TY - GEN A1 - Alsabbagh, Wael A1 - Kim, Chaerin A1 - Langendörfer, Peter T1 - No Attacks Are Available: Securing the OpenPLC and Related Systems T2 - 8th GI/ACM Workshop on Industrial Automation and Control Systems (IACS WS 2023), 2085 (2023) N2 - The use of Programmable Logic Controllers (PLCs) expands in industrial domains, which makes ensuring the security of Industrial Control Systems (ICSs) become paramount. The OpenPLC project, the first open-source initiative, provides flexible and cost-effective PLC solutions to build up affordable test-beds, as well as conduct experiments and academic researches. This project has wildly grown in the last few years, thus it is essential to address the most emerging security challenges it encounters. This paper introduces a new OpenPLC architecture, called OpenPLC Aqua, provided with a set of security solutions designed specifically to overcome the vulnerabilities that the current OpenPLC versions are prone to. The new OpenPLC architecture includes four security features: 1) user credentials encryption, securing the Webserver, Whitelisting and secure SSL/TLS communication channel. The OpenPLC Aqua software was tested against several attack scenarios, that were feasible against the old OpenPLC versions. Our experimental results showed our enhanced OpenPLC software is secure and resistant against several attack scenarios e.g., authentication, injection, Man-in-the-Middle and replay attacks. The OpenPLC Aqua is publicly available and a proof of concept demo is also published with this paper. KW - OpenPLC KW - Seucrity Solutions KW - Industrial Control Systems KW - Mitigation Solutions Y1 - 2023 U6 - https://doi.org/10.13140/RG.2.2.24570.47043 ER - TY - GEN A1 - Alsabbagh, Wael A1 - Kim, Chaerin A1 - Langendörfer, Peter T1 - Good Night, and Good Luck: A Control Logic Injection Attack on OpenPLC T2 - Proc. 49th Annual Conference of the IEEE Industrial Electronics Society (IECON 2023), (2023) Y1 - 2023 U6 - https://doi.org/10.13140/RG.2.2.32913.20321 ER - TY - GEN A1 - Alsabbagh, Wael A1 - Kim, Chaerin A1 - Patil, Nitin Sanjay A1 - Langendörfer, Peter T1 - Hacking the backbone : shell reverse attacks on IIoT systems T2 - 21st International Conference on Embedded Wireless Systems and Networks (EWSN) N2 - As Industrial Internet of Things (IIoT) systems expand , they face growing risks from complex cyber threats, including reverse shell attacks. These attacks exploit IIoT vulnerabilities, allowing unauthorized remote access and endangering industrial operations. This paper explores reverse shell attacks, where adversaries trick operators into unwittingly installing malware on IIoT devices. This malware then establishes hidden connections to the attacker's server, bypassing traditional firewalls. Exploiting command injection vulnerabilities on IIoT servers facilitates the deployment of reverse shell scripts, granting attackers persistent and covert system access. Our research focuses on IIoT device authentication, identifying weak credentials and using brute force attacks for initial access. We also demonstrate deploying Python-based reverse shell payloads via the SFTP protocol, creating lasting connections to the attacker's server. Through experiments with the Fischertechnik Learning Factory 4.0, we show how reverse shell payloads disrupt operations, enabling unauthorized commands and data theft. To counter these threats, we advocate for robust security measures like network segmentation, rigorous patch management, and advanced intrusion detection systems. All our attack codes and a proof-of-concept are publicly accessible. Y1 - 2024 U6 - https://doi.org/10.13140/RG.2.2.23097.79207 SP - 1 EP - 7 ER - TY - GEN A1 - Alsabbagh, Wael A1 - Kim, Chaerin A1 - Langendörfer, Peter T1 - Silent sabotage : a stealthy control logic injection in IIoT systems T2 - 5th Silicon Valley Cybersecurity Conference (SVCC 2024) Y1 - 2024 U6 - https://doi.org/10.1109/SVCC61185.2024.10637363 SP - 1 EP - 8 PB - IEEE CY - New York ER - TY - GEN A1 - Alsabbagh, Wael A1 - Amogbonjaye, Samuel A1 - Kim, Chaerin A1 - Langendörfer, Peter T1 - Pirates of the MQTT : raiding IIoT systems with a rogue client T2 - 2024 8th Cyber Security in Networking Conference (CSNet) N2 - The integration of MQTT (Message Queuing Telemetry Transport) in Industrial Internet of Things (IIoT) systems enhances operational efficiency but introduces significant security vulnerabilities, particularly through rogue MQTT clients. These clients exploit MQTT weaknesses to disrupt industrial processes and compromise data integrity. This paper examines the impact of rogue MQTT client attacks, demonstrated through a detailed case study using the Fischertechnik Lernfabrik 4.0. We highlight how attackers can exploit MQTT's inherent vulnerabilities, including anonymous connections and message retention, to inject false data and interfere with operations. To address these risks, we propose several mitigation strategies: implementing fine-grained authorization for topic access control, enhancing replay attack protection with Message Authentication Code (MAC), employing mutual TLS (mTLS) for secure client authentication, and incorporating real-time client activity monitoring and anomaly detection. These measures aim to bolster IIoT system security, mitigate potential disruptions, and maintain operational integrity. Our findings and recommendations contribute to advancing security practices in MQTT-based IIoT environments. All attack codes and a proof-of-concept are ublicly available. KW - Rogue Client KW - MQTT Protocol KW - Cyberattacks KW - Cybersecurity Y1 - 2024 U6 - https://doi.org/10.1109/CSNet64211.2024.10851733 SP - 248 EP - 253 PB - IEEE CY - Piscataway, NJ ER - TY - GEN A1 - Alsabbagh, Wael A1 - Kim, Chaerin A1 - Langendörfer, Peter T1 - A payload of lies : false data injection attacks on MQTT-based IIoT systems T2 - IECON 2024 - 50th Annual Conference of the IEEE Industrial Electronics Society : proceedings N2 - In the ever-evolving landscape of Industrial Internet of Things (IIoT), security emerges as a critical concern. This paper delves into the realm of False Data Injection Attacks (FDIAs) within MQTT-based IIoT systems, specifically targeting the publisher-subscriber model. Our exploration unveils two distinct attack scenarios that exploit the vulnerabilities inherent in the communication fabric. In the first scenario, we demonstrate the potential chaos wrought by sending false data to subscribers, manipulating their perception and inducing actions that align with the attacker’s whims. The second scenario ventures into the heart of the publisher, where the attacker injects false data – deceptive status updates from other publishers e.g., Programmable Logic Controllers (PLCs). The repercussions ripple through the entire industrial process, impacting operations based on fraudulent information. This showcases the cascading effects of FDIAs, illustrating the profound threat they pose to the reliability and integrity of IIoT systems. For real-world attack scenarios, Our attacks were conducted on a small MQTT-based IIoT system, using the Fischertechnik Lernfabrik 4.0 9V factory. Finally, we proposes mitigation solutions to safeguard IIoT systems from the far-reaching consequences of false data manipulation. Our attack codes as well as a proof-of-concept are publicly available for further research. KW - FDIAs KW - IIoT KW - IoT KW - MQTT Protocol Y1 - 2024 SN - 978-1-6654-6454-3 U6 - https://doi.org/10.1109/IECON55916.2024.10905487 SP - 1 EP - 8 PB - IEEE CY - Piscataway, NJ ER - TY - GEN A1 - Alsabbagh, Wael A1 - Sayegh, Bahij A1 - Kim, Chaerin A1 - Langendorfer, Peter T1 - FeatNet-IDS : anomaly detection based-features for industrial internet of things systems T2 - 2025 Silicon Valley Cybersecurity Conference (SVCC) N2 - Anomaly detection is critical for securing Industrial Internet of Things (IIoT) systems against evolving cyber threats. This paper introduces FeatNet-IDS, an enhanced Intrusion Detection System (IDS) for MQTT-based IIoT environments. FeatNet- IDS combines advanced feature selection and machine learning techniques to improve anomaly detection accuracy, efficiency, and interpretability. Evaluated on a domain-specific dataset of MQTT-related attacks, including control logic injection, the framework achieves 92.3% accuracy, 91.5% F1-score, and 96.8% ROC AUC, with a low false alarm rate of 2.73%. By emphasizing feature stability and importance, FeatNet-IDS outperforms or matches state-of-the-art methods, demonstrating robustness and transparency. Practical deployment implications are discussed, with future work addressing dataset expansion, hyperparameter tuning, and advanced ensemble approaches. The dataset and framework codes are publicly available to support further research. KW - IIoT KW - MQTT Protocol KW - Cyberattacks KW - Cybersecurity KW - Anomaly Detection Y1 - 2025 SN - 979-8-3315-3429-5 U6 - https://doi.org/10.1109/SVCC65277.2025.11133650 SP - 1 EP - 8 PB - IEEE CY - Piscataway, NJ ER -