Detection Engineering UX: 5 Key Principles to Simplify, Personalize, and Amplify AI & Non-AI Alerts
Implementing Explainable AI UX Strategies: A Guide to Frontend Design with LLMs and Machine Learning Algorithms or even good old Rules...
Hello Cyber Builders 🖖,
Closing our series on detection engineering and explainable AI, we zoom today onto an essential aspect of cybersecurity solutions: successful integration and design. Whether designing a product or selecting one as a buyer, it's crucial to consider how it will fit into day-to-day operations, benefiting your team and protecting your infrastructure.
Designing or choosing a cybersecurity product is about more than just its technical capabilities. It's about how those capabilities are presented and interacted with. A tool that excels in detection but fails in user experience is only doing half the job.
The key lies in the user experience, mainly how alerts are managed and presented. It's not just about detecting threats; it's about making those detections meaningful and actionable. Let's explore some core UX principles that should guide the design of these cybersecurity solutions.
In this Post - 5 key principles for UX in cybersecurity
1 - Clarity and Context in Alert Presentation
Users should easily understand the alerts they receive. This means clear language and immediate context. Whether it's an AI-driven alert or a signature match, users should know at a glance what's happening and why.
2 - Actionable Guidance
Once a threat is detected, what next? A well-designed tool doesn't just inform; it guides. Users should receive clear instructions on the steps to take, whether it's further investigation or immediate action.
3 - User Empowerment and Control
Users, whether novices or professionals, should feel in control. They need the ability to set preferences, prioritize alerts, and customize their experience. This empowerment leads to a deeper trust and reliance on the tool.
4 - Chatbot Interaction
The decision to make a chatbot sound human-like or machine-like impacts user experience. A human-like bot can be engaging, but setting expectations is crucial. Users should always know they're interacting with an AI.
5 - Intuitive Interface and Discoverability
A good UX design helps users intuitively discover what actions they can take. Alerts should be more than logs; they should be gateways to action. The interface should guide users naturally to the right features and capabilities.
Clarity and Context in Alert Presentation
In cybersecurity, one of the biggest challenges is dealing with alert overload. Users are often bombarded with numerous alerts, making it difficult to discern critical ones. The key to overcoming this challenge lies in the presentation of these alerts.
Alert Clarity is Key
First and foremost, alerts must be clear. They should avoid technical jargon and be written in plain, easily understandable language. The type of threat, its severity, and the affected system or data should be immediately apparent. This clarity helps users quickly grasp the situation without deciphering complex technical terms.
Beyond clarity, context is essential. An alert should not exist in isolation; it must provide users with enough information to understand why it was triggered. For instance, if an AI algorithm detects unusual login patterns, the alert should include details like the time of the attempt, the location, and how it deviates from standard patterns. This context helps users evaluate the alert's relevance and urgency.
Aggregation: Combating Repetitive Alerts
A common pitfall in alert systems is the repetition of the same alert. This not only contributes to alert fatigue but can also obscure the severity of the situation. To address this, implementing time aggregation is crucial. Instead of multiple alerts for the same issue, a consolidated alert summarizing the repetitive occurrences over a period is far more effective. This approach not only cleans up the interface but also helps track the persistence or escalation of a threat over time.
In addition to time aggregation, scenario-based aggregation plays a pivotal role in effective alert presentation. Individual alerts might seem benign but could indicate a significant threat when viewed collectively. By aggregating alerts based on a potential attack scenario, users can see the broader context of a cybersecurity threat.
For example, isolated alerts for unusual login attempts, unexpected data access, and anomalies in network traffic might not seem alarming. However, aggregating these under a potential data breach scenario paints a clearer picture of a coordinated attack. This aggregation method allows users to identify and respond to complex, multi-faceted threats quickly.
Actionable Guidance: Bridging the Expertise Gap
The initial focus of many products is often on users with a high level of expertise. However, as your product grows and aims to capture a broader market, it becomes imperative to cater to users with varying skills and experience levels. This shift requires a nuanced approach to actionable guidance that bridges the gap between expert users and those newer to the field.
As cybersecurity tools become more accessible, they attract a diverse user base with varying degrees of technical knowledge. This diversity presents a unique challenge: how do you design a tool that is sophisticated enough for experts but also approachable and understandable for beginners?
Guided Experience for Less-Skilled Users
For users with less expertise, guided experiences are essential. This can be achieved through a UX that intuitively leads them through the necessary steps to understand and react to security alerts. Interactive tutorials, contextual help, and simplified modes can make the tool approachable for beginners without compromising the depth required by seasoned users.
Detecting a threat is only the beginning of a cybersecurity response. What is equally, if not more important, is what happens next. Practical cybersecurity tools must provide clear, actionable guidance on the appropriate response. This step is crucial in transforming detection into practical action.
For example, when an alert is raised, it should be accompanied by a set of recommended actions. These instructions need to be specific, detailed, and tailored to the severity and nature of the threat. For instance, in the case of a minor vulnerability, the tool might suggest monitoring the situation or applying a specific patch.
Last but not least, an aspect of user guidance: an alert system should have a feedback mechanism. Users should be able to report false positives or confirm the detection easily. This feedback improves the system's accuracy over time and involves users actively in the security process, increasing their engagement and understanding.
User Empowerment and Control: Scaling Your Cybersecurity Solution
In the world of B2B (Business-to-Business) cybersecurity applications, user empowerment is not just a feature; it's a necessity. Unlike B2C (Business-to-Consumer) applications where simplicity and automation, like photo categorization in Google Photos, are often prioritized, B2B applications must cater to professional users who require a deeper understanding and control over their tools.
Understanding the ‘How’ and ‘Why’ Behind Detections is Material for Detection Engineers
Professional users in a B2B setting need transparency about how detections are made. This includes understanding the criteria for threat detection, the algorithm's logic, and the data sources considered. This level of detail not only aids in building trust in the tool but also empowers users to make informed decisions based on their specific contexts.
Empowerment in a B2B application also means allowing users to act on and modify the tool’s settings and classifications. Users should be able to tailor the tool’s functionality to their unique operational environment. This could include adjusting the sensitivity levels of detection algorithms, customizing alert thresholds, and modifying classification rules to better suit their specific data and risk profiles.
Customization is at the heart of user empowerment. By allowing users to tweak various aspects of the cybersecurity tool, they can ensure that the tool aligns perfectly with their organizational needs and preferences. This level of control is crucial in professional settings where one-size-fits-all solutions are often insufficient.
The Notion HQ UX team provides good resources on these topics.
At Notion, we aim to build AI tools that balance being easy to use and helpful while being accurate and trustworthy. One way to achieve this balance is by ensuring people have the correct input and visibility into AI’s analytical process. We call this keeping humans in the loop.
See their blog post: https://www.notion.so/blog/humans-in-the-loop-creating-intuitive-and-trustworthy-ai-experiences
Integrating AI Chatbots: The “hot topic” in the product roadmap must balance professionalism and AI Interaction.
Integrating a chatbot into a cybersecurity product, especially one based on Large Language Models (LLMs), presents a unique challenge. The question is whether to anthropomorphize the chatbot — to make it sound and interact like a human. While human-like interactions can be engaging, it's crucial to remember that clarity and efficiency often take precedence over a 'cool' factor in a professional cybersecurity context.
In a professional setting, it's generally more appropriate for the chatbot to be tool-like rather than person-like.
Laurent Hausermann - Cyber Builders
The focus should be on functionality and delivering precise and relevant information promptly. Over-emphasizing human-like attributes might lead to unrealistic expectations about the chatbot's capabilities and could potentially detract from its primary function as a professional tool.
The goal should be integrating generative AI capabilities that enhance efficiency and utility.
Take the example of Figma's addition of generative AI to its FigJam collaboration board. It doesn’t mimic human interaction but focuses on understanding user inputs and generating useful outputs, like workflows, based on those inputs. This type of AI integration is professional and practical and significantly speeds up the user experience without trying to be human-like.
Streamlined and Direct Interaction
The UX for the chatbot should enable users to input queries or commands in free-form text, receiving direct, relevant responses. The interaction should be straightforward, avoiding unnecessary complexities that could arise from trying to make the chatbot too human-like.
Intuitive Interface and Discoverability: Facilitating User Engagement and Efficiency
In the realm of cybersecurity tools, the efficiency and effectiveness of users are often determined by how intuitively they can navigate and utilize the software. A well-designed, intuitive interface ensures that users of all skill levels can understand and fully leverage the tool's capabilities.
Discoverability in UX design refers to how easily users can find and use features and functionalities within an application. In cybersecurity tools, this means creating an interface where essential functions are not buried in complex menus or hidden behind obscure commands. Instead, they should be easily accessible, guiding users to the necessary tools and information.
Also, it sounds quite basic to many of you, but the layout and navigation of the tool should be straightforward. Using familiar UI elements and consistent design patterns can help users quickly learn how to use the tool. Clear labels, logical grouping of features, and a well-organized menu structure enhance discoverability, making it easier for users to find the necessary functionality without unnecessary searching or guesswork.
Allowing users to customize their dashboards and create widgets for frequently used functions or critical data can significantly improve discoverability. Users can tailor their workspace to fit their needs and workflows, ensuring that the most relevant information and tools are always at their fingertips.
Incorporating visuals can greatly enhance the comprehension of alerts. Graphs, charts, or color-coded systems can convey the severity and type of threat more effectively than text alone. A well-designed visual can communicate a complex situation in an instant.
Last but not least, while providing detailed information is essential, it's equally important to maintain an easy-to-navigate overview. Users should be able to delve into the details of individual alerts while also being able to step back and view the overall security landscape. Effective UX design should facilitate this transition seamlessly, ensuring users have both the micro and macro perspectives of their cybersecurity status.
Conclusion: Elevating Cybersecurity Through User-Centric Design
As we've explored throughout this series, the success of cybersecurity tools hinges not just on their technical prowess but equally on how they resonate with their users. The five key UX principles — clarity and context in alert presentation, actionable guidance, user empowerment and control, chatbot interaction, and intuitive interface with discoverability — are more than just features; they are foundational elements that define how effectively a tool meets the needs of its users.
In a field as dynamic and critical as cybersecurity, where threats evolve rapidly, the tools we use to combat these threats must not only be robust but also accessible, intuitive, and empowering. By focusing on these UX principles, developers can create cybersecurity solutions that detect and respond to threats and enable and educate their users. This user-centric approach in design ensures that cybersecurity tools are not only efficient and practical but also foster a sense of confidence and mastery among those who rely on them every day.
Ultimately, the goal of all Cyber Builders is crystal-clear: to craft cybersecurity tools that are as user-friendly as they are powerful.
See you next week!
Laurent 💚