Decoding AI Security: The Good. The Bad. And The Terrifying.

Generative Artificial Intelligence (AI) and Large Language Models (LLM) are rapidly evolving technologies that have the potential to transform our lives, both in the digital world as well as the real world. The recent launch of ChatGPT illustrated the appetite for and promise of AI, with the chatbot reaching 1 million users in just 5 days and more than 100 million users by two months¹.  

The impact of generative AI on our digital future is multi-faceted and far-reaching, ranging from improving productivity to enhancing user experience. However, it also raises serious concerns about data privacy, cyber-security and ethical considerations. We are about to see these innovations revolutionize our lives, transforming the way we connect, shop, eat, move, live and work.

Generative AI tools have the potential to improve digital security. They can be used to develop advanced threat detection systems that identify cyber-attacks before they cause significant damage. In addition, they can be used to develop secure communication channels and authenticate users, preventing unauthorized access to sensitive data.

But there is a flip side to every coin.

Automated content creation can also threaten digital security. Cyber-criminals can leverage this technology to create highly effective phishing emails, posing as trusted entities and tricking users into divulging sensitive information. Additionally, the automated nature of content creation makes it difficult to detect malicious content and poses a challenge for organizations to protect their users and their intellectual property. As AI models evolve, so does the sophistication of cyber-threats. This underscores the need for stronger cyber-security measures to protect personal and corporate data.

Very realistic "deepfakes" are now possible thanks to artificial intelligence. Using artificial intelligence algorithms, it is possible to create realistic images and videos that can deceive and manipulate information. While deepfakes have positive applications, especially in the entertainment industry, they can also be used to spread false information, incite violence and damage reputations. Deepfakes have potential implications for the creation of pornography, fake news, hoaxes, bullying and financial fraud. There are also examples of deepfakes being used for nefarious purposes, which is a serious concern for governments, law makers and security services.

The impact of generative AI on our digital and real lives will be vast and multifaceted. While it has the potential to improve productivity, user experience and revolutionize industries, it also raises concerns about cyber-security, data privacy, and ethical considerations. Addressing these challenges will require governments, technology companies and individuals to work together.

There are a number of companies that are helping to defend against the threats posed by the darker side of generative AI and LLMs:

CrowdStrike Holdings, Inc. is an American cybersecurity technology company based in Austin, Texas. It provides endpoint security, threat intelligence, and cyberattack response services. Crowdstrike’s world-class machine learning (ML) models are trained on CrowdStrike's unparalleled intelligence and security expertise to detect the most advanced threats while minimizing false positives. Crowdstrike’s platform model is trained on over 2 trillion events per day and is able to process over 180 million Indicator Of Attack (IOA) decisions every second².

Splunk, Inc. develops web based application software. The Company provides software that collects and analyzes machine data generated by websites, applications, servers, networks, and mobile devices assisting IT, DevOps, and security teams by offering data from different sources and timescales. Splunk uses AI to help IT operations observe patterns over time and, most importantly, predict what happens next. Splunk serves customers worldwide including Intel, Comcast, Coca-Cola³.

Visa, Inc. operates a retail electronic payments network and manages global financial services. The Company also offers global commerce through the transfer of value and information among financial institutions, merchants, consumers, businesses, and government entities. Visa has invested heavily in data analytics and artificial intelligence over the past five years to secure the movement of money and keep fraud rates low. The company has 60 petabytes (1 petabyte is 1,000 terabytes) of data and has embedded AI and analytics in more than 60 different services to spot and block fraud on its networks⁴.

OSI Systems, Inc. produces medical monitoring and anesthesia systems, security and inspection systems, and lasers, optics, and optoelectronic components. Its subsidiary Rapiscan Systems, a company specializing in walk-through metal detectors and X-ray machines for screening airport luggage and cargo, uses Artificial Intelligence to enhance the detection of prohibited items using advanced deep learning techniques and computer vision.

¹Source: UBS, Global Research and Evidence Lab, Feb 2023

²Source: Crowdstrike.com, June 2023

³Source: Golden.com, June 2023

⁴Source: Darkreading.com, April 2022

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