University of Manchester
- University of Ulster
- Cardiff Metropolitan University
- CICESE (Centro de Investigacion Cientifica y de Educacion) – Mexico
- Torrens University Australia, Artificial Intelligence Research and Optimization
- Indian Institute of Technology Roorkee
- Indian Institute of Technology Delhi
- University of Central Lancashire
- Cobac Security
- JMVL Ltd
- Jawaharlal Nehru University New Delhi
Drive with Confidence
A Safe and Secure Driving System to Mitigate Remote Vehicle Hijacking Risks. The system focuses on:
1) The development of a secure vehicular communication system considering physical layer and protocol level security as well as network segmentation approach.
2) Integrating an in-vehicle intrusion detection system using artificial intelligence to monitor the vehicle's network for suspicious activity, such as attempts to connect to the vehicle's control systems from an unauthorised connection or device.
PRAVE Project (PRoactive Authentication and Verification Embedded Model for Critical Cyber-Physical Systems).
This Research and Development project will innovate a new proactive security model for protecting cyber-physical systems in the CNI using a trustworthy artificial intelligent approach. PRAVE will focus on proactive authentication and verification protocol with the involvement of some of the physical aspects from the connected smart things within the CNI.
This project has developed a secure and trustworthy AI platform suitable for AI developers and data scientists, which provides a scoring mechanism to measure the quality and trust levels of datasets and AI/ML algorithms during the development and deployment phases. The TrustMe platform is running based on a local-host web application with enabled features for designing, developing, and implementing explainable and trustworthy AI applications. TrustMe platform also offers a data quality score using the Quality of Data (QoD) estimator.
Cyber Security for Smart EV Charging Network
The core objective of the E-Mobility Cyber Security project is to foster NTU-Industry research collaboration toward EV-centric smart, secure, and green mobility. The expertise-centric research collaboration consists of three working groups including vehicular communication for EV charging management, cyber security of charging infrastructure, and data analytics for cyber risk prediction.
DroNET Cyber Security for Next-Genration Drone Networking
DroNET is targeting to innovate novel security techniques for connected drone communication for enabling range of next-generation drone use cases to realize securely connected and autonomous drones. A technology resource team will be built up in the department utilizing the drone-centric communication networking, robotics, and security expertise at NTU.
LiNET-Visible Light Secure Networking for Connected Vehicles
The LiNET project is targeting to innovate visible light communication-enabled networking framework for enabling CAV traffic environments. Building on our existing research on connected vehicles, this team will focus on developing a secure visible light communication framework for enabling CAV.
An AI-based platform helping cyber security professionals to detect, predict and manage stress. Showing cyber professionals and cyber teams how to reduce and manage stress levels. Improving your resilience and wellbeing helping you manage cyber crime from a position of strength.
Group research output
1) Analysis of Accelerometer Data for Personalised Mood Detection in Activities of Daily Living, PERCOM 2023 (accepted)
2) Analysis of accelerometer data for personalised abnormal behaviour detection in activities of daily living, UCAmI 2022
3) DIMS: A tool for setting up defects and impurities CASTEP calculations, Computational Materials Science 2022
4) IoT-Based Activities of Daily Living for Abnormal Behavior Detection: Privacy Issues and Potential Countermeasures, IEEE Internet of Things Magazine 2021
5) Fusion of Unobtrusive Sensing Solutions for Home-Based Activity Recognition and Classification Using Data Mining Models and Methods, Applied Sciences 2021.
Project 1: Mar 2023. Quantum Simuiation Algorithms for FinTech. Award from UK Quantum Computer and Simulation Hub. Total £100K for one year.
Project 2. July 2023. Quantum Predictive Sensing. Collaboration with Toyota and ETH Zurich.
During the collaboration “Predictive Sensing” will be investigated. We will investigate the usability of gate-based quantum computing for computer vision applications. In this context NTU will contribute by:
Aiding in selecting the right application for gate-based quantum computing in computer vision; Providing the background knowledge to select a quantum computing algorithm that has the potential to solve the computer vision task.
N. Kumar, R. Chaudhary, O. Kaiwartya, N. Kumar. ChaseMe: A Heuristic Scheme for Electric
Vehicles Mobility Management on Charging Stations in a Smart City Scenario, IEEE
Transactions on Intelligent Transportation Systems , 23(9), 16048-16058, 2022.
2. PK. Kashyap, S. Kumar, A. Jaisawal, O. Kaiwartya, M. Kumar, U. Dohare. DECENT: Deep
Learning Enabled Green Computation for Edge Centric 6G Networks. IEEE Transactions on
Network and Service Management, 19(3),2163-2177, 2022.
3. A. Jaisawal, S. Kumar, O. Kaiwartya, PK Kashaya, E. Kanjo, N. Kumar, H. Song. Quantum
Learning Enabled Green Communication for Next Generation Wireless Systems. IEEE
Transactions on Green Communications and Networking, 5(3), 1015-1028, 2021.
4. A. Jaisawal, S. Kumar, O. Kaiwartya, M. Prasad, N. Kumar, H. Song, Green computing in IoT:
Time slotted simultaneous wireless information and power transfer. Computer
Communications, Elsevier, 168(1), 155-169, 2021.
5. R. Yadav, W. Zhang, O. Kaiwartya, H. Song, S. Yu. Energy-latency tradeoff for dynamic
computation offloading in vehicular fog computing, IEEE Transactions on Vehicular
Technology, 69(12), 14198-14211, 2020.
6. A. Khaswaneh, O. Kaiwartya, LM. Abualigah, J. Lloret. Green Computing in Underwater
Wireless Sensor Networks Pressure Centric Energy Modeling, IEEE Systems Journal, 14(4),
7. Y. Cao, T. Jiang, O. Kaiwartya, H. Shun, H. Zhou, R. Wang. Toward Pre-Empted EV Charging
Recommendation Through V2V-Based Reservation System IEEE Transactions on Systems,
Man, and Cybernetics: Systems, 51(5), 30263039, 2019.
8. GK. Verma, BB. Singh, N. Kumar, O. Kaiwartya, MS. Obaidat PFCBAS: Pairing Free and
Provable Certificate-Based Aggregate Signature Scheme for the e-Healthcare Monitoring
System. IEEE Systems Journal, 14(2), 1704-1715, 2019.
9. O. Kaiwartya, Y. Cao, J. Lloret, S. Kumar, N. Aslam, R. Kharel, AH. Abdullah,
Geometry-based Localization for GPS Outage in Vehicular Cyber Physical Systems. IEEE
Transactions on Vehicular Technology, 67(5): 3800-3812, 2018.
10. Y. Cao, H. Song, O. Kaiwartya, B. Zhou, Y. Zhuang, Y. Cao, H. Zhang, Mobile Edge
Computing for Big-Data-Enabled Electric Vehicle Charging IEEE Communications
Magazine, 56(3), 150-156, 2018.
11. O. Kaiwartya, AH. Abdullah, Y. Cao, J. Lloret, RR Shah, M. Prasad, S. Prakash, Virtualization
in wireless sensor networks: Fault tolerant embedding for internet of things, IEEE Internet of
Things Journal, 5(2), 571-580, 2017.
12. Y. Cao, O. Kaiwartya, R. Wang, T. Jiang, Y. Cao, N. Aslam, G. Sexton, Toward Efficient,
Scalable, and Coordinated On-the-Move EV Charging Management, IEEE Wireless
Communications, 24(2), 66-73, 2017.
13. O. Kaiwartya, AH. Abdullah, Y. Cao, RS. Rao, S. Kumar, DK.Lobiyal, IF Isnin, X. Liu, RR.
Shah, T-MQM: Testbed based Multi-metric Quality Measurement of Sensor Deployment for
Precision Agriculture-A Case Study, IEEE Sensors Journal, 24(2), 16(23), 8649-8664, 2016.
14. O. Kaiwartya, AH. Abdullah, Y. Cao, A. Altameem, M. Prasad, CT. Lin, X. Liu, Internet of
Vehicles: Motivation, Layered Architecture, Network Model, Challenges and Future Aspects,
IEEE Access, 4(1), 5356-5373, 2016.
Peer-Reviewed Conference Papers (12 representative papers, 2 for each year):
1. M. Aljaidi, N. Aslam, X. Chen, O. Kaiwartya, YA. Al-Gumaei, M. Khalid, A Reinforcement
Learning-based Assignment Scheme for EVs to Charging Stations, IEEE 95th Vehicular
Technology Conference: (VTC2022-Spring), Helsinki, Finland, 19-22 June 2022.
2. AU. Makarfi, R. Kharel, KM. Rabie, X. Li, OS. Badarneh, G. Nauryzbayev, S. Arzykulov, O.
Kaiwartya. Performance analysis of SWIPT networks over composite fading channels, IEEE
Eighth International Conference on Communications and Networking (ComNet),
Hammamet, Tunisia, 27-30 Oct 2020.
3. M Aljaidi, N Aslam, X Chen, O. Kaiwartya, YA Al-Gumaei. Energy-efficient EV charging
station placement for E-mobility, IECON 2020 The 46th Annual Conference of the IEEE
Industrial Electronics Society, Singapore, 18-21 Oct 2020.
4. A. Makarfi, K. Rabie, O. Kaiwartya, O. Badarneh, G. Nauryzbayev, R. Kharel. Physical Layer
Security in RIS-assisted Networks in Fisher-Snedecor Composite Fading, International
Symposium on Communication Systems, Networks and Digital Signal Processing,
CNSDSP, Porto, Portugal, 20-22 July 2020.
5. A. Makarfi, K. Rabie, O. Kaiwartya, O. Badarneh, X. Li, R. Kharel. Reconfigurable intelligent
surface enabled IoT networks in generalized fading channels, ICC 2020 - 2020 IEEE
International Conference on Communications (ICC), Dublin, Ireland, 7-11 June 2020.
6. A. Makarfi, K. Rabie, O. Kaiwartya, O. Badarneh, X. Li, R. Kharel. Physical layer security in
vehicular networks with reconfigurable intelligent surfaces, 2020 IEEE 91st Vehicular
Technology Conference (VTC2020-Spring), Antwerp, Belgium, 25-28 May 2020.
7. A. Makarfi, R. Kharel, K. Rabie, O. Kaiwartya, G. Nauryzbayev. Physical layer security in
vehicular communication networks in the presence of interference, 2019 IEEE Global
Communications Conference (GLOBECOM), Waikoloa, HI, USA, 9-13 Dec 2019.
8. M. Aljaidi, N. Aslam, O. Kaiwartya. Optimal placement and capacity of electric vehicle
charging stations in urban areas: Survey and open challenges, 2019 IEEE Jordan
International Joint Conference on Electrical Engineering and Information Technology
(JEEIT), Amman, Jordan, 9-1a April 2019.
9. L Farhan, R Kharel, O. Kaiwartya, M. Quiroz-Castellanos, A Alissa, M. Abdulsalam. A
Concise Review on Internet of Things (IoT)-Problems, Challenges and Opportunities, 2018
11th International Symposium on Communication Systems, Networks & Digital Signal
Processing (CSNDSP), Budapest, Hungary, 18-20 July 2018.
10. A. Aliyu, M. Tayyab, AH. Abdullah, UM. Joda, O. Kaiwartya. Mobile Cloud Computing:
Layered Architecture, 2018 Seventh ICT International Student Project Conference
(ICT-ISPC), Nakhonpathom, Thailand, 11-13 July 2018.
11. R. Kasana, S. Kumar, O. Kaiwartya. Towards location error resilient geographic routing for
VANETs, International Conference on Communication and Computing Systems (ICCCS),
Greater Noida, India, 5-6 May 2017.
12. A. Khatri, S. Kumar, O. Kaiwartya, AH. Abdullah. Optimizing energy consumption and
inequality in wireless sensor networks using NSGA-II, 2017 International Conference on
Computing, Communication and Automation (ICCCA), Gurgaon, India, 9-11 September
Video steganalysis in the transform domain based on morphological structure of the motion vector maps, End-to-end image steganography using deep convolutional autoencoders
 Asmau Wali, Oluwasegun Apejoye, Thejavathy Raja, Jun He and Xiaoqi Ma. A novel approach to identifying DDoS traffic in the Smart Home network via Exploratory Data Analysis, The Second International Conference on Applied Intelligence and Informatics (AII2022), Reggio Calabria, Italy, 1-3 September 2022.
 Asmau Wali, Oluwasegun Apejoye, Jun He and Xiaoqi Ma. An exploratory data analysis of the network behavior of hive home devices. 2021 8th International Conference on Internet of Things: Systems, Management and Security (IOTSMS), Gandia, Spain, 6-9 December 2021.
J. Shahid, R. Ahmad, A. K. Kiani, T. Ahmad “Data Privacy and Protection of IoHT-based Systems: Analysis, Policies, Compliance Issues and Suggestions” mdpi Applied Sciences 2022.
Zeln Ji, A. K. Kiani, Zhijin Qin, R. Ahmad “Power Optimization in Device-to-Device Communications: A Deep Reinforcement Learning Approach with Dynamic Reward”, IEEE Wireless Communication Letters, 2020.
A. Saboor, R. Ahmad A K. Kiani, W. Ahmad, M.M.Alam "Dynamic Slot Allocation using Non Overlapping Backoff Algorithm in 802.15.6 WBAN" Accepted in IEEE Sensors , 2020.
Amna Riaz, A. K. Kiani, Shahzad Saleem, “Access Control for Fog/Cloud enabled IoTs”, International Journal of Computer Science and Information Security, (IJCSIS), Vol. 17, No. 9, September, 2019.
Muhammad Atif, Siddique Latif, A. K. Kiani, Rizwan Ahmad, Junaid Qadir, Adeel Baig, Hisao Ishibuchi, Waseem Abbas , "Soft Computing Techniques for Dependable Cyber-Physical Systems", IEEE Access, Vol. 7, ,pp 72030 – 720499, May, 2020.
Abdul Saboor, Rizwan Ahmad, A K. Kiani, Waqas Ahmad, Yannick Le Moullec, Muhammad Mahtab Alam,"On Research Challenges in Hybrid Medium Access Control Protocols for IEEE 802.15.6 WBANs", IEEE Sensors Journal, DOI 10.1109/JSEN.2018.288378618, pp. 1-13. , Nov, 2018.
M. Arif, A K. Kiani, J. Qadir, "Machine learning based optimized live virtual machine migration over WAN links." Telecommunication Systems Sep, 2016 1-13
A.Riaz, A K. Kiani, Hafiz Farooq, J. Qadir, U. Younas, " Intrusion Detection Systems in Cloud Computing: A Contemporary Review of Techniques and Solutions" Journal of Information Science and Engineering-Special Issue on Cloud Computing and Security Jan, 2017.
Z. Riaz, , M. Arslan. Adnan K. Kiani, S. Azhar. , "CoSMoS: A BIM and Wireless Sensors based Integrated Solution for Worker Safety in Confined Spaces", Automation in Construction, Vol. 45, pp. 96-106, Sep, 2014.
BIRD, J.J., NASER, A. and LOTFI, A., 2023. Writer-independent signature verification; evaluation of robotic and generative adversarial attacks. Information Sciences, 633, pp. 170-181. ISSN 0020-0255
NASER, A., LOTFI, A., MWANJE, M.D. and ZHONG, J., 2022. Privacy-preserving, thermal vision with human in the loop fall detection alert system. IEEE Transactions on Human-Machine Systems. ISSN 2168-2291
NASER, A., LOTFI,
A. and ZHONG, J., 2022. Multiple thermal sensor array fusion towards enabling privacy-preserving human monitoring applications. IEEE Internet of Things Journal. ISSN 2327-4662
NASER, A., LOTFI, A. and ZHONG, J., 2022. Calibration of low-resolution thermal imaging for human monitoring applications. IEEE Sensors Letters. ISSN 2475-1472
NASER, A., LOTFI, A. and ZHONG, J., 2021. Towards human distance estimation using a thermal sensor array. Neural Computing and Applications. ISSN 0941-0643
NASER, A., LOTFI, A. and ZHONG, J., 2020. Adaptive thermal sensor array placement for human segmentation and occupancy estimation. IEEE Sensors Journal. ISSN 1530-437X
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