The rate of high profile cyber attacks against both individuals and organizations has increased dramatically over the last few years.
This has resulted in a much more vigilant attitude from the public, as well as increasing demand for better and more accessible security tools.
Naturally, the nature of both threats and defences within the realm of cybersecurity continues to evolve and mature.
As with all other major fields within the computing industry today, the cybersecurity landscape is increasingly being shaped by artificial intelligence (AI). And, like DDOS and other tech attacks, AI is not immune to intrusion and malicious vulnerability.
AI in Cybersecurity
Reactive cybersecurity only able to deal with threats that have previously been defined and categorized is not as effective as proactive cybersecurity.
Proactive cybersecurity can identify new risks that haven’t been defined before.
But working out whether a file contains any malicious code is easier said than done. It is challenging to have a computer analyze a piece of code to determine its intent.
Without these capabilities, there is little that can be done to prevent zero-day attacks.
Sophisticated algorithmic-based artificial intelligence can be trained to spot malicious software code. This is achieved by feeding the algorithm a huge trove of data. This data consists of examples of known malicious software.
By feeding a machine learning algorithm with many thousands of pieces of malicious software, it is possible to identify patterns and connections that our human minds are simply unable to.
This allows AI to work out whether a given piece of code is malware or not.
A zero-day attack is an attack which exploits previously undisclosed hardware or software vulnerability.
Zero-day attacks are particularly effective because there are countless ways hackers can exploit weaknesses before your developer issues a patch to fix the problem, or until the vulnerability is disclosed to the public,
The AI-driven approach outlined above represents one of the few defensive techniques that can be used to protect us against zero-day attacks.
By definition, a zero-day attack has not yet been properly documented; therefore, it is impossible to develop any effective countermeasures to fight it.
The only way to identify and defend against zero-day attacks is to devise a method of reacting to these vulnerabilities as they emerge. Only an AI-driven solution can achieve this.
Machine learning is a powerful concept in the development of AI.
As stated above, if we supply a machine learning algorithm with many examples of malicious code, the algorithm will eventually learn to identify whether any given piece of code is malicious or not.
However, machine learning can also be used by attackers to develop much more sophisticated attack vectors.
Countries around the world have been increasingly using machine learning against one another. As well as crafting more sophisticated attack vectors, there has also been a growing trend towards poisoning one another’s wells.
Poisoning the well refers to deliberately inserting bad or misleading data into the pool utilized by a machine learning algorithm. By presenting the algorithm with enough bad data, it is possible to undermine its ability to learn to spot new threats.
The fact that countries are looking for new ways to undermine one another’s defences by using ML and AI has alarmed many cybersecurity researchers.
They fear the proliferation of these tools and techniques will ultimately prove just as detrimental to the average person as they will to other nation-states.
At the heart of these concerns is the fact that cybersecurity and AI have no moral bias.
This means the same techniques and principles that are used to keep us safe can also be used to undermine our defence and attack us.
Staying safe in the face of increasingly sophisticated and prevalent AI-driven cyber attacks is one of the most difficult issues that cybersecurity professionals have to deal with.
AI has dramatically increased the amount of power available to individuals and organizations, for both offence and defence.
While the average person can continue using VPNs and antivirus software to protect themselves from day to day online threats, it will require something new from the industry to ensure users can remain safe in the future.