The Psychology of Information Security is now an audiobook too!

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Thanks to my publisher, my book is now available in the audio format. It’s been narrated by Peter Silverleaf, who’s done a great job as always.

If you would rather listen to an audio while driving, exercising or commuting, this version is for you. The book has intentionally been kept to the point which means you can finish the audio in slightly over two hours. The fact that it costs the equivalent of two cups of coffee is an added benefit.

You can get it for free on Audible as part of their introductory offer (you can listen to the sample there too), through Apple iTunes or download it in the MP3 format on my publisher’s website.

I know I’m slightly biased here, but I highly recommend it!

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Cyber Security: Law and Guidance

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I’m proud to be one of the contributors to the newly published  Cyber Security: Law and Guidance book.

Although the primary focus of this book is on the cyber security laws and data protection, no discussion is complete without mentioning who all these measures aim to protect: the people.

I draw on my research and practical experience to present a case for the new approach to cyber security and data protection placing people in its core.

Check it out!


Behavioural science in cyber security

Why your staff ignore security policies and what to do about it.               

Dale Carnegie’s 1936 bestselling self-help book How To Win Friends And Influence People is one of those titles that sits unloved and unread on most people’s bookshelves. But dust off its cover and crack open its spine, and you’ll find lessons and anecdotes that are relevant to the challenges associated with shaping people’s behaviour when it comes to cyber security.

In one chapter, Carnegie tells the story of George B. Johnson, from Oklahoma, who worked for a local engineering company. Johnson’s role required him to ensure that other employees abide by the organisation’s health and safety policies. Among other things, he was responsible for making sure other employees wore their hard hats when working on the factory floor.

His strategy was as follows: if he spotted someone not following the company’s policy, he would approach them, admonish them, quote the regulation at them, and insist on compliance. And it worked — albeit briefly. The employee would put on their hard hat, and as soon as Johnson left the room, they would just as quickly remove it.  So he tried something different: empathy. Rather than addressing them from a position of authority, Johnson spoke to his colleagues almost as though he was their friend, and expressed a genuine interest in their comfort. He wanted to know if the hats were uncomfortable to wear, and that’s why they didn’t wear them when on the job.

Instead of simply reciting the rules as chapter-and-verse, he merely mentioned it was in the best interest of the employee to wear their helmets, because they were designed to prevent workplace injuries.

This shift in approach bore fruit, and workers felt more inclined to comply with the rules. Moreover, Johnson observed that employees were less resentful of management.

The parallels between cyber security and George B. Johnson’s battle to ensure health-and-safety compliance are immediately obvious. Our jobs require us to adequately address the security risks that threaten the organisations we work for. To be successful at this, it’s important to ensure that everyone appreciates the value of security — not just engineers, developers, security specialists, and other related roles.

This isn’t easy. On one hand, failing to implement security controls can result in an organisation facing significant losses. However, badly-implemented security mechanisms can be worse: either by obstructing employee productivity or by fostering a culture where security is resented.

To ensure widespread adoption of secure behaviour, security policy and control implementations not only have to accommodate the needs of those that use them, but they also must be economically attractive to the organisation. To realise this, there are three factors we need to consider: motivation, design, and culture.

Read the rest of this entry »


Artificial intelligence and cyber security: attacking and defending

Cyber security is a manpower constrained market – therefore the opportunities for AI automation are vast.  Frequently, AI is used to make certain defensive aspects of cyber security more wide reaching and effective: combating spam and detecting malware are prime examples.  On the opposite side there are many incentives to use AI when attempting to attack vulnerable systems belonging to others.  These incentives could include the speed of attack, low costs and difficulties attracting skilled staff in an already constrained environment.

Current research in the public domain is limited to white hat hackers employing machine learning to identify vulnerabilities and suggest fixes.  At the speed AI is developing, however, it won’t be long before we see attackers using these capabilities on mass scale, if they don’t already.

How do we know for sure? The fact is, it is quite hard to attribute a botnet or a phishing campaign to AI rather than a human. Industry practitioners, however, believe that we will see an AI-powered cyber-attack within a year: 62% of surveyed Black Hat conference participants seem to be convinced in such a possibility.

Many believe that AI is already being deployed for malicious purposes by highly motivated and sophisticated attackers. It’s not at all surprising given the fact that AI systems make an adversary’s job much easier. Why? Resource efficiency point aside, they introduce psychological distance between an attacker and their victim. Indeed, many offensive techniques traditionally involved engaging with others and being present, which in turn limited attacker’s anonymity. AI increases the anonymity and distance. Autonomous weapons is the case in point; attackers are no longer required to pull the trigger and observe the impact of their actions.

It doesn’t have to be about human life either. Let’s explore some of the less severe applications of AI for malicious purposes: cybercrime.

Social engineering remains one of the most common attack vectors. How often is malware introduced in systems when someone just clicks on an innocent-looking link?

The fact is, in order to entice the victim to click on that link, quite a bit of effort is required. Historically it’s been labour-intensive to craft a believable phishing email. Days and sometimes weeks of research and the right opportunity were required to successfully carry out such an attack. Things are changing with the advent of AI in cyber.

Analysing large data sets helps attackers prioritise their victims based on online behaviour and estimated wealth. Predictive models can go further and determine the willingness to pay the ransom based on historical data and even adjust the size of pay-out to maximise the chances and therefore revenue for cyber criminals.

Imagine all the data available in the public domain as well as previously leaked secrets through various data breaches are now combined for the ultimate victim profiling in a matter of seconds with no human effort.

When the victim is selected, AI can be used to create and tailor emails and sites that would be most likely clicked on based on crunched data. Trust is built by engaging people in longer dialogues over extensive periods of time on social media which require no human effort – chatbots are now capable of maintaining such interaction and even impersonate the real contacts by mimicking their writing style.

Machine learning used for victim identification and reconnaissance greatly reduces attacker’s resource investments. Indeed, there is even no need to speak the same language anymore! This inevitably leads to an increase in scale and frequency of highly targeted spear phishing attacks.

Sophistication of such attacks can also go up. Exceeding human capabilities of deception, AI can mimic voice thanks to the rapid development in speech synthesis. These systems can create realistic voice recordings based on existing data and elevate social engineering to the next level through impersonation. This, combined with other techniques discussed above, paints a rather grim picture.

So what do we do?

Let’s outline some potential defence strategies that we should be thinking about already.

Firstly and rather obviously, increasing the use of AI for cyber defence is not such a bad option. A combination of supervised and unsupervised learning approaches is already being employed to predict new threats and malware based on existing patterns.

Behaviour analytics is another avenue to explore. Machine learning techniques can be used to monitor system and human activity to detect potential malicious deviations.

Importantly though, when using AI for defence, we should assume that attackers anticipate it. We must also keep track of AI development and its application in cyber to be able to credibly predict malicious applications.

In order to achieve this, a collaboration between industry practitioners, academic researchers and policymakers is essential. Legislators must account for potential use of AI and refresh some of the definitions of ‘hacking’. Researchers should carefully consider malicious application of their work. Patching and vulnerability management programs should be given due attention in the corporate world.

Finally, awareness should be raised among users on preventing social engineering attacks, discouraging password re-use and advocating for two-factor-authentication where possible.

References

The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation 2018

Cummings, M. L. 2004. “Creating Moral Buffers in Weapon Control Interface Design.” IEEE Technology and Society Magazine (Fall 2004), 29–30.

Seymour, J. and Tully, P. 2016. “Weaponizing data science for social engineering: Automated E2E spear phishing on Twitter,” Black Hat conference

Allen, G. and Chan, T. 2017. “Artificial Intelligence and National Security,” Harvard Kennedy School Belfer Center for Science and International Affairs,

Yampolskiy, R. 2017. “AI Is the Future of Cybersecurity, for Better and for Worse,” Harvard Business Review, May 8, 2017.


Of people and security: To build a working security culture, focus first on empathy and communication

A security department may sometimes be referred to by executives as the ‘Business Prevention Department’. Cyber security professionals, eager to minimise potential risks, can put controls in place that may stifle productivity and innovation.

Cyber security professionals are often too aware of what the business shouldn’t do and forget to mention what it should be doing instead. Ok, USB ports are now blocked, but have we provided people with an alternative to share files securely? Yes, we might’ve mitigated the risk of introducing malware through a flash drive, but have we considered a wider impact on the ability of employees to perform their core business activities, and, in turn, on overall profitability of the company.

Instead of saying ‘No’ to everything, let’s try to understand the business context of what we are trying to protect and why. Because that’s what actually matters and is absolutely key when designing security solutions that work.

People often think that security is the opposite of usability. In reality, the reverse is true. Design and security can coexist by defining constructive and destructive behaviours: what people should and shouldn’t do. Effective design, therefore, streamlines constructive behaviours while making risky ones harder to accomplish.

To do this effectively, security has to be a vocal influence in the design process, and not an afterthought. But it can only regain this influence if the value to the people and business is first demonstrated.

Wondering why your security policies don’t work? Ask your staff!  Empathy, communication and collaboration are vital to build a culture of security. Security processionals need to shift their role from that of policeman enforcing policy from the top-down through sanctions to someone who is empathetic to the business needs and takes time to understand them.

Security mechanisms should be shaped around the day-to-day working lives of employees, and not the other way around. The best way to do this is to engage with employees and to factor in their unique experiences and insights into the design process. The aim should be to correct the misconceptions, misunderstandings and faulty decision-making processes that result in non-compliant behaviour.

Changing culture is not easy and will take time; but it is possible. Check out my book to find out more about developing an effective business-oriented security programme and improving security culture in your organisation.


DevOps and Operational Technology: a security perspective

I have worked in the Operational Technology (OT) environment for years, predominantly in major Oil and Gas companies. And yes, we all know that this space can move quite slowly! Companies traditionally employ a waterfall model while managing projects with rigid stage gates, extensive planning and design phases followed by lengthy implementation or development.

It’s historically been difficult to adopt more agile approaches in such an environment for various reasons. For example, I’ve developed architecture blueprints with a view to refresh industrial control assets for a gas and electricity distribution network provider in the UK on a timeline of 7 years. It felt very much like a construction project to me.  Which is quite different from the software development culture that typically is all about experimenting and failing fast. I’m not sure about you, but I would not like our power grid to fail fast in the name of agility. The difference in culture is justified: we need to prioritise safety and rigour when it comes to industrial control systems, as the impact of a potential mistake can cost more than a few days’ worth of development effort – it can be human life.

The stakes are not as high when we talk about software development.  I’ve spent the past several months in one of the biggest dot-coms in Europe and it was interesting to compare and contrast their agile approach to the more traditional OT space I’ve spent most of my career in. These two worlds can’t be more different.

I arrived to a surprising conclusion though: they are both slow when it comes to security. But  for different reasons.

Agile, and Scrum in particular, is great on paper but it’s quite challenging when it comes to security.

Agile works well when small teams are focused on developing products but I found it quite hard to introduce security culture in such an environment. Security often is just not a priority for them.

Teams mostly focus on what they perceive as a business priority. It is a standard practice there to define OKRs – Objectives and Key Results. The teams are then measured on how well they achieved those. So say if they’ve met 70% of their OKRs, they had a good quarter. Guess what – security always ends up in the other bottom 30% and security-related backlog items get de-prioritised.

DevOps works well for product improvement, but it can be quite bad for security. For instance, when a new API or a new security process is introduced, it has to touch a lot of teams which can be a stakeholder management nightmare in such an environment. A security product has to be shoe horned across multiple DevOps teams, where every team has its own set of OKRs, resulting in natural resistance to collaborate.

In a way, both OT and DevOps move slowly when it comes to security. But what do you do about it?

The answer might lie in setting the tone from the top and making sure that everyone is responsible for security, which I’ve discussed in a series of articles on security culture on this blog and in my book The Psychology of Information Security.

How about running your security team like a DevOps team? When it comes to Agile, minimising the friction for developers is the name of the game: incorporate your security checks in the deployment process, do some automated vulnerability scans, implement continuous control monitoring, describe your security controls in the way developers understand (e.g. user stories) and so on.

Most importantly, gather and analyse data to improve. Where is security failing? Where is it clashing with the business process? What does the business actually need here? Is security helping or impeding? Answering these questions is the first step to understanding where security can add value to the business regardless of the environment: Agile or OT.


Sharing views on security culture

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I’ve been invited to talk about human aspects of security at the CyberSecurity Talks & Networking event.  The venue and the format allowed the audience to participate and ask questions and we had insightful discussions at the end of my talk. It’s always interesting to hear what challenges people face in various organisations and how a few simple improvements can change the security culture for the better.