By harnessing the power of AI and ML, businesses can stay one step ahead of cybercriminals
Today’s businesses increasingly rely on cloud environments to scale, maintain flexibility, and enhance their operations and productivity. However, this surge in cloud adoption comes with increased cybersecurity threats. Cloud attacks pose severe data security, privacy, and operational continuity risks. The growth of “cloud-conscious” adversaries – groups that abuse cloud-specific features to achieve their goals – represent a significant risk to any organisations operating in the cloud.
According to the CrowdStrike 2023 Threat Hunting report, cloud exploitation grew by 95% from 2022 and cases involving adversaries targeting cloud environments have nearly tripled, increasing 288% year-over-year. This growth indicates a larger trend of eCrime and nation-state actors adopting knowledge and tradecraft to increasingly exploit cloud environments. Adversaries are landing on the endpoint and pivoting to the cloud, making it the new battleground for stopping breaches.
In this scenario where the complexity of cloud infrastructures is already at risk of growing cyber threats, innovative solutions become imperative for safeguarding sensitive data, and deploying advanced security measures to protect businesses against potential breaches is a stern necessity.
Adoption of advanced AI and ML tools
Businesses are turning to advanced artificial intelligence (AI) and machine learning (ML) tools to address the security challenges. These technologies play a pivotal role in bolstering organisations’ cybersecurity defences against evolving threats. By leveraging AI and ML tools, businesses can detect and respond to cyber threats more effectively in a number of ways including defending adversarial AI, responding to threats in real-time, and predicting future attacks.
Machine learning algorithms can detect anomalies and identify potential security incidents, providing businesses with early warning systems that can prevent catastrophic data breaches. With the growing trend of businesses equipping themselves with multi cloud platforms for their diverse workloads, the complexity is further increasing.
Generative AI will also serve specifically as a powerful tool for defenders, helping them elevate their skills, save time and gain speed by enhancing productivity within security operations centres through the automation of mundane tasks and use of generative workflows.
The need for unified security solutions
Managing security across various cloud platforms can be more challenging particularly with the issue of visibility across a network. It requires a unified platform approach that seamlessly integrates telemetry from across customer endpoints, workloads, identities, and data to offer accurate detection and real-time protection. AI and ML-powered security platforms provide the flexibility and scalability to protect businesses across different cloud environments. These solutions can adapt to the unique requirements of each platform, providing seamless security without compromising efficiency.
As the scope of cloud computing widens, the chances of unnoticed security breaches grow. Using appropriate tools is essential for gaining crucial insights into security status and fostering proactive security management. While major cloud platforms offer advanced native Cloud Security Posture Management (CSPM) solutions, they are often limited to specific platforms. Integrating specialised tools is advisable for comprehensive security visibility in hybrid or multi-cloud setups.
Furthermore, AI and ML also play individual yet vital roles in identifying and responding to threats.
Role of AI in identifying and responding to threats
Cybersecurity has always been a data challenge, but finding the faint signal of adversary activity hidden in trillions of data points is a significant undertaking. Solving this requires a powerful cloud-native data platform to handle massive volumes of data and a single agent architecture to ingest data into the platform. It requires AI and ML built into speed detection to quickly surface hidden threats and drive automation to simplify complex tasks. That is how we engineered and built the Falcon platform from the ground up.
While AI and ML have revolutionised cybersecurity, there are concerns about the potential misuse of generative AI.
Potential impact of Generative AI on cybersecurity incidents
Generative AI’s ability to create convincing fake content poses a significant threat, introducing complexities in distinguishing real from fake content, particularly in emails. Synthetic media like DeepFakes allows adversaries to convincingly mimic trusted individuals on video calls, amplifying social engineering threats. This might contribute to heightened scepticism towards online content, impacting public trust in information from public figures. A deepfake video recently went viral, targeting popular actress Rashmika Mandanna. The video, initially shared by British-Indian influencer Zara Patel, featured Rashmika dressed in a black workout outfit inside an elevator. Using artificial intelligence (AI) tools, the video was manipulated, replacing Zara’s face with Rashmika’s.
Cybercriminals could use this technology to create sophisticated phishing emails, deceptive websites, or even deep fake videos, accelerating cybersecurity incidents. To counter this threat, it is essential for businesses to invest in AI-driven solutions that can detect and mitigate the risks associated with generative AI.
Managing Director
CrowdStrike India
It is why we launched Charlotte AI recently, to give defenders a generative AI solution specific to security. We believe generative AI should be about generative workflows. It should make defenders better, faster, and rapid in surfacing the information they need to make smarter decisions. Generative workflows created by Charlotte can turn an 8-hour day of security analyst activity into minutes. Security professionals can have a conversation with Charlotte, get contextualised information they need, create workflows and go after the adversary. For example, it will condense thousands of pages of Intelligence reports into the insight you need to make better, faster decisions. It’ll also help security analysts with their work, hunting for signs of adversary activity, creating remediation, identifying exposure to vulnerabilities and more.
The integration of AI and ML technologies is imperative for businesses to safeguard their assets in the cloud. As cyber threats continue to evolve, so must our defence mechanisms. By harnessing the power of AI and ML, businesses can stay one step ahead of cybercriminals, ensuring a secure and resilient digital future.
