Publications

2025

1. 

   A Comparative Analysis of Lightweight Hash Functions Using AVR ATXMega128 and ChipWhisperer

   Mohsin Khan, Håvard Dagenborg, and Dag Johansen

   In Proceedings of Nordic Conference on Secure IT Systems (NordSec), Tartu, Estonia, 2025

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   Lightweight hash functions have become important building blocks for security in embedded and IoT systems. A plethora of algorithms have been proposed and standardized, providing a wide range of performance trade-off options for developers to choose from. This paper presents a comparative analysis of 22 key software-based lightweight hash functions, including the finalist from the SHA-3 competition. We use a novel benchmark methodology that combines an AVR ATXMega128 microcontroller with the ChipWhisperer cryptanalysis platform and evaluate and compare the various hash functions along several dimensions, including execution speed, % measured in Cycles per Byte (CpB), memory footprint, and energy consumption. Using the composite E-RANK metric, we provide new insight into the various trade-offs each hash function offers to system developers.

2. 

   Survey of Lightweight Hardware-Based Hash Functions for Security in Constrained IoT Devices

   Mohsin Khan, Elisavet Kozyri, Dag Johansen, and 1 more author

   IEEE Access, 2025

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   This survey provides a comprehensive analysis of lightweight hardware-based hash functions designed for security in constrained IoT devices. It examines the architectural design of sponge- and cipher-based constructions, compares performance metrics such as throughput, area, and energy cost, and analyzes cryptanalytic findings to understand practical security trade-offs. The work offers a structured framework for selecting efficient, resource-aware hash functions suitable for next-generation IoT deployments.

3. 

   System Support for Accountable and Trusted Data Collection and Fog Processing in Remote Electronic Monitoring

   A.B. Ovesen, Mohsin Khan, Håvard Dagenborg, and 1 more author

   In Proceedings of International Conference on Fog and Mobile Edge Computing (FMEC), Florida, USA, 2025

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   Edge data collection systems play an increasingly important role in enabling digital forensics, by facilitating the secure and efficient capture, processing, and transmission of data from remote environments. These systems, however, face challenges related to data integrity, privacy, and accountability, especially when dealing with sensitive data in compliance-driven domains such as video surveillance. Remote Electronic Monitoring systems in industrial fisheries exemplify these challenges, through their deployment in harsh and privacy-sensitive environments. While this field has primarily been focused on challenges with catch estimation and sustainability, this paper describes how the Dorvu system provides support for accountable, traceable, and verifiable edge data collection and processing. This is achieved by providing different stakeholders, such as data subjects and legal authorities, with mechanisms that can be used to verify collected data, monitor system behavior, and challenge decisions made on the grounds of system output, and as such hold the system accountable, while it is deployed in remote areas.

4. 

   Software Benchmarking of NIST Lightweight Hash Function Finalists on Resource-Constrained AVR Platform via ChipWhisperer

   Mohsin Khan, Håvard Dagenborg, and Dag Johansen

   In Proceedings of International Conference on Security and Cryptography (SECRYPT), BilBao, Spain, 2025

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   This paper presents a novel performance evaluation of five key lightweight hash functions on an ATxmega128 microcontroller, using our E-RANK metric as a composite metric that integrates execution speed, memory footprint, and energy efficiency into a unified and balanced ranking. We leverage hardware-specific profiling techniques using the ChipWhisperer FPGA toolkit to capture power traces and execution metrics. The findings offer fine-grained insights into which LWHFs are best suited for constrained IoT environments.

2024

1. 

   Performance Evaluation of Lightweight Cryptographic Ciphers on ARM Processor for IoT Deployments

   Mohsin Khan, Dag Johansen, and Håvard Dagenborg

   In Proceedings of International Conference on Science of Cyber Security (SciSec), Copenhagen, Denmark, 2024

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   This paper presents a comprehensive evaluation of lightweight cryptographic ciphers (LWCCs) on a single-core ARM processor to assess their applicability in IoT environments. It introduces a new E-Rank metric that integrates throughput, memory footprint, and energy consumption into a unified score to rank cipher efficiency in constrained settings.

2. 

   Performance Evaluation of Lightweight Stream Ciphers for Real-Time Video Feed Encryption on ARM Processor

   Mohsin Khan, Håvard Dagenborg, and Dag Johansen

   Future Internet, 2024

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   This paper presents a comprehensive performance evaluation of prominent Lightweight Stream Ciphers (LWSCs) for encrypting live video feeds on ARM processors. The study develops a benchmarking tool and applies it to assess metrics like encryption frame rate, throughput, processing cycles, memory footprint, ROM usage, and energy consumption, including a unified E-RANK metric for overall software performance.

2023

1. 

   A Multi-pronged Self-adaptive Controller for Analyzing Misconfigurations for Kubernetes Clusters and IoT Edge Devices

   A. Samir, A. Al-Wosabi, Mohsin Khan, and 1 more author

   In Proceedings of European Conference on Service-Oriented and Cloud Computing (ESoCC), Larnaca, Cyprus, 2023

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   Kubernetes default configurations do not always provide optimal security and performance for all clusters and IoT edge devices deployed, making them vulnerable to security breaches and information leakage if misconfigured. Misconfiguration leads to a compromised system that disrupts the workload, allows access to system resources, and degrades the system’s performance. To provide optimal security for deployed clusters and IoT edge devices, the system should detect misconfigurations to secure and optimize its performance. We consider that configurations are hidden, as they are some sort of secret key or access token for an external service. We aim to link the clusters and IoT edge devices’ undesirable observed performance to their hidden configurations by providing a multi-pronged self-adaptive controller to monitor and detect misconfigurations in such settings. Furthermore, the controller implements standardized enforcement policies, demonstrating the controls required for regulatory compliance and providing users with appropriate access to the system resources. The aim of this paper is to introduce the controller mechanism by providing its main processes. Initial evaluations are done to assess the reliability and performance of the controller under different misconfiguration scenarios.

2021

1. 

   Traffic Congestion Reduction and Accident Circumvention System via Incorporation of CAV and VANET

   Mohsin Khan and Bhavna Arora

   International Journal of Advanced Computer Intelligence, 2021

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   This work proposes an intelligent algorithm using MATLAB and Simulink to reduce traffic congestion and accident risk in CAV-VANET systems. It focuses on maintaining safe distance, acknowledged overtaking, and lane shifting using a discrete event simulation framework. The results demonstrate the algorithm’s effectiveness in mitigating phantom traffic jams and improving vehicular safety in connected environments.

2. 

   Traffic Jam Minimization and Accident Avoidance System Using IoT

   Mohsin Khan and Bhavna Arora

   In Procedings of Evolving Technologies for Computing, Communication and Smart World (ETCCS), Noida, India, 2021

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   The paper proposes an IoT-enabled model to reduce traffic jams and accidents by leveraging real-time communication between vehicles. It introduces algorithms and flowcharts for maintaining safe distances, overtaking, and lane shifting, aimed at reducing ’phantom jams’ and enhancing safety in level-2 vehicle automation environments.

2018

1. 

   Smart n Secure Home Using IoT

   Malik Mubashir Hassan, Mohsin Khan, Malik Shoeib, and 2 more authors

   International Journal of Scientific Research in Computer Science, Engineering and Information Technology, India, 2018

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   This paper presents a cloud-connected IoT-based smart home system offering automation, security, and remote control through an Android app and online dashboard. The system incorporates sensors for temperature, humidity, motion, gas detection, and soil moisture, enabling intelligent responses such as lighting control, gas valve shutdown, and automated irrigation.