Artificial Intelligence Focused Cyber Risk and Security Management

Year 2021, Volume: 5 Issue: 2, 144 - 165, 31.12.2021

Ahmet Efe

https://doi.org/10.33461/uybisbbd.972206

Cited By: 2

Abstract

While arming AI and machine learning for cybersecurity is still in its early stages, large-scale firms and organizations continuously develop autonomous defense capabilities that include AI and machine learning to protect their security systems and applications. In addition, intelligent cyber attackers have started to use independent AI algorithms, continuously developing their capabilities due to the advantages of automatically uncovering new security vulnerabilities for achieving their illegal goals. For this reason, attack tools that learn by themselves, automatically scan vulnerabilities, discover proper techniques to exploit and disable firewalls and attack directly have become very sophisticated. On the other hand, AI can play a critical role in risk management and providing more effective and agile service by automatically detecting risks and control vulnerabilities in the dynamic IT environment and reporting their probability and impact degrees. Therefore, while risk management can become more effective with AI, the risks exposed through AI have also become more sophisticated. This study investigates from literature and sectoral reports the role of AI in cybercrime and cybersecurity and the manageability of risks in the cyber area through AI algorithms. The study explores how serious the AI-based dangers and threats are and how they can help improve an organization's security posture and risk appetite against AI-powered advanced persistent threats (APT).

Keywords

artificial intelligence, risk management, IT risks, risk automation, smart MIS

Yapay Zeka Odaklı Siber Risk ve Güvenlik Yönetimi

Abstract

Yapay zekayı (YZ) ve makine öğrenimini siber güvenlik için silahlandırmak hala erken aşamalarda olsa da büyük ölçekli firmalar ve kuruluşlar, güvenlik sistemlerini ve uygulamalarını korumak için YZ ve makine öğrenimini içeren özerk savunma yeteneklerini geliştirmeye çalışmaktadırlar. Bunun yanı sıra, siber saldırganlar da yetenek ve araçlarını sürekli geliştirirken yeni güvenlik açıklarını ortaya çıkarmak ve yasa dışı amaçlarına ulaşmak için sağladığı avantajlardan dolayı otonom YZ algoritmalarını kullanmaya başlamışlardır. Bu nedenle kendi kendisine öğrenen, zafiyetleri otomatik olarak tarayarak hangi tekniklerle suiistimal yapılmasının ve güvenlik duvarlarının etkisiz hale getirilebileceğinin nasıl olanaklı olduğunu raporlayan ve/veya doğrudan saldırıya geçebilen otonom saldırı araçları büyük bir risk olarak çok sofistike hale gelmiştir. Buna karşın dinamik BT ortamındaki riskleri ve kontrol zafiyetlerini otomatik olarak algılayarak ve bunların olasılık ve etki derecelerini raporlayarak risk yönetiminin de daha etkili olarak güvenlik ve savunma hizmetine destek sağlamasında da YZ kritik roller oynayabilmektedir. Dolayısıyla YZ ile risk yönetimi daha etkin hale gelebilirken YZ üzerinden maruz kalınan riskler de daha sofistike hale gelmiştir. Bu çalışma, YZ’ nin siber suç ve siber güvenlikteki rolünü, bu alandaki risklerin YZ üzerinden yönetilebilirliğini literatür ve sektörel raporların incelenmesi yoluyla araştırmaktadır. Çalışmada, YZ tabanlı risk ve tehditlerin ne kadar ciddi olduğu yanı sıra, bir kuruluşun YZ destekli gelişmiş kalıcı tehditlere (APT) karşı güvenlik duruşunu ve risk iştahını iyileştirmeye nasıl yardımcı olunabileceği teknik olarak ortaya konulmaktadır.

Keywords

yapay zeka, risk yönetimi, BT riskleri, risk otomasyonu, akıllı YBS

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