Tuesday, October 26, 2021

How to Improve Cybersecurity for Artificial Intelligence

Increasing reliance on artificial intelligence for critical functions and services may create greater incentives for attackers to target those algorithms. In this blog post, you will learn how to improve cybersecurity and safety for your artificial intelligence systems.

Cybersecurity, Artificial Intelligence,
Artificial Intelligence and Cybersecurity

Artificial Intelligence and Cybersecurity: How to Improve Cybersecurity for Artificial Intelligence

Artificial Intelligence (AI) has really grown in recent years. Just a decade ago ‘AI’, ‘open-source’, and ‘cloud-based were jargon used by IT specialists and we did not need to be in the loop. But with ever-increasing real-world and virtual threats, AI is becoming essential to information security, especially in light of data privacy in a digital world.  

With the growth of remote work, IT systems provide the ultimate target for cyber attackers. This is evidenced by cybersecurity stats from large organizations which show a large and imminent threat. These statistics are alarming and call for more secure environments in all spheres where data is exchanged. 


Understanding AI basics

Artificial intelligence (AI) refers to the basic systems, technology, or machines that imitate human intelligence to perform certain tasks. 

There are 3 AI basics to understand

  •  Assisted Intelligence – Currently used worldwide by organizations that enables employees to complete their daily tasks more efficiently and time effectively.
  • Augmented Intelligence – Emerging in the market today, enabling individuals and organizations to do things thought previously impossible.
  • Autonomous Intelligence – Futuristic developments like self-driving vehicles and machines that can perform tasks on their own.

Subsets used by AI to achieve organizational objectives

  • Machine Learning - Organizational computer systems use data to improve progressively performance.
  • Expert Systems - Programs designed to solve problems within specific domains.
  • Neural Networks - This biologically inspired method of programming enables computer learning from observed data.
  • Deep Learning - Is based on learning data methods and is often more accurate than human intellectual capabilities. For example, medical diagnoses, scan analysis, autonomous vehicles, or biometrics.

 AI and machine learning can help reinforce BIOS-level technologies that are embedded into each computer motherboard and constantly improve output. AI is a dual-use technology which means it can be used to protect an organization’s data privacy in a digital world or be used against the organization by cybercriminals. 


Exponential growth in digital infrastructure

Artificial Intelligence and Internet of Things are Inextricably Intertwined. Each year, millions of connected vehicles, wearable devices, and Internet of Things (IoT) devices are added to an already large consumer base. This brings over a hundred billion lines of software code, which is then added to the existing digital infrastructure

These digital technological and smart devices have improved customer experience, increased business agility, and revolutionized digital innovation.

With the number of devices increasing exponentially, connecting networks across various platforms have exponentially increased cybersecurity threats. As a result, these threats and attacks on organizations and individuals have become a primary focus for digital safety.


Securing AI Decision Making Systems

Artificial Intelligence (AI) and Machine Learning (ML) have hugely impacted the way organizations operate, people work, socialize, and complete daily tasks.

Organizations are basing their product development and sales strategies on customer-driven data. These organizations have access to personal data and are aware that they have to secure this intelligence. 

AI makes analyzing vast amounts of data effortless. It also provides critical insights into organizational information. These insights give owners and stakeholders the ability to view the larger picture, enabling informed decision-making.

AI can also be manipulated by hackers to compromise the integrity of the decision-making process. This has implications for every individual and organization. However, there are ways to mitigate these risks which is something stakeholders should be educated on. 

 

Applying AI to cybersecurity

AI is ideal as a problem solver and is best suited to prevent cybercrimes, due to its machine learning abilities. AI can always be a step ahead of external threats since automated threat detection and response is more efficient than traditional software-driven responses.

 

Cybersecurity has some distinctive challenges

  • An expansive and exponentially growing attack surface
  • Extensive attack vectors and devices
  • Shortfalls in skilled cybersecurity professionals
  • Data masses that are unscalable by security professionals

AI-based self-learning cybersecurity should be able to overcome most of the challenges above. Existing technologies working independently are able to train a self-learning system to deal with possible threats. It does so by analyzing data using billions of signals to reveal a possible point of attack.

 

Making AI systems safe and reliable to develop and deploy

Cybersecurity as the best defense in AI 

Implementing self-learning AI is the best way in which to be proactive and stay ahead of the infinitely changing technological advances, so as to protect your data from rising cyber attacks and protect organizations against cybercrimes.

During the COVID-19 pandemic, AI has been used to prevent related disruptions while still increasing efficiency, productivity, and innovation.

Using AI-enabled security cloud platforms is very effective against cyber-attacks. These cloud platforms continuously evolve as trillions of signals are intercepted daily. Organizations need a comprehensive architecture that can provide scalable real-time analysis and solutions across the threat landscape.

 

The Future of AI and Cybersecurity 

As the tech world constantly adapts and changes, cybersecurity risks will always need to be mitigated. Organizations will continuously need to identify, prevent, and guard their digital data against emerging threats.

AI cannot change this paramount dynamic. Research and implementation into harnessing the benefits of AI are critical. The importance of having data privacy in a digital world cannot be emphasized enough. 

As a user of any data or data system, it is important to understand the differences in data types and have an overview of what can be done to safeguard your data.

Cybersecurity is a threat and current AI is the best defense strategy. The future of AI needs to have the ability to self-propagate and make autonomous decisions by using data to repair the infected system and be alert to any signals caused by malware detection.

 

Conclusion

While the benefits of cybersecurity in AI are numerous, there’s still a lot of room for improvement. Using cybersecurity in AI is expected to advance in the future, thus ensuring that systems can respond better to attacks. In this technological day and age, staying one step ahead in the world of AI is an absolute must.

AUTHOR BIO: David Lukić is an information privacy, security, and compliance consultant at IDStrong. The passion to make cybersecurity accessible and interesting has led David to share all the knowledge he has.