Supervisory Control and Data Acquisition (SCADA) System Forensics Based on the Modbus Protocol

Supervisory Control and Data Acquisition (SCADA) has been at the cored of Operational Technology (OT) used in industries and process plants to monitor and control critical processes, especially in the energy sector. In petroleum sub-sector, it has been used in monitoring transportation, storage and loading of petroleum products. It is linked to instruments that collect and monitor parameters such as temperature, pressure and product densities. It gives commands to actuators by the use of the application programs installed on the programmable logic controllers (PLCs). Earlier SCADA systems were isolated from the internet, hence protected by an airgap from attacks taking place on interconnected systems. The recent trend is that SCADA systems are becoming more integrated with other business systems using Internet technologies such as Ethernet and TCP/IP. However, TCP/IP and web technologies which are predominantly used by IT systems have become increasingly vulnerable to cyberattacks that are experienced by IT systems such as malwares and other attacks.  It is important to conduct vulnerability assessment of SCADA systems with a view to thwarting attacks that can exploit such vulnerabilities. Where the vulnerabilities have been exploited, forensic analysis is required so as to know what really happened. This paper reviews SCADA systems configuration, vulnerabilities, and attacks scenarios, then presents a prototype SCADA system and forensic tool that can be used on SCADA. The tool reads into the PLC memory and Wireshark has been to capture network communication between the SCADA system and the PLC

Assessing and augmenting SCADA cyber security: a survey of techniques

SCADA systems monitor and control critical infrastructures of national importance such as power generation and distribution, water supply, transportation networks, and manufacturing facilities. The pervasiveness, miniaturisations and declining costs of internet connectivity have transformed these systems from strictly isolated to highly interconnected networks. The connectivity provides immense benefits such as reliability, scalability and remote connectivity, but at the same time exposes an otherwise isolated and secure system, to global cyber security threats. This inevitable transformation to highly connected systems thus necessitates effective security safeguards to be in place as any compromise or downtime of SCADA systems can have severe economic, safety and security ramifications. One way to ensure vital asset protection is to adopt a viewpoint similar to an attacker to determine weaknesses and loopholes in defences. Such mind sets help to identify and fix potential breaches before their exploitation. This paper surveys tools and techniques to uncover SCADA system vulnerabilities. A comprehensive review of the selected approaches is provided along with their applicability

Autonomic computing architecture for SCADA cyber security

Cognitive computing relates to intelligent computing platforms that are based on the disciplines of artificial intelligence, machine learning, and other innovative technologies. These technologies can be used to design systems that mimic the human brain to learn about their environment and can autonomously predict an impending anomalous situation. IBM first used the term ‘Autonomic Computing’ in 2001 to combat the looming complexity crisis (Ganek and Corbi, 2003). The concept has been inspired by the human biological autonomic system. An autonomic system is self-healing, self-regulating, self-optimising and self-protecting (Ganek and Corbi, 2003). Therefore, the system should be able to protect itself against both malicious attacks and unintended mistakes by the operator

Autonomic computing meets SCADA security

© 2017 IEEE. National assets such as transportation networks, large manufacturing, business and health facilities, power generation, and distribution networks are critical infrastructures. The cyber threats to these infrastructures have increasingly become more sophisticated, extensive and numerous. Cyber security conventional measures have proved useful in the past but increasing sophistication of attacks dictates the need for newer measures. The autonomic computing paradigm mimics the autonomic nervous system and is promising to meet the latest challenges in the cyber threat landscape. This paper provides a brief review of autonomic computing applications for SCADA systems and proposes architecture for cyber security

Forensic Attacks Analysis and the Cyber Security of Safety-Critical Industrial Control Systems

Industrial Control Systems (ICS) and SCADA (Supervisory Control And Data Acquisition) applications monitor and control a wide range of safety-related functions. These include energy generation where failures could have significant, irreversible consequences. They also include the control systems that are used in the manufacture of safety-related products. In this case bugs in an ICS/SCADA system could introduce flaws in the production of components that remain undetected before being incorporated into safety-related applications. Industrial Control Systems, typically, use devices and networks that are very different from conventional IP-based infrastructures. These differences prevent the re-use of existing cyber-security products in ICS/SCADA environments; the architectures, file formats and process structures are very different. This paper supports the forensic analysis of industrial control systems in safety-related applications. In particular, we describe how forensic attack analysis is used to identify weaknesses in devices so that we can both protect components but also determine the information that must be analyzed during the aftermath of a cyber-incident. Simulated attacks detect vulnerabilities; a risk-based approach can then be used to assess the likelihood and impact of any breach. These risk assessments are then used to justify both immediate and longer-term countermeasures

Towards a Layered Architectural View for Security Analysis in SCADA Systems

Supervisory Control and Data Acquisition (SCADA) systems support and control the operation of many critical infrastructures that our society depend on, such as power grids. Since SCADA systems become a target for cyber attacks and the potential impact of a successful attack could lead to disastrous consequences in the physical world, ensuring the security of these systems is of vital importance. A fundamental prerequisite to securing a SCADA system is a clear understanding and a consistent view of its architecture. However, because of the complexity and scale of SCADA systems, this is challenging to acquire. In this paper, we propose a layered architectural view for SCADA systems, which aims at building a common ground among stakeholders and supporting the implementation of security analysis. In order to manage the complexity and scale, we define four interrelated architectural layers, and uses the concept of viewpoints to focus on a subset of the system. We indicate the applicability of our approach in the context of SCADA system security analysis.Comment: 7 pages, 4 figure

Towards Realistic Threat Modeling: Attack Commodification, Irrelevant Vulnerabilities, and Unrealistic Assumptions

Current threat models typically consider all possible ways an attacker can penetrate a system and assign probabilities to each path according to some metric (e.g. time-to-compromise). In this paper we discuss how this view hinders the realness of both technical (e.g. attack graphs) and strategic (e.g. game theory) approaches of current threat modeling, and propose to steer away by looking more carefully at attack characteristics and attacker environment. We use a toy threat model for ICS attacks to show how a realistic view of attack instances can emerge from a simple analysis of attack phases and attacker limitations.Comment: Proceedings of the 2017 Workshop on Automated Decision Making for Active Cyber Defens

Efficient Passive ICS Device Discovery and Identification by MAC Address Correlation

Owing to a growing number of attacks, the assessment of Industrial Control Systems (ICSs) has gained in importance. An integral part of an assessment is the creation of a detailed inventory of all connected devices, enabling vulnerability evaluations. For this purpose, scans of networks are crucial. Active scanning, which generates irregular traffic, is a method to get an overview of connected and active devices. Since such additional traffic may lead to an unexpected behavior of devices, active scanning methods should be avoided in critical infrastructure networks. In such cases, passive network monitoring offers an alternative, which is often used in conjunction with complex deep-packet inspection techniques. There are very few publications on lightweight passive scanning methodologies for industrial networks. In this paper, we propose a lightweight passive network monitoring technique using an efficient Media Access Control (MAC) address-based identification of industrial devices. Based on an incomplete set of known MAC address to device associations, the presented method can guess correct device and vendor information. Proving the feasibility of the method, an implementation is also introduced and evaluated regarding its efficiency. The feasibility of predicting a specific device/vendor combination is demonstrated by having similar devices in the database. In our ICS testbed, we reached a host discovery rate of 100% at an identification rate of more than 66%, outperforming the results of existing tools.Comment: http://dx.doi.org/10.14236/ewic/ICS2018.