Cyber Threat Intelligence Framework

Sample Solution

    Introduction Artificial Intelligence (AI) and Machine Learning (ML) models are increasingly being used in various sectors including healthcare, military, financial services, etc. However, their robustness against adversarial attacks is still an issue of great concern. Cyber threat intelligence framework provides a systematic approach to recognize and mitigate risks posed by cyber-attacks on AI/ML models.

Objectives The objectives of this dissertation are to analyze the existing literature related to AI/ML security threats and develop a cyber threat intelligence framework for increasing the robustness of AI/ML models against adversarial attacks. Methodology The research methodology employed for developing the proposed cyber threat intelligence framework will be based on an empirical approach. This includes conducting qualitative interviews with experts from different industries that use AI/ML technologies as well as analyzing existing literatures on the topic. A combination of both primary and secondary data sources will be used to identify relevant factors such as malicious actors who leverage AI/ML technology, attack scenarios that can be leveraged to disrupt model performance, techniques used by hackers to bypass defenses put in place by organizations etc., which need to be taken into consideration when designing a comprehensive threat intelligence framework for AI/ ML systems. Data Analysis Data collected from primary sources such as interviews with industry experts and quantitative survey responses will be analyzed using methods such as thematic analysis. Furthermore, Secondary data gathered through reviews of existing literatures and reports related to cybersecurity threats faced by artificial intelligence systems will also be analyzed using content analysis technique for further insights about security vulnerabilities associated with these systems and appropriate countermeasures required for protecting them from adversary attacks . Conclusion To sum up, this research project aims at addressing one of the major challenges faced by organizations while deploying or operating with artificial intelligence technologies - how effectively they can protect their sophisticated machine learning models from adversaries who may attempt malicious activities like training misleading datasets or manipulating outputs generated by these algorithms? Henceforth, the proposed cyber threat intelligence framework would help researchers build secure systems that are resilient against multiple forms of attack vector faced during adoption or deployment phase or while running these models in production environment thereby providing much needed confidence among users towards trustworthiness of applications built upon such algorithms