而人工智能可以减少工作量, provide new types of protection and increase adaptablity, 这也带来了新的风险.
Cyber安全解决方案 are constantly evolving to deal with emerging threats. The next step in this evolution is the adoption of highly specialized AI. 和任何新技术一样, however, organizations need to consider the risks associated with this new technology.
Signature-based detection systems have historically been the standard when it comes to warding off cyberattacks. These systems compare known threat signatures in their database with incoming network traffic and create an alert when suspicious behaviour is detected. 在大多数组织中, a security analyst will have to manually review many hundreds of alerts every day. A large number of false positives makes this a laborious process, and cyberthreats that don’t match the previous patterns can slip through the cracks undetected.
人工智能如何帮助一个组织?
Security models based on AI can analyze huge amounts of data in a short period of time, 发现模式和检测异常活动. 这带来了许多显著的好处:
• Reduced workload – AI cybersecurity software greatly reduces the number of alerts generated by the system. The cybersecurity team is able to focus on more complex, strategic work because they aren’t constantly overwhelmed by false positives. This makes the IT team more efficient, lowering operating costs for the organization.
• Better protection – AI is more likely to pick up new cyberattacks through pattern recognition when compared to a signature-based approach, which only detects threats that match those in its database. The speed of threat detection and response is very close to real-time, so hackers have less time to perform malicious activity if they do succeed in accessing the system.
• 更大的适应性 – AI-based platforms allow the cybersecurity team to respond quickly to address an increase in potential threats or new behaviour on a network without the need for additional staff.
人工智能的利弊是什么?
While AI-based cybersecurity software offers many benefits, it also comes with substantial risks.
• Data problems – AI models rely on the amount and quality of training data that they use to ‘learn’ about patterns of activity. A model trained with incomplete or inaccurate data may produce false positives or a false sense of security.
• Privacy concerns – The real-world data used to train AI models on traffic patterns needs to be protected by sufficient encryption to prevent its misuse.
• 资源消耗 – AI tends to have a larger carbon footprint than conventional 安全解决方案 because it consumes a substantial amount of energy and water to power and cool the data processing systems.
AI works both ways
While organizations consider deploying AI cybersecurity software, 网络犯罪分子也在采用人工智能. The technology is likely to assist with malware and exploit development, 脆弱性研究和横向移动, 在其他技术中. This will intensify cyber resilience challenges and increase the number of threats organizations face. One way for organizations to defend themselves is to fight fire with fire and adopt AI to counteract the new techniques and an increased number of attacks.
AI clearly brings both benefits and risks as a tool in cybersecurity. Yet, 正确使用时, 除了人类专家, it is a tool that has the potential to provide protection to organizations who are currently facing an unprecedented cyber threat. 安全必须是一个核心需求, 不仅仅是在人工智能系统的开发阶段, but throughout its lifecycle in order to minimize the associated risks.
了解更多与之相关的风险 网络安全中的人工智能.
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