5 ways AI can help strengthen security in a post-pandemic world
The role of machine learning and AI in a post-pandemic world across key sectors, like retail, and building and construction is continuously increasing.
As technology continues to develop at a rapid pace, a multifaceted defence is needed for hybrid risk management, integrating physical security with automated and cyber security defences.
2020 has already highlighted the impact of ‘hybrid’ risks, following the Australian Bushfires and now COVID-19, key sectors need to realise that adversaries can present both tangible and intangible. For example, a fire knocks out a data centre and then a pandemic prevents staff from accessing the site.
A CIO Tech Poll from February found 62 per cent of respondents felt that AI and Machine Learning was the most disruptive technology, and 42 per cent dubbed it the technology with the greatest impact—almost double the respondents that named big data analytics.
So what are the physical applications of AI and Machine Learning in a world where social distancing is enforced and we’ll be wanting to reduce our exposure to high-touch surfaces?
- Blockchain for a contactless security solution
Blockchain could be a creative solution for reducing, or removing, physical security measures in a post-pandemic world. It’s also a great data capture system, which is all important for Machine Learning. Without a data set to analyse, AI can’t learn.
We’ve already seen Blockchain implemented in the authentication of goods like artworks, where Blockchain can quickly and easily authenticate the artwork with a public (or private) record. The ledger can detail previous owners and transactions to ensure its provenance and prevent the sale of fakes or stolen pieces. This helps reduce the incentive to steal, and could be used in a retail setting for mitigating stock-loss without needing to remove garment tags.
In the art world, a simple solution has been designed whereby a physical seal of approval containing a chip with a key is attached to the artwork. This is scanned and opens the ownership log, confirming its the real deal.
In other sectors, like building and construction, there also exists an opportunity to replace some biometric security protocols and access points like thumbprint recognition with a Blockchain application. This can be easily scaled with the use of tokens and a private-to-private key.
What’s more, Blockchains technology can easily assist with contact tracing and occupancy counting—two key considerations in a post-pandemic world. Because of the ledger system that underpins blockchain, detailed information of who accessed a building (or part of a building) and when is easily accessible. It’s also more likely a budget friendly option when compared to a large scale biometric system.
As vice president and principal analyst at Forrester, J.P. Gownder told Computerworld, AI might become something of a colleague to many workers.
“For those of us who do not lose our jobs to automation, we are going to be working with increasingly intelligent software, side-by-side,” he said.
“It is going to become applicable to almost every kind of business process you can imagine.”
- Enhanced Capabilities
When purse strings are being tightened and budgets combed over, Machine Learning and AI can help with more accurate forecasting of project lengths, quicker planning processes, and risk assessment.
AI does this by learning from past mistakes, which humans can sometimes be slow to do.
AI and Machine Learning isn’t just helping businesses pick-up the physical slack during these times, it’s also helping businesses understand where they can be better. Taking a leaf from the medical sector, AI is helping data scientists glean insights by structuring and controlling the available data—something the retail sector is grappling with as online stores handle an onslaught of transactions.
Machine Learning is capable of handling much more data and quicker.
“In the ideal situation, these technologies are helping make better decisions, giving more insights, helping people execute certain tasks on their behalf automatically, or automating processes that are clearly not something that employees want to engage in anyway,” said Gownder.
Timing is important in a digital-first world because threats can happen anywhere, anytime, so any extra ‘arm’ in a security arsenal helps.
- Ability to pivot rapidly
This is particularly pertinent for retail as the sector has been forced to shift rapidly from brick and mortar stores to eCommerce, many without experience in the online space. In Australia, particularly for Victorians in Stage 4, the volume of online activity is huge—Australia Post facilitates an additional $2.4 billion in ecommerce during COVID-19.
As we know all too well, the rush to go online shouldn’t come at the cost of security. As your organisation’s customer base grows, so too does your database. Naturally, data protection becomes a looming concern—not just from ethereal threats but physical intrusions or natural disasters wreaking havoc on data centres.
One way to protect is with network diversity and ‘smart islands’, where systems are physically isolated so they can run applications independently without affecting or relying on other systems and the applications they’re running. Think of it like decentralising, just as Blockchain helps distribute and reduce ‘entrances’.
- Fortifying physical security remotely
If machines will begin to replace manufacturing staff for example, how will you ensure the security of those advanced assets and their IP as well?
It adds another layer of security considerations above and beyond structural security and armed patrols, and where the risk isn’t always physical.
And if remote construction becomes a reality, biometrics do a great job at keeping intruders out of buildings but what about your digital backdoors? How will you protect fulfilment centers remotely?
If an organisation has a near worker-less site with a fleet of drones, robotically enhanced exoskeletons and bots, their cybersecurity needs to be fortified. Machine Learning can detect and even predict attacks by reading network activity.
- Learns to act on threats
AI learns the queue of suspicious activity and can act on ‘instinct’. Case in point, the Australian Government themselves have partnered with IBM to develop secure data management and cybersecurity systems using Blockchain technology.
However, even with the most advanced AI there is of course still a need for a human element, to input quality information that enables the learning to take place—which comes down to your team.
An organisation needs to actively support its employees as they increasingly are interacting with AI as part of their role.
“Are your employees equipped with the right culture, skills, inclinations to be able to start working with increasingly intelligent software? A lot of people may not want to do that or may not have the skills—they may be intimidated by the technology,” said Gownder.
“It is quite possible to craft a better employee experience by investing in AI and automation, but it is also possible to do this wrong, as with anything.”
So where does this leave an organisation and what does the future of the sector look like? In a world where risk management continuously expands, AI can help fortify security on all fronts. Afterall, every bit helps.
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