Expleo, a global engineering, technology and consulting service provider, has recently launched a guide called ‘AI in Cybersecurity: Between Shield and Shadow’ which looks at rapidly emerging AI-based technology and how it can be leveraged for enhanced cybersecurity protection.
Go deeper with GlobalData
We spoke to Steve McEvoy, VP of automotive, Expleo, to learn more about the new guide and how AI can help with cybersecurity threats.
Just Auto (JA): Can you describe your recently launched guide ‘the AI in Cybersecurity: Between Shield and Shadow’, and what it covers?
Steve McEvoy (SM): The launch of Expleo’s guide AI in Cybersecurity: Between Shield and Shadow is particularly timely, as the convergence of AI and connected technologies presents both opportunities and unprecedented challenges.
In the automotive sector, AI is transforming how we design and protect vehicles, from enabling smarter, more adaptive driving experiences to safeguarding critical vehicle systems. The guide explores the impact of AI across key industries including automotive, aerospace, banking and energy, each facing unique cyber threats.
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By GlobalDataOne of the standout insights for automotive is how AI can actively prevent cyber-attacks by analysing vast data sets in real-time, detecting, predicting and responding to potential threats far more quickly than traditional methods. For instance, the report highlights AI’s role in protecting vehicle-to-everything (V2X) systems, which are vital for autonomous driving and smart city integration. These connected systems are vulnerable to signal manipulation, and AI’s ability to identify and neutralise threats in real-time is a gamechanger.
This guide doesn’t just focus on AI benefits; it also underscores the risks of AI being exploited by bad actors.
This guide doesn’t just focus on AI benefits; it also underscores the risks of AI being exploited by bad actors. We need to be just as vigilant in leveraging AI to protect ourselves as we are in developing it for good. The guide also makes it clear that automakers must adopt a proactive mindset, embedding cybersecurity into vehicle design from the earliest stages.
Has the automotive space seen an increase in cyber threats?
There has been a significant rise in cyber threats within the automotive sector. As modern vehicles evolve into ‘supercomputers on wheels’, with some containing over 100 million lines of code—four times more than an F-35 jet—this has created a much larger surface for attacks.
Automotive systems such as V2X communication, over-the-air software updates and autonomous driving functions have made vehicles more susceptible to cyber-attacks. Core vehicle controls like braking, steering and engine management are now deeply interconnected, and any vulnerability in one system could potentially compromise the entire vehicle.
An example of this is the manipulation of over-the-air updates, where hackers could alter the data being sent to a vehicle’s software, potentially disrupting vital safety features. More complex attacks could even target critical systems, such as the electronic control units (ECUs), leading to severe safety risks.
As AI continues to integrate into vehicle systems, it’s vital to recognise that while it offers real-time monitoring and threat detection, it also requires equally sophisticated defences to counter the increasingly advanced cyber threats automakers now face.
How is AI transforming automotive cybersecurity by detecting and preventing threats in real-time?
AI is fundamentally reshaping how we approach automotive cybersecurity by enabling real-time threat detection and prevention. One of the major benefits of AI is its ability to process and analyse vast quantities of data from various systems within the vehicle and its surrounding environment, spotting patterns and anomalies that would be difficult or impossible for human operators to identify.
AI is fundamentally reshaping how we approach automotive cybersecurity by enabling real-time threat detection and prevention.
For example, AI algorithms can continuously monitor V2X communication systems, which allow vehicles to communicate with each other and the infrastructure around them. This technology is essential for autonomous driving, but it also opens up new vulnerabilities, such as signal interference or hacking attempts. With AI, these systems can detect unusual communication patterns or abnormal sensor data that may indicate a cyber-attack. AI can flag such issues in real-time, preventing an attacker from gaining access to sensitive systems or altering how a vehicle behaves on the road.
Another example is AI’s ability to protect against the manipulation of camera systems and LiDAR sensors, which are crucial for autonomous navigation. By continuously checking for discrepancies between the expected environment and what the vehicle’s sensors are reporting, AI can catch attempts to feed false data into the system before it causes harm. These real-time responses are a significant improvement over traditional cybersecurity measures, which often rely on reactive defences. AI’s predictive capabilities also enable early intervention, minimising damage before an attack fully unfolds.
What vulnerabilities in connected vehicles can AI help to identify?
AI is a powerful tool for identifying and addressing vulnerabilities in connected vehicles. One of the most significant threats comes from the ability of cyber attackers to exploit wireless communication channels used by connected vehicles, such as those facilitating over-the-air updates or vehicle-to-infrastructure communication.
For instance, AI can monitor for anomalies in wireless signals or data transmissions, which may indicate that a bad actor is trying to intercept or manipulate the communication between a vehicle and a remote server. This might include tampering with a vehicle’s navigation system to send it off course or disabling critical safety systems.
An example of AI’s role in preventing these attacks can be seen in V2X systems, where the manipulation of traffic signals or road signage could lead to accidents. AI can detect the inconsistent data being fed to the vehicle, recognise it as a potential attack and override the malicious inputs to keep the vehicle and its occupants safe.
Another area where AI excels is in securing the vehicle’s internal network. Many modern vehicles are highly connected internally, with systems like braking, engine control and infotainment linked via a network. A breach in one of these systems can quickly propagate across the vehicle. AI can help by continuously monitoring these internal networks for unusual activity, such as a sudden influx of data or abnormal command requests that may indicate a hacker is trying to take control. The ability to spot these warning signs early is crucial for ensuring the safety of connected vehicles.
How important is collaboration across the industry to tackle these threats?
Collaboration is absolutely essential if we are to tackle the evolving cybersecurity threats in the automotive industry. Regulations like UNECE R155 are already pushing automakers and suppliers to adopt common standards but the future lies in more open-source collaboration.
Sharing threat intelligence, cybersecurity best practices and tools between OEMs, tier-one suppliers and even regulatory bodies is crucial. By co-creating solutions and setting industry-wide standards, we can collectively defuse the challenges that AI brings, ensuring that cybersecurity evolves in step with technological advancements.
We are already seeing encouraging efforts from bodies such as the US National Institute of Standards and Technology (NIST), which has established communities of interest to address automotive cybersecurity. However, further collaboration will be key to addressing the complexities and ensuring the industry stays one step ahead of emerging threats.
