Visible to the public Biblio

Filters: Keyword is industrial control systems (ICS)  [Clear All Filters]
2022-06-09
Pyatnitsky, Ilya A., Sokolov, Alexander N..  2021.  Determination of the Optimal Ratio of Normal to Anomalous Points in the Problem of Detecting Anomalies in the Work of Industrial Control Systems. 2021 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT). :0478–0480.

Algorithms for unsupervised anomaly detection have proven their effectiveness and flexibility, however, first it is necessary to calculate with what ratio a certain class begins to be considered anomalous by the autoencoder. For this reason, we propose to conduct a study of the efficiency of autoencoders depending on the ratio of anomalous and non-anomalous classes. The emergence of high-speed networks in electric power systems creates a tight interaction of cyberinfrastructure with the physical infrastructure and makes the power system susceptible to cyber penetration and attacks. To address this problem, this paper proposes an innovative approach to develop a specification-based intrusion detection framework that leverages available information provided by components in a contemporary power system. An autoencoder is used to encode the causal relations among the available information to create patterns with temporal state transitions, which are used as features in the proposed intrusion detection. This allows the proposed method to detect anomalies and cyber attacks.

2021-07-27
Su, K.-M., Liu, I.-H., Li, J.-S..  2020.  The Risk of Industrial Control System Programmable Logic Controller Default Configurations. 2020 International Computer Symposium (ICS). :443—447.
In recent years, many devices in industrial control systems (ICS) equip Ethernet modules for more efficient communication and more fiexible deployment. Many communication protocols of those devices are based on internet protocol, which brings the above benefits but also makes it easier to access by anyone including attackers. In the case of using the factory default configurations, we wiiˆ demonstrate how to easily modify the programmable logic controllers (PLCs) program through the Integrated Development Environment provided by the manufacturer under the security protection of PLC not set properly and discuss the severity of it.
2021-03-30
Pyatnisky, I. A., Sokolov, A. N..  2020.  Assessment of the Applicability of Autoencoders in the Problem of Detecting Anomalies in the Work of Industrial Control Systems.. 2020 Global Smart Industry Conference (GloSIC). :234—239.

Deep learning methods are increasingly becoming solutions to complex problems, including the search for anomalies. While fully-connected and convolutional neural networks have already found their application in classification problems, their applicability to the problem of detecting anomalies is limited. In this regard, it is proposed to use autoencoders, previously used only in problems of reducing the dimension and removing noise, as a method for detecting anomalies in the industrial control system. A new method based on autoencoders is proposed for detecting anomalies in the operation of industrial control systems (ICS). Several neural networks based on auto-encoders with different architectures were trained, and the effectiveness of each of them in the problem of detecting anomalies in the work of process control systems was evaluated. Auto-encoders can detect the most complex and non-linear dependencies in the data, and as a result, can show the best quality for detecting anomalies. In some cases, auto-encoders require fewer machine resources.

2021-03-29
Alabugin, S. K., Sokolov, A. N..  2020.  Applying of Generative Adversarial Networks for Anomaly Detection in Industrial Control Systems. 2020 Global Smart Industry Conference (GloSIC). :199–203.

Modern industrial control systems (ICS) act as victims of cyber attacks more often in last years. These cyber attacks often can not be detected by classical information security methods. Moreover, the consequences of cyber attack's impact can be catastrophic. Since cyber attacks leads to appearance of anomalies in the ICS and technological equipment controlled by it, the task of intrusion detection for ICS can be reformulated as the task of industrial process anomaly detection. This paper considers the applicability of generative adversarial networks (GANs) in the field of industrial processes anomaly detection. Existing approaches for GANs usage in the field of information security (such as anomaly detection in network traffic) were described. It is proposed to use the BiGAN architecture in order to detect anomalies in the industrial processes. The proposed approach has been tested on Secure Water Treatment Dataset (SWaT). The obtained results indicate the prospects of using the examined method in practice.

2019-05-09
Shrestha, Roshan, Mehrpouyan, Hoda, Xu, Dianxiang.  2018.  Model Checking of Security Properties in Industrial Control Systems (ICS). Proceedings of the Eighth ACM Conference on Data and Application Security and Privacy. :164-166.

With the increasing inter-connection of operation technology to the IT network, the security threat to the Industrial Control System (ICS) is increasing daily. Therefore, it is critical to utilize formal verification technique such as model checking to mathematically prove the correctness of security and safety requirements in the controller logic before it is deployed on the field. However, model checking requires considerable effort for regular ICS users and control technician to verify properties. This paper, provides a simpler approach to the model checking of temperature process control system by first starting with the control module design without formal verification. Second, identifying possible vulnerabilities in such design. Third, verifying the safety and security properties with a formal method. 

2018-06-11
Wang, Brandon, Li, Xiaoye, de Aguiar, Leandro P., Menasche, Daniel S., Shafiq, Zubair.  2017.  Characterizing and Modeling Patching Practices of Industrial Control Systems. Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems. :9–9.

Industrial Control Systems (ICS) are widely deployed in mission critical infrastructures such as manufacturing, energy, and transportation. The mission critical nature of ICS devices poses important security challenges for ICS vendors and asset owners. In particular, the patching of ICS devices is usually deferred to scheduled production outages so as to prevent potential operational disruption of critical systems. In this paper, we present the results from our longitudinal measurement and characterization study of ICS patching behavior. Our analysis of more than 100 thousand Internet-exposed ICS devices reveals that fewer than 30% upgrade to newer patched versions within 60 days of a vulnerability disclosure. Based on our measurement and analysis, we further propose a model to forecast the patching behavior of ICS devices.

2017-10-19
Lau, Stephan, Klick, Johannes, Arndt, Stephan, Roth, Volker.  2016.  POSTER: Towards Highly Interactive Honeypots for Industrial Control Systems. Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. :1823–1825.
Honeypots are a common tool to set intrusion alarms and to study attacks against computer systems. In order to be convincing, honeypots attempt to resemble actual systems that are in active use. Recently, researchers have begun to develop honeypots for programmable logic controllers (PLCs). The tools of which we are aware have limited functionality compared to genuine devices. Particularly, they do not support running actual PLC programs. In order to improve upon the interactive capabilities of PLC honeypots we set out to develop a simulator for Siemens S7-300 series PLCs. Our current prototype XPOT supports PLC program compilation and interpretation, the proprietary S7comm protocol and SNMP. While the supported feature set is not yet comprehensive, it is possible to program it using standard IDEs such as Siemens' TIA portal. Additionally, we emulate the characteristics of the network stack of our reference PLC in order to resist OS fingerprinting attempts using tools such as Nmap. Initial experiments with students whom we trained in PLC programming indicate that XPOT may resist cursory inspection but still fails against knowledgeable and suspicious adversaries. We conclude that high-interactive PLC honeypots need to support a fairly complete feature set of the genuine, simulated PLC.