In the opening presentation of Reset 2018, Mary Haigh, product director BAE Systems dissected the analogy of cyber-immune systems and biological immune systems, concluding there were indeed parallels - but its not an exact fit.
Artificial intelligence startup Clarifai failed to report that it had been hacked by Russian operatives while it was working on the Defence Department's Maven project, according to a recent lawsuit.
AI has contributed to the increase in cyber-attacks, but in this article Rob Holloway explains how AI could improve the accuracy of predicting, preventing and detecting cyber-attacks.
You won't become a great defender without attack capability. As a goalkeeper you need to play against the best to improve." Red teaming simulations part of AI tool learning process to identify truly malicious events.
Needing constant human input for AI training in cyber-security defeats the purpose of reducing the required human labour. Unsupervised learning is a whole other challenge. But AI needn't be 100 percent supervised or unsupervised.
Data needs context, meaning and insight to move it up to the level of wisdom or understanding. AI should always be seen as decision support rather than decision-maker. The latter role is always best left to the human mind.
Cyber-attacks can leave companies more clued-up and prepared from a technology and process perspective on how to cope with the damage they inflict - and can spur on implementation of new technologies - including those using AI.
As AI technology becomes standard in defence, it is likely to become equally standard in attack - with one side using AI to spot patterns of misuse and malicious activity, while the other uses it to find vulnerabilities and evade detection.
Learning algorithms are capable of recognising patterns in data and discern fraudsters from legitimate clients by correlating thousands of pieces of information that, most probably, wouldn't be otherwise noticeable to a human.
AI needs to be representative of the community it serves. It should use established concepts: open data, ethics advisory boards, data protection legislation, new frameworks & mechanisms, such as data portability & data trusts.
While we wait for technology to mature, businesses need to view AI as a tool to be harnessed by skilled cyber-security professionals, not used in place of them.
Organisations need to equip themselves with a united view of their entire network, extending from the endpoint through to the cloud - including penetrating through encrypted traffic that could be hiding malicious activity.
More data and hack case studies should allow professionals to take a step back and place attacks into a broader context, harnessing the power of AI to learn from these breaches.
Most ransomware victims hit more than once, and don't have defences. Industry adopting AI that deploys deep learning neural network machine learning is predictive by looking for and identifying the techniques scammers use.
AI driven applications rely on machine learning to make decisions but they cannot yet think for themselves though that is coming. Neural networks and expert systems may be inspired by the human brain, but there is little comparison.
Happy New Year! SC Media UK resumes news reporting on 2 Jan 2018. During the break, catch up on our experts' predictions for a range of positive and negative futures, from the impacts of AI to likely new Zero days.
Driving the Autumn Budget - speed of introduction causes concerns over safety of autonomous vehicles, including terrorist take-over, plus where responsibility lays - user, manufacterer (hardware/software) and regulator.
From reactive network security capabilities we moved to developing predictive capabilities and now we are now able to achieve prescriptive security capability, intervening autonomously or flagging up issues to assist human decisions.
Deloitte fell victim to a data breach that could have been prevented by having simple measures that are standard security protocols but businesses must not only focus on the basics, but also incorporate an innovative approach.
Kasparov disagrees with Turing that machines winning chess was such a watershed. He contends that the machine which beat him was not intelligent, it was very fast. It was just a matter of time before they became the winners.
Brian Cox explained that the use of quantum computing for factoring large numbers for cryptography was so effective that it makes classic cryptography redundant.
We can expect to see a cyber-security incident at a category one level within the next few years. The government specifying what it will buy is an effective way of changing the market - Ian Levy, technical director, NCSC
More talent, less technology is the best strategy for keeping networks safe. Rather than use AI, companies are better off paying a bunch of junior engineers to patch vulnerabilities all day says Heather Adkins.
Humans and machine learning will have to come together to test autonomous vehicles, and the idea of crash test dummy with an AI brain may soon become a very necessary reality.
CISOs do indeed need to articulate cyber risk to the board in a business context, but equally, the board need to get a better grasp of cyber and prioritise criticality of security integrity vs continuity of service vs profitability.
Given shortages of skilled staff, Ryan Benson says we need to change processes or adopting new technologies then get better at managing data at scale, at automating the tasks that slow down analysts.
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Staying safe and protecting data is increasingly going to be in the hands of artificial intelligence says Peter Boyle who adds, that we need to get this right, spot attacks and breaches earlier, and cut security costs.
The business world has been battered by successive waves of new technologies, but Sean Harrison-Smith says they need to take the risk now and deploy AI and big data for cyber-security as it may lead to fewer risks in the future.
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