AI Security Threats

Incontrovertibly, technology has come a long way, with the latest trend being the rise of Artificial intelligence and intelligent automation (AI and IA) is a blessing to all sectors of the economy, including health, education, and commerce, with its benefits ranging from service automation and marketing to high-level data analytics that can be used to draw actionable conclusions. However, the evolution and increased adoption of AI has some serious concerns. Security threats and risks are among the key challenges faced by the rapid deployment of AI across all sectors. This is a significant loophole in the cybersecurity space, which, unless properly addressed, can lead to serious and irreversible consequences and losses (Hu et al., 2021).

Examples of AI Security Risks

Adversarial Attacks: Refers to the manipulation of AI systems, with the intent of compromising the accuracy of the results. This might include discovering a weakness in the AI system and using it to launch an attack against the model.

Data poisoning: This trick works by feeding AI learning models with incorrect data disguised as the correct data. As a result, the AI model is wrongly trained, creating a gap often used to maliciously alter the output of the AI model (Zaman et al., 2021).

Breach of Data: Training AI models utilize huge junks of data, which is required to be collected and stored. In this process, attackers can gain access to this data, which can be sensitive in nature, and use it unlawfully and unethically.

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References

Hu, Y., Kuang, W., Qin, Z., Li, K., Zhang, J., Gao, Y., ... & Li, K. (2021). Artificial intelligence security: Threats and countermeasures.?ACM Computing Surveys (CSUR),?55(1), 1-36.

Zaman, S., Alhazmi, K., Aseeri, M. A., Ahmed, M. R., Khan, R. T., Kaiser, M. S., & Mahmud, M. (2021). Security threats and artificial intelligence based countermeasures for internet of things networks: a comprehensive survey.?Ieee Access,?9, 94668-94690.