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It’s Algorithms vs. Algorithm in Cyber War

Very soon bots will be guarding network traffic, identify risks and plug in any weak points to eliminate security threats

It’s algorithm vs. algorithm; both cyber attackers and defenders are turning to artificial intelligence (AI). While cyber criminals, hackers are weaponizing AI to find vulnerabilities to penetrate an organizations IT infrastructure, cyber defenders or white hats as they are called in this industry, are using AI to recognize threats faster, look for patterns, and create rapid defensive mechanisms.

Cyber Security has been an issue ever since organizations started embracing internet connections. However, the threat landscape has continued to evolve as organizations have progressively added their strategic manufacturing equipment into mix to capitalise on the many benefits of embracing big data, machine learning and AI.

Unfortunately, these same technologies can rapidly become weapons, especially with nefarious characters setting their sights on new targets. According to results from a Darktrace commissioned study completed by Forrester Consulting, 88% of respondents think offensive AI is inevitable. And, almost half of respondents anticipate seeing AI-based attacks within the next year. With AI-powered attacks on the horizon, the report notes it “will be crucial to use AI as a force multiplier.”

One of the scariest elements of AI-powered attacks is that it can target the entire digital environment at the same time. IoT devices and environments will almost certainly be targeted. AI attacks will likely use different parts of the digital environment for different aspects of the kill chain. IoT environments might provide a very good slow-and-low data exfiltration vector.

Other key findings that emerge are as follows:

  • 77% of respondents expect weaponized AI to lead to an increase in the scale and speed of attacks, while 66% felt that it would lead to novel attacks that no human could envision.
  • 75% of respondents cited system/business disruption as their top concern about weaponized AI.
  • Over 80% of cybersecurity decision-makers agree that organisations require advanced cybersecurity defences to combat offensive AI.

Smart manufacturers need to think about security earlier in the development process and make it a priority. They also need to allow for easier integrations into a company’s existing security infrastructure. Businesses need to implement cyber AI for defence now, before offensive AI becomes mainstream. When it becomes a war of algorithms against algorithms, only autonomous response will be able to fight back at machine speeds to stop AI-augmented attacks.

The study similarly calls for AI defences: “If an organization is not operating with AI-enabled defences to counter AI-enabled attacks, how can it expect to win? The goal is to fight these advanced attacks with advanced tactics that detect, interpret, and respond to the threat before it has a chance to make an impact.”

Currently IBM is taking the initiative to apply AI and cognitive technologies to address cybersecurity issues, so that organisations can detect threats early and quickly, leading to more effective responses. Over 2 billion archives has been added tothe corpus and thousands are in the process of being included. This has allowed scrutinising incidents in the twinkle of an eye; what previously took hours to is now possible within minutes – leading to fast-tracking of redressals and minimising negative consequences in a big way.

Very soon we will have bots that will be guarding cyber-traffic, identifying risks and fortifying any weak points to eliminate security threats. Universally, such frameworks are gaining speed and initiatives are in progress. We find that the Big data start-up Splunk has entered into an collaboration with counselling firm Booz Allen Hamilton to offer AI-powered services to counter cyberattacks. Any textual communication over the network will increasingly use AI-augmented protection, as AI would help reveal more important and increasingly complex patterns that are currently not recognisable in existing information. Artificial intelligence is also being used to perform tasks that involve breaking down information where the volume is large, or the dimensions contained in it too complex to be interpreted by humans. These are the areas where deep learning machines would be taking over from us.

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