When cyber security risk for process automation systems is estimated I often see references made to process safety risk. This has several reasons:
- For estimating risk we need likelihood and consequence, the process safety HAZOP and LOPA processes used by plants to estimate process safety risk, identify the consequence of the process scenarios they identify and analyze. These methods also classify the consequence in different categories such as for example finance, process safety, and environment.
- People expect a cyber security risk score that is similar to the process safety risk score, a score expressed as loss based risk. The idea is that the cyber threat potentially increases the process safety risk and they like to know how much that risk is increased. Or more precisely how high is the likelihood that the process scenario could occur as result of a cyber attack.
- The maturity of the process safety risk estimation method is much higher than the maturity of cyber security risk estimation methods in use. Not that strange if you consider that the LOPA method is about 20 years old, and the HAZOP method goes back to the end sixties. When reading publications, or even the standards on cyber security risk (e.g. IEC 62443-3-2) this lack of maturity is easily detected. Often qualitative methods are selected, however these methods have several drawbacks which I discuss later.
This blog will discuss some of these differences and immaturities. I’ve done this in previous blogs mainly by comparing what the standards say and what I’ve experienced and learned over the past 8 years as a cyber risk analysis practitioner for process automation systems doing a lot of cyber risk analysis for the chemical, and oil and gas industries. This discussion requires some theory, I will use some every day examples to explain to make it more digestible.
Let us start with a very important picture to explain process safety risk and its use, but also to show how process safety risk differs from cyber security risk.
There are various ways to express risk, the two most used are risk matrices and FN plots / FN curve. FN curves require a quantitative risk assessment method, such as used in process safety risk analysis by for example LOPA. In an FN curve we can show the risk criteria. The boundaries for what we consider acceptable risk and what we consider unacceptable risk. I took a diagram that I found on the Internet where we have a number of process safety scenarios (shown as dots on the blue line) their likelihood of occurrence ( the vertical ax) and in this case the consequence expressed in fatalities when such a consequence can happen (horizontal ax). The diagram is taken from a Hydrogen plant, these plants belong to the most dangerous plants, this is why we see the relative high number of scenarios with a single or multiple fatalities.
Process safety needs to meet regulations / laws that are associated with their plant license. One such “rule” is that the likelihood of “in fence” fatalities must be limited to 1 every 1000 years (1.00E-3) If we look at the risk tolerance line (RED) in the diagram we see that what is considered tolerable and intolerable is exactly at the point where the line crosses the 1.00E-03 event frequency (likelihood). Another often used limit is the 1.00E-04 frequency for the limit used as acceptable risk, risk not further addressed.
How does process safety determine this likelihood for a specific process scenario? In process safety we have several structured methods for identifying hazards. One of them is the Hazard and Operability study, in short the HAZOP. In a hazop we analyze, for a specific part of the process, if specific conditions can occur. For example we can take the flow through an industrial furnace and analyze if we can have a high flow, no flow, maybe reverse flow. If such a condition is possible we look at the cause of this (the initiating event), perhaps no flow because a pump fails. If we have established the cause (the initiating event) we consider what would be the process consequence. Well possibly the furnace tubing will be damaged, the feed material would leak into the furnace and an explosion might occur. This is what is called the process consequence. This explosion has an impact on safety, one or multiple field operators might be in the neighborhood and killed by the explosion. There will also be a financial impact, and possibly an environmental impact. A hazop is a multi-month process where a team of specialists goes step by step through all units of the installation and considers all possibilities and ways how to mitigate this hazard. This results in a report with all analysis results documented and classified. Hazops are periodically reviewed in a plant to account for possible changes, this we call the validity period of the analysis.
However we don’t have yet a likelihood expressed as an event frequency such as used in the FN curve. This is where the LOPA method comes in. LOPA has tables for all typical initiating events (causes), so the event frequency for the failure of a pump has a specific value (for example 1E-01, once every 10 years). How were these tables created? Primarily based on statistical experience. These tables have been published, but can also differ between companies. It is not so that a poly propylene factory of company A uses by default the same tables as a poly propylene factory of company B. All use the same principles, but small differences can occur.
In the example we have a failing pump with an initiating frequency of once every 10 years and a process consequence that could result in a single fatality. But we also know that our target for single fatalities should be once per 1000 years or better. So we have to reduce this event frequency of 1E-01 with at least a factor 100 to get to once per 1000 years.
This is why we have protection layers, we are looking for one or more protection layers that offer us a factor one hundred extra protection. One of these protection layers can be the safety system, for example a safety controller that detects the no flow condition by measuring the flow and shuts down the furnace to a safe state using a safety valve. How much “credit” can we take for this shutdown action? This depends on the safety integrity level (SIL) of the safety instrumented function (SIF) we designed. This SIF is more than the safety controller where the logic resides, the SIF includes all components necessary to complete the shutdown function, so will include transmitters that measure the flow and safety valves that close any feed lines and bring other parts of the process into a safe condition.
We assign a SIL to the SIF. We typically (SIL 4 does exist) have 3 safety integrity levels: SIL 1, 2, and 3. According to LOPA a SIL 1 SIF gives us a reduction of a factor 10, SIL 2 will reduce the event frequency by a factor 100, and SIL 3 by a factor 1000.
How do we estimate if a SIF meets the requirements for SIL 1, 2, or 3? This requires us to estimate the average probability of failure on demand for the SIF. This estimation makes use of mean time between failure of the various components of the SIF and the test frequency of these components. For this blog I skip this part of the theory, we don’t have to go into that level of detail. High level we estimate what we call the probability of failure on demand for the protection layer (the SIF). In our example we need a SIF with a SIL 2 rating, a protection level relatively easy to create.
In the FN curve you can also see process scenarios that require more than a factor 100, for example a factor 1000 like in a SIL 3 SIF. This requires a lot more, both from the reliability of the safety controller as well as from the other components. Maybe a single transmitter is not reliable enough anymore and we need some 2oo3 (two out of three) configuration to have a reliable measurement. Never the less the principle is the same, we have some initiating event, we have one or more protection layers capable of reducing the event frequency with a specific factor. These protection layers can be a safety system (like in my example), but also some physical device (e.g. pressure relief valve), an alarm from the control system, an operator action, a periodic preventive maintenance activity, etc. LOPA gives each of these protection layers what is called a credit factor, a factor with which we can reduce the event frequency when the protection layer is present.
So far the theory of process safety risk,. One topic I avoided discussing here is the part where we estimate the probability of failure on demand (PFDavg) for a protection layer. But it has some relevance for cyber risk estimates. If we would go into more detail and discuss these formulas to estimate the effectiveness / reliability of the protection layer we see that the formulas for estimating PFDavg we depend on what is called the demand rate. The demand rate is the frequency which we expect the protection layer will needs to act.
The standard (IEC 61511) makes a difference between what is called low-demand rate and high / continuous demand rate. The LOPA process is based upon the low demand-rate formulas, the tables don’t work for high / continuous demand rate. This is an important point to notice when we start a quantitative cyber risk analysis because the demand rate of a cyber protection layer is by default a high / continuous demand rate type of protection layer. This difference impacts the event frequency scale and as such the likelihood scale. So if we were to estimate cyber risk in a similar manner as we estimated process safety risk we end up with different likelihood scales. I will discuss this later.
A few important points to note from above discussion:
- Process safety risk is based on randomly occurring events, events based on things going wrong by accident, such as a pump failure, a leaking seal, an operator error, etc.
- The likelihood scale of process safety risk has a “legal” meaning, plants need to meet these requirements. As such a consolidated process safety and cyber security risk score is not relevant and because of estimation differences not even possible.
- When we estimate cyber security risk, the process safety risk is only one element. With regard to safety impact the identified safety hazards will most likely be as complete as possible, but the financial impact will not be complete because financial impact might also result from scenarios that do not impact process operations but might impact the business. The process safety hazop or LOPA does not generally address cyber security scenarios for systems that have no potential process impact, for example a historian or metering function.
- The IEC 62443 standard tries to introduce the concept of “essential” functions and ties these functions directly to the control and safety functions. However plants and automation functions have many essential tasks not directly related to the control and safety functions, for example various logistic functions. The automation function contains all functions connected to level 0, level 1, level 2, level 3, and demilitarized zone. When we do a risk analysis these systems should be included, not just the control and safety elements. The problem that a ship cannot dock to a jetty also has significant cost to consider in a cyber risk analysis.
- Some people suggest that cyber security provides process safety (or worse the wider safety is even suggested.) This is not true, process safety is provided by the safety systems. The various protection layers in place. Cyber security is an important condition for these functions to do their task, but not more as a condition. The Secret Service protects the president of the US against various threats, but it is the president of the US that governs the country – not the Secret Service by enabling the president to do his task.
Where does cyber security risk differ from process safety risk? Well first of all they have different likelihood scales. Process safety risk is based on random events, cyber security risk is based on intentional events.
Then there is the difference that a process safety protection layer always offers full protection when it is executed, many cyber security protection layers don’t. We can implement antivirus as a first protection layer, application white listing as a 2nd protection layer, they both would do their thing but still the attacker can slip through.
Then there is the difference that a cyber security protection layer is almost continually “challenged”, where in process safety the low demand rate is most often applied, which sets the maximum demand rate to once a year.
If we would look toward cyber security risk in the same way as LOPA does toward process safety risk, we could define various events with their initiating event frequency. For example we could suggest an event such as a malware infection to occur bi-annually. We could assign protection layers against this, for example anti-virus and assign this protection layer a probability of failure on demand (risk reduction factor), so a probability on a false negative or false-positive. If we have an initiating event (the malware infection) with a certain frequency and a protection layer (antivirus) with a specific reduction factor we can estimate a mitigated event frequency (of course taking high demand rate into account).
We can also consider multiple protection layers (e.g. antivirus and application white listing) and arrive at a frequency representing the residual risk after applying the two protection layers. Given various risk factors and parameters to enter the system specific elements and given a program that evaluates the hundreds of attack scenarios, we can arrive at a residual risk for one or hundreds of attack scenarios.
Such methods are followed today, not only by the company I work for but also by several other commercial and non-commercial entities. Is it better or worse than a qualitative risk analysis (the alternative)? I personally believe it is better because the method allows to take multiple protection layers into account. Is it actuarial type of risk, no it is not. But the subjectivity of a qualitative assessment has been removed because of the many factors determining the end result and we have risk now as residual risk based upon taking multiple countermeasures into account.
Still there is another difference between process safety and cyber security risk not accounted for. This is the threat actor in combination with his/her intentions. In process safety we don’t have a threat actor, all is accidental. But in cyber security risk we do have a threat actor and this agent is a factor that influences the initiating event frequency of an attack scenario.
The target attractiveness of facilities differ for different threat actors. A nation state threat actor with all its capabilities is not likely to attack the local chocolate cookie factory, but might show interest in an important pipeline. Different threat actors mean different attack scenarios to include but also influence the initiating event frequency it self. Where non-targeted attacks show a certain randomness of occurrence, a targeted attack doesn’t show this randomness.
We might estimate a likelihood for a certain threat actor to achieve a specific objective for the moment that the attack takes place, but this start moment is not necessarily random. Different factors influence this, so to express cyber risk on a similar event frequency scale as process safety risk is not possible. Cyber security risk is not based on the randomness of the event frequencies. If there is a political friction between Russia and Ukraine, the amount of cyber attacks occurring and skills applied is much bigger than in times without such a conflict.
Therefore cyber security risk and process safety risk cannot be compared. Though the cyber threat certainly increases the process safety risk (both initiating event frequency can be higher and the protection layer might not deliver the level of reliability expected), we can not express this rise in process safety risk level because of the differences discussed above. Process safety risk and cyber security risk are two different things and should be approached differently. Cyber security has this “Secret Service” role, and process safety this “US president” role. We can estimate the cyber security risk that this “Secret Service” role will fail and the US government role is made to do bad things, but that is an entirely different risk than that the US government role will fail. It can fail even when the “Secret Service” role is fully active and doing its job. Therefore cyber security risk has no relation with process safety risk, they are two entirely different risks. The safety protection layers provide process safety (resilience against accidental failure), the cyber security protection layers provide resilience against an intentional and malicious cyber attack.
There is no relationship between my opinions and references to publications in this blog and the views of my employer in whatever capacity. This blog is written based on my personal opinion and knowledge build up over 43 years of work in this industry. Approximately half of the time working in engineering these automation systems, and half of the time implementing their networks and securing them, and conducting cyber security risk assessments for process installations since 2012.
Author: Sinclair Koelemij
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