Artificial Intelligence (AI) is a trending topic for many industries now. A variety of organizations currently employ AI mechanisms to support their operational functions. Automated tasks, natural language processing, deep learning, and problem-solving; such AI characteristics have made business tasks much easier. The factor of security in AI is largely overlooked, and with the increasing number of cyber threats and attacks, AI security serves as a crucial element that should be paid attention to. Security in AI falls into two different areas:
- Using AI for cybersecurity.
- Using cybersecurity for AI.
Using AI for cybersecurity
Distinct capabilities of AI, for instance, deep learning and unsupervised learning, serve huge benefits for cybersecurity since it holds the ability to analyze and mitigate large sets of potentially malicious data without any human interaction, while providing recommendations for future threats.
The application of AI for Digital Safety has several benefits and usages:
- The ability to detect and identify anomalous patterns and vulnerabilities within extensive networks. It is time-consuming or rather complicated for humans to monitor and analyze large-scale networks. With AI, analyzing data from multiple endpoints becomes more efficient and faster which leads to quick detection of vulnerabilities and threats before any attack is executed. AI-powered Intrusion Detection Systems (IDS) detect any unusual or malicious traffic over normal traffic that enters a network. A real-life application of Artificial Intelligence for IT operations (AIOps) platforms uses big data analytics and Machine Learning (ML) to detect problems by analyzing large amounts of data and predicting to prevent future issues.
- Accurate risk assessments and improved threat intelligence – Precise identification, analysis, and evaluation of risks, and recommendations of strong security controls for discovered risks can be accomplished through the compiled intelligence of AI. This also leads to the advancement of automated security models, thus building a strong organizational security posture.
- Ability to automate tasks – Time-intensive operations can be automated without any intervals, which will increase response times and reduce the pressure of handling complex security tasks for human analysts. IBM states that adopting AI and automation in security saves more than 14 weeks in threat detection and response times, and helps to reduce the overall costs of a data breach.
Unfortunately, the same AI technology used for defensive purposes can also be used by threat actors to breach systems. Attackers use AI-driven tools that constantly change their malware signatures to evade detection. They also use tools that spawn large amounts of malware to increase the power of their attacks. Using AI, malicious actors are able to launch new attacks, created by analyzing an organization’s vulnerabilities through spyware.
Using cybersecurity for AI
Artificial Intelligence programs are vulnerable to direct attacks as well. Machine Learning (ML) algorithms can be exploited by altering their functionality through data manipulation. The AI behaves as intended according to the data that is fed to it. If false positives are provided, it would bring damaging consequences to the ones who are relying on the intelligence of the system. This could also happen through vulnerabilities in the code, such as software bugs. Adequate testing mechanisms and bug bounty programs can be used to resolve this problem, but to protect the ML algorithms themselves, methods are still underway.
For all these matters various policies and standards have been proposed regarding the security of AI.
- The Brookings Institution suggests a policy of securing decision-making systems of AI. The authenticity of the programmed decision-making algorithms must be protected from any malicious influence that would alter their desired behavior. They can be manipulated by entering malicious inputs, such as data poisoning, or by indirectly training the AI model for defective results.
- The ETSI Industry Specification Group on Securing Artificial Intelligence (ISG SAI), states that they will create 3 standards to address the security of new AI technologies. They are, securing AI components of a system from attacks, mitigation against malicious AI that enhances or creates new attack vectors, and finally, using AI itself to improve and enhance security measures.
Artificial Intelligence is a powerful tool for identifying vulnerabilities, threats, and attacks in cyberspace. Security-focused AI is capable of detecting and analyzing enormous amounts of data without interruption, seeking malicious activities and providing necessary recommendations. The benefits are vast, however, AI software is itself vulnerable to data manipulation and poisoning, which destroys the integrity of their programs. Necessary procedures must be adapted to mitigate these issues and to protect and strengthen the functionality of AI.
About the Author:
Dilki Rathnayake is a Cybersecurity student studying for her BSc (Hons) in Cybersecurity and Digital Forensics at Kingston University. She is also skilled in Computer Network Security and Linux System Administration. She has conducted awareness programs and volunteered for communities that advocate best practices for online safety. In the meantime, she enjoys writing blog articles for Bora and exploring more about IT Security.
Editor’s Note: The opinions expressed in this guest author article are solely those of the contributor, and do not necessarily reflect those of Tripwire, Inc.