Evolution of cyber warfare — how it has moved up from conventional threats to a digital siege

evolution of cyber warfare — how it has moved up from conventional threats to a digital siege

Evolution of cyber warfare — how it has moved up from conventional threats to a digital siege

Organisations today face a constant barrage of threats — right from malware and phishing attacks to ransomware and social engineering – as cybercriminals adopt newer tactics to exploit vulnerabilities and gain unauthorised access to information with more sophisticated and pervasive attacks.

These challenges are compounded in today’s distributed working environments where data can be spread across limitless services, devices, applications, and users. What has added to the complexity is the proliferation of artificial intelligence (AI) and machine learning (ML). While its impact on the digital world cannot be neglected, it presents a double-edged sword for security practitioners.

However, the larger advantage of AI lies with defenders. After years of needing to be right all the time while attackers only had to be right once, we can start to see how the scales could tip in favour of defenders with AI. If your organisation has the right platforms and the right telemetry, you can apply AI to operate at machine scale, draw meaningful insights, enhance team capacity, and move from simply detecting and responding to predicting and preventing.

AI — The Force Multiplier In Cybersecurity

Globally, there are an estimated 3.5 million cybersecurity jobs unfilled. Despite the high stakes to a company’s operations, revenue and reputation, many security teams remain understaffed due to the skills shortage. Through automation and interactive natural language interfaces, AI can enable workers with less specialised training to take on important, fulfilling, and well-paying positions around the world. While many contend that AI will eliminate jobs, I believe AI will help draw top talent with non-traditional security backgrounds to our field and expand the available market.

Helping make this possible, AI “assistants” are transforming the day-to-day lives of security professionals. With GenAI natural language interfaces, we are enabling the intuitive machine-to-human and human-to-machine interactions to augment individual and team outcomes.

These interactions monitor and flag issues for security workers like potential threat anomalies, while freeing them from time-intensive tasks around logs, policy and rule updates, patching, and ongoing security hygiene — many of which can be handled predictively and proactively by the security assistant in minutes instead of days. I see a world where a single security professional could scale their capacity by a factor of 10x or more, and where security teams operate with far greater efficacy.

Overcoming security obstacles with AI

A recent study by Cisco shows that in India only 4% of organisations are at a level of readiness we would define as mature, while 88% of companies feel confident in their ability to stay resilient amidst this evolving cybersecurity landscape. We cannot underestimate the threat posed by our own overconfidence.

That’s why we need to take big steps with AI to improve security resilience. Here are just a handful of today’s security obstacles that AI can help us overcome:

  • a. Currently, the average security team manages up to 70 point solutions, many of which do not interoperate with one another. AI-powered platforms can simplify and streamline the web of networks, clouds, devices, remote end-users, and applications that give security leaders headaches. Today's organisations need to prioritise investments in AI-powered integrated platforms with shared telemetry in order to operate at machine scale. 
  • b. AI is being used effectively by our opponents. Cybercriminals have access to the same sophisticated AI-enabled technologies that we do. For example, with generative AI, today’s phishing emails are more convincing and often highly personalised. AI can help us spot these threats as well as correlate data across email, web, endpoint and networks to identify high-level alerts that would otherwise be missed.  
  • c. Why hack when you can simply log in? Identity-related attacks are on the rise, and we need new techniques and technology to keep data secure. Historically we have asked if someone “can” access a system, but really, we should be asking “should” they be accessing a system. If an identity appears correct, but there are anomalies in behaviour — whether from a human or a machine — AI can pinpoint those suspicious patterns and automatically protect assets. 
  • d. Securing everything is hard when network infrastructure is becoming more and more highly distributed with edge applications and end points leveraging hundreds and thousands of microservices. This creates a scale problem for security that only AI will be able to help us with. For example, during my recent trip to India I learned that they are expecting to install 250 million smart metres across the country. That is 250 million end points that will need to be secured, monitored, and updated. Security at this scale requires a hyper-distributed approach powered by AI to be orders-of-magnitude more autonomous than how we operate today. 
  • We have a tremendous opportunity where AI can help us overcome obstacles like these and reimagine security to build a more sustainable, equitable, and secure future for everyone. By investing in integrated platforms, leaning into the responsible use of AI, and synergising human ingenuity with the computational capabilities of AI, today's organisations will begin to operate at machine scale and finally tip the scales in favour of defenders.

    —The author, Jeetu Patel, is EVP and General Manager, Security & Collaboration, at Cisco Systems, Inc., the US multinational digital communications technology conglomerate. The views expressed are personal.

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