Gerhard P. Hancke

City University of Hong Kong

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Adnan M. Abu‐Mahfouz

Council for Scientific and Industrial Research

Bruno Silva

City University of Hong Kong

Daniel Ramotsoela

University of Cape Town

Keith Mayes

Royal Holloway University of London

Qiao Hu

Hunan University

Adeiza James Onumanyi

Council for Scientific and Industrial Research

Konstantinos Markantonakis

Royal Holloway University of London

Dutliff Boshoff

City University of Hong Kong

Umair Mujtaba Qureshi

Chinese University of Hong Kong

Raphael E. Nkrow

City University of Hong Kong

Cooperative Institutions

City University of Hong Kong

University of Pretoria

Institute of Electrical and Electronics Engineers

Chinese Academy of Sciences

Council for Scientific and Industrial Research

Royal Holloway University of London

Tshwane University of Technology

Nanjing University of Aeronautics and Astronautics

Tsinghua University

Shanghai Jiao Tong University

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A Session Hijacking Attack Against a Device-Assisted Physical-Layer Key Agreement

IEEE Transactions on Industrial Informatics (2019)

Qiao Hu Bianxia Du Konstantinos Markantonakis Gerhard P. Hancke

Physical-layer key agreement is used to generate a shared key between devices on demand. Such schemes utilize the characteristics of the wireless channel to generate the shared key from the device-to-device channel. As all characteristics are time-dependent and location-dependent, it is hard for eavesdroppers to get the key. However, most research works in this area use passive attack models whereas active attacks that aim at manipulating the channel and key are also possible. Physical-layer key agreement with User Introduced Randomness (PHYUIR) is a solution similar to the Diffie-Hellman protocol against such a kind of active attack. The users (devices) introduce their own randomness to help to prevent active attacks. In this paper, we analyze the possibility of launching a session hijacking attack on PHY-UIR to allow an attacker to control the shared key established. The session hijacking attack manipulates the key agreement through a man-in-the-middle interaction and forces legitimate devices to run the PHY-UIR protocol with the attacker. Our simulation and experiment results validate our attack and show the high performance of our attack on manipulating the generated key. We also propose PHY-UIR± where devices simultaneously exchange information about the established shared keys, which allows them to detect whether they have agreed to different keys with a third party.

Session key

PHY

Key-agreement protocol

Key generation

Shared secret

Application layer

10.1109/tii.2019.2923662

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Citations (27)

Autonomous Interference Mapping for Industrial Internet of Things Networks Over Unlicensed Bands: Identifying Cross-Technology Interference

IEEE Industrial Electronics Magazine (2020)

Simone Grimaldi Aamir Mahmood Syed Ali Hassan Mikael Gidlund Gerhard P. Hancke

The limited coexistence capabilities of current Internet-of-things (IoT) wireless standards produce inefficient spectrum utilization and mutual performance impairment. The entity of the issue escalates in industrial IoT (IIoT) applications, which instead have stringent quality-of-service requirements and exhibit very-low error tolerance. The constant growth of wireless applications over unlicensed bands mandates then the adoption of dynamic spectrum access techniques, which can greatly benefit from interference mapping over multiple dimensions of the radio space. In this article, the authors analyze the critical role of real-time interference detection and classification mechanisms that rely on IIoT devices only, without the added complexity of specialized hardware. The trade-offs between classification performance and feasibility are analyzed in connection with the implementation on low-complexity IIoT devices. Moreover, the authors explain how to use such mechanisms for enabling IIoT networks to construct and maintain multidimensional interference maps at run-time in an autonomous fashion. Lastly, the authors give an overview of the opportunities and challenges of using interference maps to enhance the performance of IIoT networks under interference.

Radio spectrum

10.1109/mie.2020.3007568

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Citations (10)

Efficient Implementation of Kyber on Mobile Devices

Lirui Zhao Jipeng Zhang Junhao Huang Zhe Liu Gerhard P. Hancke

Kyber, an IND-CCA-secure key encapsulation mechanism (KEM) based on the MLWE problem, has been shortlisted for the third round evaluation of the NIST Post-Quantum Cryptography Standardization. In this paper, we explored the optimizations of Kyber in high-performance processors from the ARM Cortex-A series, which are widely used in mainstream mobile phones. To improve the performance of Kyber, we utilized the powerful SIMD instruction set NEON in an ARMv8-A to parallelize the core modules of Kyber, i.e., modular reduction and NTT. Specifically, we specially designed the optimized implementation based on the characteristic of the NEON instruction set for the Barrett and Montgomery reduction algorithms. To make full use of the computing power of NEON instructions, we proposed a novel strategy for computing the 16-bit Barrett reduction without handling the 32-bit intermediate result. Our Barrett and Montgomery reduction showed 8.52 and 8.89 times faster than the reference implementation. As for NTT/INTT, we adopted the 2+5 layer merging strategy on an ARMv8-A to implement NTT/INTT after carefully analyzing the register occupancy of various layer merging techniques. Thanks to the selected layer merging strategy, our NTT and INTT achieved 11.89 and 13.45 times speedups compared with the reference implementation. Our optimized software achieved 1.77×, 1.85×, and 2.16× speedups for key generation, encapsulation, and decapsulation compared with Kyber's reference implementation.

SIMD

10.1109/icpads53394.2021.00069

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Citations (4)

Interpretable Heart Disease Detection Model for IoT-Enabled WBAN Systems

IEEE Sensors Journal (2024)

Damilola D. Olatinwo Adnan M. Abu‐Mahfouz Gerhard P. Hancke Hermanus C. Myburgh

10.1109/jsen.2024.3520866

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Citations (0)

May the Force Be with You: Force-Based Relay Attack Detection

Lecture notes in computer science (2018)

Iakovos Gurulian Gerhard P. Hancke Konstantinos Markantonakis Raja Naeem Akram

10.1007/978-3-319-75208-2_9

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Citations (3)

Investigating Distance Bounding for Delegated Proof-of-Proximity Consensus within IIoT

2022 IEEE 31st International Symposium on Industrial Electronics (ISIE) (2022)

Lehlogonolo P. I. Ledwaba Gerhard P. Hancke Sherrin J. Isaac

With limited processing, energy and storage along with a deadline sensitive operational environment, the combination of the Industrial IoT (IIoT) with distributed ledger technologies (DLTs) could serve to introduce intolerable latency into network processes; counteracting the potential advantages that come from combining the two technologies. In an effort to improve the compatibility of DLTs for the industrial informatics context, the authors developed a lightweight consensus for IIoT environments based off delegated proof of stake (DPoS), called Delegated Proof of Proximity (DPoP), to limit the processing and energy effort required by DLTs. DPoP will, however, require an existing, IIoT neighbour discovery process to facilitate a proof of proximity for the consensus process. Thus, this preliminary work aims to evaluate distance bounding as a possible mechanism for establishing a secure proof of proximity and neighbour discovery between nodes during the DPoP consensus process to improve the scalability and flexibility of DLT solutions, like Ethereum, for IIoT use cases.

Proof of concept

Bounding overwatch

10.1109/isie51582.2022.9831631

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Citations (0)

Preventing Overshadowing Attacks in Self-Jamming Audio Channels

IEEE Transactions on Dependable and Secure Computing (2018)

Qiao Hu Yuanzhen Liu Anjia Yang Gerhard P. Hancke

Recently there has been a growing interest in short-range communication using audio channels for device pairing and as a self-jamming communication medium. Given that such channels are audible to participants they are considered more resistant to active attacks, i.e., the attack signal would be heard by the participants. In this paper, we investigate the validity of this assumption using two prominent acoustic self-jamming systems implementations. We show that basic overshadowing attacks are possible in these systems and that these attacks cannot be effectively detected by the participants if the attacker is close to the receiving device. Finally, we propose a novel physical-layer solution for effectively detecting overshadowing attacks, which can improve state-of-the-art acoustic self-jamming systems by ensuring channel integrity while not requiring fundamental modifications to these schemes.

10.1109/tdsc.2018.2873767

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Citations (10)

A Review of Artificial Intelligence Based Intrusion Detection for Software-Defined Wireless Sensor Networks

S. Masengo Wa Umba Adnan M. Abu‐Mahfouz Daniel Ramotsoela Gerhard P. Hancke

Wireless communications and Wireless Sensor Networks (WSNs) are intensively used in manufacturing industries, in medical devices, for the determination of the position and for the guidance of military drones and bombs. Given the scope of utilization of WSNs, the security of wireless communications is a very critical problem that must be tackled accordingly. A Software-Defined Wireless Sensor Network (SDWSN) is realized by infusing a Software Defined Network (SDN) model in a WSN. In this paper, the cryptography schemes as well as the security threats related to SDWSNs are identified and the Artificial Intelligence (AI) techniques used to detect intrusions in SDWSNs are presented. It is shown that a two-level security model combining cryptography schemes and AI techniques can be used to fight malicious attacks against SDWSNs.

Drone

10.1109/isie.2019.8781458

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Citations (20)

Pose Estimation of a Mobile Robot Based on Fusion of IMU Data and Vision Data Using an Extended Kalman Filter

Sensors (2017)

Mary B. Alatise Gerhard P. Hancke

Using a single sensor to determine the pose estimation of a device cannot give accurate results. This paper presents a fusion of an inertial sensor of six degrees of freedom (6-DoF) which comprises the 3-axis of an accelerometer and the 3-axis of a gyroscope, and a vision to determine a low-cost and accurate position for an autonomous mobile robot. For vision, a monocular vision-based object detection algorithm speeded-up robust feature (SURF) and random sample consensus (RANSAC) algorithms were integrated and used to recognize a sample object in several images taken. As against the conventional method that depend on point-tracking, RANSAC uses an iterative method to estimate the parameters of a mathematical model from a set of captured data which contains outliers. With SURF and RANSAC, improved accuracy is certain; this is because of their ability to find interest points (features) under different viewing conditions using a Hessain matrix. This approach is proposed because of its simple implementation, low cost, and improved accuracy. With an extended Kalman filter (EKF), data from inertial sensors and a camera were fused to estimate the position and orientation of the mobile robot. All these sensors were mounted on the mobile robot to obtain an accurate localization. An indoor experiment was carried out to validate and evaluate the performance. Experimental results show that the proposed method is fast in computation, reliable and robust, and can be considered for practical applications. The performance of the experiments was verified by the ground truth data and root mean square errors (RMSEs).

RANSAC

Sensor Fusion

Iterative closest point

10.3390/s17102164

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Citations (183)

Attack detection in water distribution systems using machine learning

Human-centric Computing and Information Sciences (2019)

Daniel Ramotsoela Gerhard P. Hancke Adnan M. Abu‐Mahfouz

Abstract The threat to critical water system infrastructure has increased in recent years as is evident from the increasing number of reported attacks against these systems. Preventative security mechanisms are often not enough to keep attackers out so a second layer of security in the form of intrusion detection is paramount in order to limit the damage of successful attacks. In this paper several traditional anomaly detection techniques are evaluated in the context of attack detection in water distribution systems. These algorithms were centrally trained on the entire feature space and compared to multi-stage detection techniques that were designed to isolate both local and global anomalies. A novel ensemble technique that combines density-based and parametric algorithms was also developed and tested in the application environment. The traditional techniques had comparable results to the multi-stage systems and when used in conjunction with a local anomaly detector the performances of these algorithms were greatly improved. The developed ensemble technique also had promising results outperforming the density-based techniques and having comparable results to the parametric algorithms.

Ensemble Learning

Feature (linguistics)

Feature vector

10.1186/s13673-019-0175-8

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Citations (66)