Security

Find out how Passkey makes logging in easier and safer by introducing passwordless authentication. Learn how this new feature works, the benefits it brings, and why it's a game-changer for your security and convenience. Dive in to see how Grab is making your app experience smoother and more secure.

As the amount of data Grab handles grows, there is an increased need for quick detections for data anomalies (incompleteness or inaccuracy), while keeping it secure. Read this to learn how the Risk Data team utilised Flink and Datadog to enhance data observability within Grab’s services.

Since its launch in 2015, Grab’s Bug Bounty programme has made strides in giving back to the global security community and aiding research. Read this article to find out more about our quarterly campaigns in collaboration with HackerOne and other achievements we’ve had in 2023.

Graphs are powerful data representations that detect relationships and data linkages between devices. This is very helpful in revealing fraudulent or malicious users. Graph modelling is the key to leveraging graph capabilities. Read to find out how the GrabDefence team performs graph modelling to create graphs that can help discover potentially malicious data linkages.

As fraudsters continue to evolve, it becomes more challenging to automatically detect new fraudulent behaviours. At Grab, we are committed to continuously improving our security measures and ensuring our users are protected from fraudsters. Find out how Grab’s Data Science team designed a machine learning model that has the ability to discover new fraud patterns without the need for label supervision.

Grab's data streaming infrastructure runs in the cloud across multiple Availability Zones for high availability and resilience, but this also incurs staggering network traffic cost. In this article, we describe how enabling our Kafka consumers to fetch from the closest replica helped significantly improve the cost efficiency of our design.

Data engineers at Grab work with large sets of data to build and train advanced machine learning models to continuously improve our user experience. However, as with any data-handling company, dealing with users' data may present a potential privacy risk as it contains Personally Identifiable Information (PII). Read this article to find out more about Grab’s mature privacy protective measures and how our data streaming team uses PII tagging and masking on data streaming pipelines to protect our users.

To ensure our consumers continue to be well-protected, we need to ensure our data access measures are compliant with evolving security standards. With more services and resources to manage, it becomes increasingly difficult to maintain a frictionless process. Read to find out how we solve this by migrating from role to attribute-based access control.

Graphs are powerful data representations that detect relationships and data linkages between devices and help reveal fraudulent or malicious users. Learn how GrabDefence built the graph service platform to help discover potentially malicious data linkages.

In addition to ensuring the high performance and availability of our services, security continues to be one of our highest priorities. Read this article to find out how the Coban team enhances security by moving from network-based access control to zero trust with Kafka.

Fraud detection has become increasingly important in a fast growing business as new fraud patterns arise when a business product is introduced. We need a sustainable framework to combat different types of fraud and prevent fraud from happening. Read and find out how we use graph-based models to protect our business from various known and unknown fraud risks.

Telematics is most commonly used to monitor vehicle movements and track driving safety, profiling, fleet optimisation and possible productivity improvements. Read this to find out more about how Grab uses telematics to encourage safer driving across our driver and delivery partner fleet.

As fraud schemes get more complex, we need to stay one step ahead by improving fraud investigation methods. Read to find out more about graph visualisation, why we need it and how it helps with uncovering patterns and relationships.

Facial recognition technology has grown tremendously in recent years due to the rise of deep learning techniques and accelerated digital transformation. Read to find out more about facial recognition technology in Grab and the components that help keep you safe.

Graph theory-based approaches show the concepts underlying the behaviour of massively complex systems and networks. Read to find out how graphs came about, where they can be used and the part they play in graph technology.

As fraudulent entities evolve and get smarter, Grab needs to continuously enhance our defences to protect our consumers. Read to find out how Graph Networks help the Integrity team advance fraud detection at Grab.

As cyberattacks get more advanced, authentication methods like one-time passwords (OTPs) and personal identification numbers (PINs) are no longer enough to protect your users. Find out how biometric authentication can help enhance security.

Read about how the product security team's bug bounty programme has helped keep Grab secure.