1. Cybersecurity’s changing landscape
Attacks on computing systems and infrastructure continue to grow in complexity, speed, frequency, and scale. We have seen new attack techniques and the exploitation of new attack surfaces aimed at disrupting critical infrastructure and accessing confidential data. In 2021 alone, the Microsoft 365 Defender suite, supported by AI techniques, blocked more than 9.6 billion malware threats, 35.7 billion phishing and malicious emails, and 25.6 billion attempts to hijack customer accounts targeting both enterprise and consumer devices., Multiple independent reports have characterized the nature and status of different forms of cyberattack. As detailed in Microsoft’s recent Digital Defense Report, cyber criminals and nation-state actors continue to adapt their techniques to exploit new vulnerabilities and counter cyber defenses.
2. Advancements in Artificial Intelligence
Artificial intelligence is an area of computer science focused on developing principles and mechanisms to solve tasks that are typically associated with human cognition, such as perception, reasoning, language, and learning. Numerous milestones have been achieved in AI theory and applications over the 67 years since the phrase “artificial intelligence” was first used in a funding proposal that laid out a surprisingly modern vision for the field.
Particularly stunning progress has been made over the last decade, spanning advances in machine vision (e.g., object recognition), natural language understanding, speech recognition, automated diagnosis, reasoning, robotics, and machine learning—procedures for learning from data. Many impressive gains across subdisciplines of AI are attributed to a machine learning methodology named deep neural networks (DNNs). DNNs have delivered unprecedented accuracy when fueled by large amounts of data and computational resources.
3. Advancing Cybersecurity with AI
The value of harnessing AI in cybersecurity applications is becoming increasingly clear. Amongst many capabilities, AI technologies can provide automated interpretation of signals generated during attacks, effective threat incident prioritization, and adaptive responses to address the speed and scale of adversarial actions. The methods show great promise for swiftly analyzing and correlating patterns across billions of data points to track down a wide variety of cyber threats of the order of seconds. Additionally, AI can continually learn and adapt to new attack patterns—drawing insights from past observations to detect similar attacks that occur in the future.
4. AI-powered cyberattacks
While AI is improving our ability to detect cybersecurity threats, organizations and consumers will face new challenges as cybersecurity attacks increase in sophistication. To date, adversaries have commonly employed software tools in a manual manner to reach their objectives. They have been successful in exfiltrating sensitive data about American citizens, interfering with elections, and distributing propaganda on social media without the sophisticated use of AI technologies. ,, While there is scarce information to date on the active use of AI in cyberattacks, it is widely accepted that AI technologies can be used to scale cyberattacks via various forms of probing and automation. Multiple research and gaming efforts within cybersecurity communities have demonstrated the power using AI methods to attack computing systems. This area of work is referred to as offensive AI.,