How Governments Can Mitigate AI-Powered Cyber Threats

Cybersecurity leaders across all levels of government are growing increasingly alarmed by the rise of cyber attacks fueled by Artificial Intelligence (AI). Cybercriminals are now incorporating machine learning and automation into their strategies, significantly boosting the scale, efficiency and sophistication of their attacks.

According to a recent survey of over 800 IT leaders, a staggering 95% believe that cyber threats have become more advanced than ever before. Some examples include highly personalized, automated phishing campaigns, deceptive deepfake videos and audio and AI-driven malware designed to bypass traditional security measures. 

This post will explore various AI-powered cyber threats and provide strategies for governments to mitigate these risks effectively.

Common AI-powered cyber threats

Malicious actors are increasingly adopting AI for complex cyber attacks. Unlike traditional cyber threats that rely on manual techniques, AI enables attackers to adapt their strategies in real time and exploit vulnerabilities more efficiently. This has forced organizations to rethink their cybersecurity strategies, as traditional methods alone are no longer sufficient to address these advanced, automated attacks​. Below are some of the most common AI-powered cyber threats.

Sophisticated phishing attacks

In the early days of phishing attacks, users were prompted to send money to Nigerian princes, a tactic that quickly became an obvious ploy and a running joke. As phishing attacks grew more sophisticated, messages began to more closely resemble legitimate requests, albeit usually with spelling and grammatical errors and formatting issues.  

AI is now used to compose messages with a more professional writing style and quickly fix grammatical issues. Phishing attacks are also becoming more timely. For example, AI can use real-time information from news outlets and websites to generate a believable sense of urgency.

Deepfakes and misinformation

AI-generated deepfakes are misleading videos or audio recordings of political figures, celebrities or organizational leaders saying or doing things they never actually did. For example, during elections, fake videos of candidates making controversial statements or engaging in inappropriate behavior could be released to damage their reputation or sway voters. These deepfakes can spread quickly through social media, influencing public perception before the misinformation is corrected. 

Another example is a deepfake audio recording impersonating a high-ranking official used to convince a lower-level employee to transfer large sums of money. The voice can sound eerily accurate, using AI to mimic the tone, cadence and style of the leader’s speech. These attacks can be devastating when aimed at government employees, who may be tricked into authorizing the release of sensitive information or conducting financial transactions.

Automated hacking and malware 

Machine learning algorithms are continually improving at identifying and exploiting vulnerabilities faster than traditional hacking methods. AI-enabled ransomware can now identify and encrypt the most critical files first, spreading autonomously across a network and making it difficult for traditional defenses to stop.

In automated credential stuffing attacks, AI-powered bots can automatically test combinations of leaked usernames and passwords at an unprecedented rate. Machine learning algorithms optimize these attacks by learning from past attempts, increasing the likelihood of gaining unauthorized access to accounts.

Another example is AI-powered botnets, which use machine learning algorithms to identify and exploit Internet of Things (IoT) devices that are vulnerable due to weak security protocols. They can also be used to spread misinformation on social media networks.

Fight AI with AI

Fortunately for security officials, AI also powers tools that can detect subtle network anomalies and suspicious activity that might go unnoticed by traditional security tools. AI can also aggregate and analyze threat data from multiple sources, helping to speed up coordination and communication between public- and private-sector partners.

Governments can implement automated response systems powered by AI to quickly neutralize cyber threats before they escalate. These systems use machine learning to assess the severity of an attack, isolate compromised systems and trigger countermeasures like blocking malicious traffic or disabling compromised accounts. AI-powered automation reduces the time between detection and response, which is crucial in mitigating the damage caused by cyber incidents. Government organizations can use the below strategies to counteract AI-powered cyber threats.

Enhancing cybersecurity frameworks

Governments can enhance existing cybersecurity frameworks with AI by leveraging technology to improve threat detection, response and prevention capabilities. For example, AI can analyze network traffic and system logs for anomalies that may indicate a threat. 

Government leaders should implement and enforce mandatory security standards for critical infrastructure and systems, ensuring access is limited to users who need it to perform their jobs. Government contractors and vendors should also be required to meet strict cybersecurity standards.  

Collaboration and information sharing

Public-private partnerships play an important role in sharing intelligence on emerging AI-driven threats. For example, the Cybersecurity and Infrastructure Security Agency (CISA) has several initiatives, such as its Automated Indicator Sharing (AIS) program, which facilitates the exchange of machine-readable cyber threat information between the government and the private sector. CISA also established the Joint Cyber Defense Collaborative (JCDC) to proactively gather, analyze and share actionable cyber risk information to defend against cyber threats.

Incident response plans for AI threats

Fast incident response times are imperative. Fortunately, AI-driven systems can automatically isolate affected systems, block malicious IPs or disable compromised user accounts. Machine learning can also improve response accuracy by learning from past incidents and refining response protocols. 

IT teams at government agencies should invest in training employees to recognize AI cyber threats and implement regular simulations and training exercises to prepare for cyber attacks driven by AI. 

Defend against AI attacks with Keeper Security

Keeper protects government agencies against AI cyber threats with zero-trust cybersecurity, ensuring that access to sensitive information is strictly authenticated, authorized and continuously verified, regardless of location or device. Even if an attacker uses AI to craft convincing phishing attempts, Keeper will not autofill credentials on a spoofed website. Keeper also continuously monitors the dark web for leaked credentials and alerts organizations if compromised credentials are found, allowing for an immediate fix. 

Keeper helps mitigate the risks posed by AI tools that rapidly crack weak passwords by enforcing the use of strong, unique passwords. Employees don’t have to remember these passwords because Keeper stores and autofills them on the correct sites and applications.

With Keeper, IT administrators are provided with the tools they need to monitor and analyze user behavior, which helps detect anomalies or potential AI-driven attacks, such as mass login attempts using stolen or AI-generated credentials. By combining these features with continuous innovation, Keeper helps government agencies stay ahead of evolving AI-powered cyber threats with a zero-trust platform that is FedRAMP and StateRAMP Authorized and available in the AWS GovCloud. 

Book a demo today to see how Keeper Security can help secure and protect your environment.