Cyber threats have come a long way since the days when, in order to steal secrets from a company, you needed someone who worked there. This person would be authorised to be on the premises and would be able to access confidential documents to find sensitive information.
These days, hackers can be miles away from the computers they access, and sometimes they may not even be in the same country. In order to gain access to systems and networks, they use viruses, spyware and ransomware – malicious software (malware) – which is especially designed to be smart and unobtrusive.
Since cyber threats are much more sophisticated today, Cyber Security needs to evolve accordingly, to identify them quickly and isolate them before they can do any significant damage.
In this blog, we discuss the future of cyber Security and how it is adapting.
The Future of Smart Cyber Security
Digital technology today is all about cloud computing, Internet of Things (IoT) and remote working. With so much personal information saved in vulnerable places, it has become more and more important to protect user data from cyber-attacks.
To ensure the protection of devices and networks that contain personal or sensitive information, cyber security needs to be equally smart, capable of recognising threats and automated to take action.
As such, here are the evolving technologies that we think will help secure digital information.
Artificial Intelligence – Supporting Cyber Security Technologies
Artificial Intelligence (AI) allows machines to mimic human performance, like learning and problem-solving. It does this by studying the information it comes in contact with, processing and understanding the data to reach a conclusion.
Because of this, it is capable of making simple decisions and undertaking simple tasks without the help of humans.
As AI becomes more advanced, it could support other technologies to detect and prevent extremely sophisticated cyber-attacks.
Machine Learning – Learning and Identifying New Threats
Machine Learning (ML) uses AI to instruct a computer so it can act without programming, by accessing the information it needs to acquire the requisite knowledge. Like a human being, it gathers experiences and learns from them to become smarter.
In the early days of cyber security, and even today, anti-virus (AV) software has been used to look for specific malware ‘signatures’ against a database of known threats. These databases have to be constantly updated as new viruses were developed. This is because AV scanners would detect unusual activity and check its signature against the database to identify threats. If the signature was not in there (as would be the case with any new malware), the AV scanner would not be able to identify the invasive software as a danger. This means that cybersecurity companies needed to constantly look for new malware as it was developed and add it to the database in order for AV scanners to be effective.
With Machine Learning, this system may be improved upon. Since the computer is constantly learning, it could be taught what constitutes as a threat, use that information to be able to identify malware and add this static database of malware ‘signatures’.
Using Machine Learning and AI, cyber security of the future could have computers monitoring their own networks to detect abnormal behaviour that may be an invasive software, even if the activity does not match any known malware signatures. It could also make identity management simpler by cross-checking logins, biometric and other identity marker information across multiple databases.
Automated and Adaptive Networks – Machines Monitoring Themselves
Both AI and Machine Learning can be instrumental in creating networks and systems that can monitor themselves in real-time. Such networks could scan for any anomalies and defend against it automatically. Such machines would also be able to update their defence, including firewalls and anti-virus software, to combat, diagnose and analyse any threat.
AI and Machine Learning could also support Robotic Process Automation (RPA), allowing websites or applications to perform rule-based tasks, which are simple commands that follow the same process each time. For example, if a virus needs to be removed by following a certain process – like removing it from a certain folder before it can be deleted from another location – Robotic Process Automation could be used instead of a person doing it manually.
These technologies could facilitate Security Orchestration Automation and Response (SOAR) products too. SOAR combines three software capabilities, which are:
- Threat and vulnerability management
- Security incident response
- Security operations automation
Using these capabilities, SOAR products collect information related to a threat from different sources. This data helps cyber security companies create automated responses to low-level attacks, freeing up cyber security experts to focus on higher-level attacks or strategies.
Using Robotic Process Automation, SOAR products would then implement these automated responses. As a result, machines and networks will be able to defend themselves with little to no human intervention.
Supercomputing – Rapid Detection and Response
Supercomputers are machines with higher storage and processing powers than mainframe computers (which are much more powerful than personal computers). These faster and smarter machines could find and eliminate threats even more rapidly.
Since they have such high processing capabilities, supercomputers could analyse regular network traffic to create a model against which they could compare current traffic.
As they can analyse, process and react much faster than normal computers, supercomputers can sift through more information than mainframes in a much shorter time. If there are any abnormal behaviours, these machines could detect and deal with them very quickly.
In fact, supercomputers could help companies secure systems not just at a personal or organisational level but also at the national level with their superior processing power.
As you can see, the future of cyber security is going to be reliant on AI to create smarter computers and networks that can defend themselves against any potential threats.
However, these will need to be used in conjunction with software applications that are developed for security.
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