Final Exam: Generative AI Security Considerations

WHAT YOU WILL LEARN

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  Identify common challenges organizations face as they relate to cybersecurity
  

  list common cyber threats
  

  outline components of a successful cyberattack defense strategy
  

  list common use cases in which ai can help improve an organization's security posture
  

  state applications of ai in cybersecurity
  

  recognize advantages of using ai in cybersecurity
  

  outline how to monitor emerging generative ai technologies to stay safe and secure
  

  identify how to use generative ai to enhance security posture
  

  recognize how machine learning can be leveraged in cybersecurity
  

  outline the future of ai in cybersecurity
  

  list possible downsides of using ai in cybersecurity
  

  provide an overview of intellectual property and outline the relevance of ip
  

  identify common risks associated with intellectual property
  

  describe potential perpetrators of ip crime and assets that may be targeted, such as trade secrets and proprietary business information
  

  outline considerations when dealing with copyright
  

  provide an overview of brands and describe how artificial intelligence (ai) can be leveraged to protect them
  

  provide an overview of trade secrets and describe why they are often targeted by cyber criminals
  

  provide an overview of patents and outline how ai can be used to offer patent protection
  

  describe some of the challenges ai involved software has relating to patents
  

  outline patentable inventions and possible exclusions related to ai
  

  defend against intellectual property infringement
  

  detect intellectual property infringement
  

  outline legal considerations surrounding intellectual property and ai
  

  provide an overview of future trends of intellectual property in the era of ai
  

  outline common technical, ethical, and legal challenges of generative ai
  

  provide an overview of the principle of responsible ai
  

  describe why governance around generative ai is important and how it can be achieved
  

  describe how governments can regulate generative ai and what regulations are in place
  

  outline ai governance best practices, including engaging stakeholders, managing ai models, and building internal governance structures
  

  provide an overview of how ai auditing can be used to identify potential exposures and mitigate all potential risks
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  describe how generative ai monitoring can be used to enforce ai policies
  

  differentiate between technical metrics and business metrics
  

  outline steps to implement effective governance
  

  identify the benefits of user education and adoption when implementing a governance approach
  

  outline data and ai risk management considerations
  

  assess regulatory risks associated with known design options
  

  provide an overview of the rise of generative ai and how it can improve security
  

  identify common ai generative models
  

  outline considerations when picking a generative ai model
  

  describe how ai deepfake technology works
  

  identify ai-generated content and avoid misinformation
  

  provide proper attribution for ai-generated content and avoid copyright issues
  

  describe how generative ai is being used in healthcare, software development, business, and other industries
  

  list common use cases for boosting cybersecurity using generative ai
  

  provide an overview of key applications of the top generative ai models
  

  list common considerations that should be examined at the stakeholder level
  

  describe potential challenges associated with using generative ai
  

  outline common security protections when using generative ai tools
  

  provide an overview of the potential security risks of generative ai
  

  describe how to mitigate the risks associated with generative ai
  

  describe how to navigate generative artificial intelligence (ai) attacks and how to put countermeasures in place
  

  describe the concerns that generative ai brings on an ethical level and how privacy plays a role
  

  provide an overview of the increased risk of data breaches and identity theft
  

  describe how generative ai can increase and speed up social engineering attacks
  

  describe how generative ai can be used to help generate malicious malware
  

  outline how generative ai can be used maliciously to perform model manipulation and data poisoning
  

  provide an overview of how content created using generative ai can pose legal challenges
  

  describe how poor development processes can create risks
  

  list ways to enhance protection controls including processes, governance, and ethics
  

  outline common considerations for securing ai systems