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The next big business challenge: How organizations are preparing to secure AI

  • min read
    • Of all investments today, artificial intelligence (AI) is transforming enterprises, enabling them to provide improved services, automate processes and make better decisions. Business leaders must invest in the right tech at the right time, and have the people and systems in place that can guarantee success. AI will change most industries but also brings new risks and challenges in securing enterprises and safeguarding customers. Kaspersky's new research aims to help businesses stay ahead of the changes AI brings, published in this 2024 report, Connecting the future of business: How leaders should prepare for using and securing AI and interconnected technologies. About the interconnected tech research Kaspersky surveyed 560 IT security leaders in six regions – North America (US,) Latin America (LATAM: Brazil, Chile, Columbia and Mexico,) Europe (Austria, France, Germany and Switzerland,) Middle East and Africa (META: Saudi Arabia, South Africa, Turkey and United Arab Emirates,) Russia and Asia-Pacific (APAC: China, India and Indonesia.) Respondents were either aware of or involved in cybersecurity decisions about interconnected tech such as AI, web 3.0, data spaces, digital twins, augmented reality (AR,) virtual reality (VR,) 6G and internet of things (IoT.) They worked in organizations with at least 1,000 employees across many sectors. Kaspersky asked how they're introducing and securing AI and other interconnected technologies. Here's what the research revealed. AI is organizations' significant focus for the next two years AI is becoming a cornerstone for organizations striving to stay ahead thanks to its ability to foster innovation. In cybersecurity, AI offers predictive analytics and greater adaptability. Goldman Sachs says global investment in AI will reach 200 billion US dollars by 2025. AI is more than a technology. It's a strategy that lets organizations navigate today's complex business environment. AI adoption Nearly all organizations surveyed have already adopted (54 percent) or plan to adopt AI within two years (33 percent.) Respondents see Generative AI (GenAI) as valuable for improving security technologies' performance. Goldman Sachs economists Joseph Briggs and Devesh Kodnani say GenAI could boost global labor productivity by more than one percentage point yearly once its use becomes widespread. IT companies worldwide are upskilling their workforce and undertaking GenAI pilots to avoid falling behind. IT giants Accenture pledged three billion US dollars to data and AI investment, while French tech firm Capgemini is putting two billion Euros towards GenAI over the next three years. Securing AI 49 percent of organizations said they were extremely well, or well prepared, to secure AI. Almost 50 percent think AI is slightly or not at all hard to secure. Compared with securing other interconnected technologies, most organizations felt more prepared to secure AI. In responding to Kaspersky's survey, the head of cybersecurity at a Brazilian bank said, "I mostly don't find security problems with GenAI. We already understand how to run and train it." While many organizations feel confident in their ability to secure AI, a little over half felt less than well-prepared to secure AI. These businesses need to do more to prepare for the inevitable scale-up of AI-based technologies. AI makes digital trust and data compliance indispensable AI introduces new challenges and complexities in protecting sensitive data and maintaining digital trust. Digital trust is an aspect of customer trust. In Kaspersky podcast Insight Story, emerging tech security expert Malek Ben Salem described digital trust as, "Our confidence that our privacy is protected and secured, the reliability of digital transactions and how sure we are of the identities of those we engage with." Tech researchers McKinsey's 2022 Digital Trust report said 70 percent of people trust companies to protect their privacy, but most companies aren't meeting their expectations. Data breaches, unauthorized access and privacy violations can erode digital trust and lead to reputation damage, lost business and regulatory consequences. Building digital trust takes time but is essential to users' confidence in AI. How AI impacts digital trust AI lets organizations collect and store more data about customers, operations and interactions. This wealth of data helps gain insight but also means more risk of breaches. AI facilitates sharing data between devices, networks and organizations. Data sharing aids collaboration, efficiency and innovation but also means more opportunities for unauthorized access. As it is relatively new, organizations may struggle to be clear about their practices and security around AI. Without clear communication, trust may break down. Top ways organizations are improving digital trust and compliance Adopting zero-trust frameworks is organizations' top response to the need to improve digital trust, with 81 percent already using or planning to adopt zero-trust within two years. Other actions include pursuing data privacy and cyber resilience regulations (74 percent) and digital sovereignty initiatives (73 percent.) Kaspersky's research found companies introducing zero-trust frameworks are better prepared to secure AI and other interconnected technologies: 51 percent of zero-trust framework early adopters said they were extremely well-prepared or well-prepared to secure these technologies, compared with just 27 percent of the rest. The zero-trust canvas: Painting the future of cybersecurity The rise of AI is opening the door for organizations to break with all traditions that don't work for today's tech realities. Traditional cybersecurity is vulnerable to insider attack because it relies on trusting those within a network's perimeter while viewing outsiders as suspicious. Enter: Zero-trust frameworks. The head of IT at cloud provider Searce said, "The zero-trust security model is the only framework that works. The traditional security model can't do the job, especially for interconnected technologies." Under zero-trust frameworks, every user and device must undergo continuous multi-factor authentication (MFA) and authorization, regardless of their trust level. Users and devices get the minimum access needed for their tasks, with constant monitoring of user activity, device behavior and network traffic. Regulation and compliance With each territory having different data protection and privacy legislation, global organizations find it hard to achieve consistent standards around AI. 62 percent of leaders find compliance certification hard. They want to see standardized compliance processes across regulations and say online tools and platforms, with clear guidelines, would further simplify certification. Handling growing challenges and preparing to secure AI With the scale of change AI will likely bring, organizations must have a strategy to prepare themselves to adopt and secure it. Kaspersky research uncovered four effective strategies to ensure readiness to secure AI and other interconnected technologies: Adopting security by design principles, training and upskilling your workforce, upgrading your cybersecurity solutions and meeting regulation and standards. The full report, Connecting the future of business, details each strategy. Interconnected technologies like AI bring huge business opportunities but also a new era of vulnerability to serious cyberthreats. With more data collected and transmitted, cybersecurity measures must get stronger. Organizations can use effective strategies to safeguard critical assets and fortify customer trust amid a growing interconnected landscape. Leaders must also resource cybersecurity well enough to enable access to improved cybersecurity solutions that can meet oncoming challenges.
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Four ways to prepare your business to secure AI and interconnected technologies

  • min read
    • Of all business investments today, interconnected technologies – the growing network of devices, systems and applications connected to the internet and to each other – are the most vital and challenging. From artificial intelligence (AI) to data spaces to internet of things (IoT,) interconnected tech is letting enterprises gather more data, automate processes and make better decisions. While this 'Fourth Industrial Revolution' is propelling change in every industry, it also brings new risks and challenges in securing enterprises and safeguarding customers. Kaspersky's new research aims to help businesses stay ahead of the changes interconnected technologies bring, published in this 2024 report, Connecting the future of business: How leaders should prepare for using and securing AI and interconnected technologies. About our interconnected tech research Kaspersky surveyed 560 IT security leaders in six regions – North America (US,) Latin America (LATAM: Brazil, Chile, Columbia and Mexico,) Europe (Austria, France, Germany and Switzerland,) Middle East and Africa (META: Saudi Arabia, South Africa, Turkey and United Arab Emirates,) Russia and Asia-Pacific (APAC: China, India and Indonesia.) Respondents were either aware of or involved in cybersecurity decisions about interconnected technologies. They worked in organizations with at least 1,000 employees across many sectors. We asked how they're introducing and securing AI, web 3.0, data spaces, digital twins, augmented reality (AR,) virtual reality (VR,) 6G and internet of things (IoT.) Four interconnected tech preparation strategies With the scale of change these new technologies will likely bring, organizations must have strategies to prepare to adopt and secure interconnected tech. We found organizations that felt ready to secure interconnected tech tended to adopt four strategies: Embracing security by design principles, training and upskilling their workforce, upgrading their cybersecurity solutions and striving to meet regulation and standards. Here's a little more on each strategy. 1.    Adopting security by design principles Integrating cybersecurity into each stage of the software development lifecycle makes secure-by-design software and hardware more resilient to cyberattacks. Our research found leaders focused on integrating cybersecurity into development processes – dubbed Security by Design Promoters – were also better prepared to secure interconnected technologies. 50 percent of Security by Design Promoters felt prepared to secure interconnected tech, compared with 26 percent of the rest. Leadership teams can start promoting security by design by asking where in their design processes cybersecurity expertise is usually first involved. They may also play a role in ensuring budget for security testing during design. 2.   Training and upskilling your workforce With the right cybersecurity education, staff can be a formidable line of defense against cyberattacks. Building a cyberaware culture requires a strategy that empowers employees to gain knowledge and put it into practice. Our research found Training and Upskilling Promoters – organizations prioritizing training and upskilling their people – were better prepared to secure interconnected tech. 55 percent of Training and Upskilling Promoters felt prepared to secure interconnected tech, compared with 25 percent of the rest. Leaders we surveyed shared cybersecurity education approaches that worked well. They favored regular programs covering topics like cybersecurity policies and common cyberthreats, phishing simulations to identify further training needs and awareness campaigns sharing best practice and real-world cyber incident examples. Leaders also emphasized user-friendly security policies, greater collaboration with the IT and security teams and demonstrating good cybersecurity practice from the top. Leadership teams can support training and upskilling the workforce by asking how often employees receive cybersecurity training and how the organization measures their understanding. 3.   Upgrading cybersecurity solutions More devices connecting to the internet means more ways to attack. As businesses adopt these technologies, they need more advanced cybersecurity solutions, such as those with enhanced access controls, encryption and regulatory compliance. Our research found Advanced Cybersecurity Adopters — organizations focused on upgrading cybersecurity solutions — are better prepared to secure interconnected tech. 55 percent of Advanced Cybersecurity Adopters felt prepared to secure interconnected tech, compared with 22 percent of the rest. Advanced cybersecurity solutions let your business adapt to evolving threats, meet new regulation and protect critical data. The leadership team should ask what the organization knows about threats that suggest upgrading cybersecurity solutions, how to minimize the impact of upgrading solutions on workflows and how to ensure employees can use the upgraded tools effectively. 4.   Meeting regulation and standards To avoid legal problems or reputation damage, your cybersecurity practice must meet changing standards and legal requirements. Our research found organizations prioritizing meeting new regulation and standards — Regulation Promoters — are better prepared to secure interconnected tech. 40 percent of Regulation Promoters felt prepared to secure interconnected tech, compared with 27 percent of the rest. To better meet regulation and standards, leadership teams can ask if the organization already meets all security regulation and standards, and if not, which to prioritize. You might also look at how to use cybersecurity compliance processes to build customer's digital trust. Interconnected technologies bring huge business opportunities but also a new era of vulnerability to serious cyberthreats. With more data collected and transmitted, cybersecurity measures must get stronger. Organizations can use these four strategies to safeguard critical assets and fortify customer trust amid a growing interconnected landscape. Leaders must also resource cybersecurity well enough to enable access to new cybersecurity solutions that can meet interconnected tech's oncoming challenges.
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As AI’s influence rapidly expands, here’s how business ethics must keep up

  • min read
    • We live in a world where algorithms can make decisions and data fuels innovation. It means ethical considerations are more critical than ever for business. They must balance using new technology to increase competitive advantage while preserving integrity and protecting customers. In our podcast Insight Story, experts Tomoko Yokoi (Switzerland,) senior business executive and researcher at Global Centre for Digital Business Transformation, IMD Business School and Andy Crouch (UK,) consultant and co-founder of ethical-AI natural language processing company, Akumen, outline how AI biases can impact business and what steps they can take to ensure its fairness. Kaspersky Global Research and Analysis Team's Dr. Amin Hasbini expands on the privacy and responsible data use implications. Not all AI is created ethically equal Andy's company Akumen found a problem that needed solving. "Scores out of five are useful, but we wanted insight from written responses like product reviews, and there was no way to do it. The team created an AI solution to identify meaning like topics, emotions and sentiment. Sentiment measures opinion – positive, negative or neutral – but emotions drive behavior. It works on text feedback anywhere, which might be about consumer goods, healthcare or anything else." Their approach uses AI differently from generative AI tools like ChatGPT. "Our AI is rule-based, human-created and human-curated. It's completely transparent and there are no algorithms as with large language models. We can dive in and make rules more nuanced if we recognize bias. With large language models, that would be complex and expensive." Andy expands on generative AI's limits for truly understanding people. "We asked ChatGPT how many emotions humans experience – it said 138,000. That doesn't help us understand what drives behavior. Our platform has 22 emotions – enough to see what drives behavior. Through our partner, Civicom, we're helping the UK's national health service (NHS) to understand what patients and staff experience." And that understanding can improve lives: Larger language models use big data pools, but there are also more contained, enterprise-level tools like ChatGPT Enterprise that businesses can furnish with their own data and control how they use it. Tomoko sees enterprise-level tools as useful but notes they can't do what big data can do. "Organizations are developing new functions around AI, like data annotators, who clean data before it goes into models. But is it foolproof? The beauty of using data from everywhere is it gives you insights you otherwise wouldn't get." Choosing ethical suppliers Luckily for companies using AI ethically, more businesses are adopting digital responsibility policies and choosing ethics-first suppliers. Tomoko gives an example. "Deutsche Telekom has been a pioneer in AI ethics. They've trained all employees to ensure AI ethics are distributed throughout the organization. At the same time, they have about 300 suppliers and ensure it's in all their contracts. So it goes beyond the boundaries of the company." But many businesses don't know where to start. Tomoko says, "Over 250 companies have committed to AI ethics, but codified mechanisms only help if they change behavior. How can we live these principles and ideals? External experts can help, and there's a case for individuals taking responsibility, which will have a collective impact." She suggests how companies frame AI ethics matters. "You can see AI ethics as value or as compliance. If it's compliance, it will be cost- or risk-driven. But AI ethics could also be a competitive advantage." Andy compares AI ethics to health and safety. "If you have a health and safety director, it's only one person's responsibility. Change won't happen unless everyone understands health and safety's importance, and especially that it drives productivity and revenue." The competitive advantage is real. McKinsey research found 72 percent of customers considered a business's AI policy before making an AI-related purchase. Tomoko highlights the importance of backing up policies with action. Which AI issues should companies care about? Tomoko outlines three places to look. "First, consider the software development lifecycle. If you're considering developing an AI product, think of how it's designed. Look for bias in the data. "Second, once it's being developed, although many companies say they're implementing AI ethics, people developing AI-driven products don't know how to apply those principles. So, look at how people use ethical principles in day-to-day software development. "Third, we test products in controlled environments. Once it launches, ask who is monitoring it and how we ensure it doesn't gather bias and that people use it correctly." Tomoko is part of IMD Business School and knows that what future executives learn about AI ethics will shape future companies' ethical behaviors with AI. She says, "First, we say everyone has a responsibility to these issues that goes beyond the company. You need to be aware of this responsibility, but also be able to make others in your team aware." Secondly, "What type of organizations do we want to build? We coach people to be able to handle multiple goals – not only profit but also social, environmental and ethical goals. We want them to walk away thinking of the future." Andy drills down into the data AI is using. "Understand how the AI model is built. Is the data you're analyzing through that AI model ethically sourced, and are you using it ethically? The lack of transparency over large language models is rife for ethical risk and bias." AI training data bias can have life-threatening impacts. Poor AI translations have been found to be jeopardizing asylum claims. Andy sees retrieval-augmented generation (RAG,) which uses more proofed datasets, as part of the solution. Can we have secure and well-regulated AI? Dr. Amin Hasbini. Head of Research Centre, Middle East, Turkey and Africa for Kaspersky Global Research and Analysis Team, thinks AI ethical standards are needed. "AI won't self-define its ethics. They must be programmed with ethical standards." Since there is almost no way the public can evaluate, critique or improve AI ethics, regulation must play a part, according to Amin. "We need security and safety by design, and continuous verification of it. That would require transparency, especially from big tech vendors, and letting the public influence how these technologies develop." He likens the challenge to that of regulating social media. "We're asking people to adopt technologies that can do much damage without giving them ways to ensure that doesn't happen. The same has happened before with social media, with it being used for data leaks and fake news. European Union regulation is moving fast around AI, but AI could be much more dangerous than social media – we need rules now." For improved ethical data use, Amin recommends asset management controls. "If well deployed, asset management controls allow data to be classified, including which is available to AI, which can be shared publicly and which needs to stay inside the organization." Andy says regulation is hard in this fast-moving space because no one knows what's coming next. "I question anyone saying they know what will happen in the next six months or beyond. But there's a lot of fear and lobbying going on – so go slow. If your AI-driven capability can't deliver because it's non-compliant, ethically or otherwise, it will be damaging." However, he believes regulation is necessary. "It will be interesting to see how they regulate something that's not easily defined and morphs quickly, but we must protect those who need protecting." Kaspersky has recently proposed six principles for ethical use of AI in the cybersecurity industry with transparency at the core. Getting started with AI ethics Our experts have straightforward advice for those business executives yet to approach AI ethics. Tomoko says, "As a mindset, remember the analog and digital worlds are the same. Your analog-world values should extend into the digital world." Andy highlights the need for both widespread knowledge and deep expertise. "Get your whole team conversant with AI, but have a well-informed friend who lives and breathes this stuff to call when there are challenges." With headlines about AI taking our jobs and AI founders like Geoffrey Hinton sounding the alarm on unregulated AI perils, it's easy to write off AI ethics as a problem too hard to fix. But these complex issues need priority. There are green shoots of change. In December 2023, the AI Alliance launched to focus on developing AI responsibly, including safety and security tools. Its 50 members include Meta, IBM, CERN and Cornell. The message may be, 'Let's not move too fast and not break things.' With OpenAI, creators of ChatGPT, not invited to the party, could the tortoise of collective corporations beat the nimble hare of innovation? AI gives business potential for great gains but comes with great risks to reputation, security and privacy. With strong ethical AI policies translated into action and widespread knowledge among employees, businesses can have more confidence to take advantage of AI's many benefits.
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How to get better returns on business tech investments

  • min read
    • In a tech store, it's tempting to convince yourself you need the latest shiny gadget. That device upgrade will radically improve your productivity. You leave with a bag of stylish little boxes and a dented credit card. Enterprise tech decision-makers also struggle with these magpie-like impulses. Recent research found GE, Ford and other major players poured 1.3 trillion US dollars into digital transformation. 70 percent of it – $900 billion – went into failed programs. That's quite some buyer's remorse. Businesses know they need tech for competitive advantage – but which tech? And when they've got it, how do they use it effectively? In our podcast Insight Story, Olivier Blanchard, Research Director for future analysts The Futurum Group, and Arun Narayanan, Chief Digital Officer at renewable energy service providers RES, share how business leaders can ensure best bang for their new tech buck. Every enterprise is different Olivier says there's no one-size-fits-all approach to getting better tech returns. "A major mistake is picking tools because other companies are using them. A solution might be good for your problem but might not suit your company's technical capabilities and cultural processes." Instead, he suggests figuring out what you need the technology to achieve. "Understand your problems and look for the best solution to help them." Arun, who has overseen digital transformation in several big mining and oil and gas companies, echoes Olivier's belief in starting in the right place. "Don't rush around trying to work out what a technology can do for you. Instead, think about how you want to change your business. Do you want to delight customers in new ways? Make employees safer and more productive? Get better returns for investors? Imagine the business processes, then find the technology to make them work." He gives an example from sectors he's worked in – oil and gas, mining and renewable energy. "What they have in common is the work is in remote places. They now have remote operations centers giving information on screen to those who can do the work but can't spend days to weeks away." But the aim isn't to replace those working on-site. "Successful digital transformation will balance what's operationally correct at a site and what a remote center can know and understand. You can't take all control away from operations, nor can those making minute-to-minute decisions on site examine long-term trends and patterns." Evolution or revolution? Olivier thinks senior leadership can contribute to improved returns by appreciating the size of change possible. "If you want to become more competitive within your existing understanding of your company, then it's about finding problem areas to optimize." Arun suggests one place to start. "You're spending a lot of money on this, so find the waste. For example, if you don't know where the oil is and you're drilling in the wrong location. The business question is, how do we drill more in the right place?" The answer isn't always high-tech. "Once you understand the business question, you'll know what technology to find. If software from the 1990s can solve your problem beautifully, use that. Or if you find nothing available, technology like AI might solve it." Getting the people on side Failing to bring your people along on the tech journey can be expensive. Many fear technology will replace them, with Elon Musk saying there'll be no jobs for people in the future. How can leaders ensure people understand tech is there to help, not put them out of work? Arun says, "When calculators came out, they didn't replace accountants – but they let them do a better job, faster. Generative AI solutions like chatbots and document generators are tools – they aim to do the mundane piece fast, then the artistic, skillful and human piece can follow." Arun has had much experience getting people on board with tech integration in industrial settings. "Technology change will create many new jobs. The economic models will change, jobs will be created and lost." "We'll still need project managers, HR and people who can communicate. You don't need to be a technical expert to take part in the transformation." Olivier highlights that cost savings can flow from upskilling employees. "It's easier for someone to learn a new skill than learn everything about a company from scratch. Focusing on employee retention and development rather than letting workers fall by the wayside makes good financial sense." Cybersecurity education's role in new tech adoption Dr. Amin Hasbini, Head of Research Center Middle East, Turkey and Africa for Kaspersky Global Research and Analysis Team (GReAT,) thinks successful tech adoption means getting everyone up to speed on cybersecurity. But many companies aren't yet doing it. Amin says, "A recent Kaspersky and Longitude study found organizations that emphasize cybersecurity training have 25 percent more readiness for dealing with security incidents from employees." The most effective forms of cybersecurity education are generally immersive. Amin says, "Gaming and VR are great for security training because they allow better engagement and learning. Gamification and competition challenges improve managers and director safeguarding decisions." Some approaches are even more immersive. "The most successful involve simulating a real attack on the organization when only a few people in top management know it's a simulation. They test employee capacity and how well teams cooperate to contain and close down an incident." Training must go beyond the IT team. "Security everyone's job, from desk employees in a remote office to top managers. If everyone is aware, it stops incidents getting big." How much risk is right? Arun says businesses must accept that in making room for success, some initiatives will fail. "If you're reimagining with a bold vision, you're guessing about the future. Some guesses will come true – others won't. If your structure has no room for failure, you sell out the opportunity for innovation." He says one way is to make a few calculated smaller bets rather than one big bet. Even if some fail, it's better than not taking those risks. Olivier points to lower-risk ways to trial solutions. "You don't have to buy all your technology anymore. With cloud services and managed services, fantastic industry partners can help you test, implement or scale up new tech. There's a giant menu of opportunities to get expert help." With enterprises finding many tech investments don't pay off, there's much potential for competitive advantage in smarter exploration of new tech options. Business leaders may find more implementations succeed if they start with the right problems and upskill their people as part of the transformation.
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Quantum computing: Is it time for your business to get involved?

  • min read
    • In Douglas Adams' 1979 science fiction comedy novel The Hitchhiker's Guide to the Galaxy, a supercomputer called Deep Thought takes 7.5 million years to answer the question, "What is the meaning of life?" Unlike Adams' monolithic supercomputer, quantum computers will be like today's fiber broadband compared to 1990s dial-up internet. Google's quantum computer can perform a calculation 158 million times faster than classical computers. Quantum computing's sped-up computations could reshape nearly every industry. But it also has strange quirks that make it hard to use in ways that beat classical computer abilities. At least, that's how things are today. Businesses that value innovation are throwing their hat in the quantum ring to ensure they're ready for sweeping change. Should your business get involved – and if so, how? In Insight Story Season 2 Episode 3, I discuss quantum computing's relevance to business with Dr. Oliver Thomson Brown (UK,) Chancellor's Fellow at EPCC (formerly Edinburgh Parallel Computing Centre,) University of Edinburgh and Dr. Henning Soller (Germany,) Partner and Director of Quantum Research, McKinsey & Company. What is quantum computing? Quantum computers are the next step up from the powerful supercomputers that often power AI applications today. They'll be part of our computing future but have a starting role today. Quantum and classical computers are very different beasts – in fact, they can't even communicate with one another. Quantum data is different, too – for example, you can't copy it. Some quantum computers must be kept at very low temperatures in purpose-built fridges. These features may not sound encouraging, but quantum computers have potential to do some things much better and faster. These abilities could be game-changing in many sectors, including finance, chemicals and logistics. How could business use quantum computing? Despite quantum computers currently being about as sophisticated as the classical computers of the mid-20th century, business is interested. Henning advises companies throughout Europe and the Middle East on large-scale IT and data transformations. He's confident quantum's impact will be huge. "We haven't yet proven a case where quantum computers outperform classical computers, but we're certain this technology will be the major disruption for the business in the coming decade. We estimate economic potential of at least several trillion US dollars." Oliver's research focuses on the interaction of quantum and high-performance computing. He says quantum could help with problems where the solution is a sequence of binary numbers. "That might include logistical problems around deciding where things go. For example, how do you fill beds in a hospital ward? Or flow- or network-type problems, like traffic management. Quantum computers may also have advantages when finding the best configuration for a molecule, like in drug discovery." Quantum might also work well for problems that scale poorly on classical computers. "We're looking at problems in aviation and genomics. Genome assembly scales factorially – with a quantum computer, we may be able to reduce that by a lot." Henning adds, "We could use it for experiments that we need humans or animals for today. We could test chemicals much faster and transact money in different but completely secure ways. Some banks are using it for derivative pricing and Monte Carlo simulations." It's something of a hammer looking for a nail, he says. "It's not about having an advantage today, but being able to exploit the advantage tomorrow." Quantum challenges Oliver says, "Adoption will be driven by how easy they are to use." But today, quantum computers aren't easy to use. "You have qubits, and multiple qubits form a register. Then you set up quantum gates in a circuit that apply to that qubit register and transform it – hopefully – into a state representing the solution to your problem." If you didn't understand that, don't worry – classical computers don't get it either. That's one of the biggest challenges that must be overcome for quantum to go mainstream, says Oliver. "You have results stored as quantum information on qubits in your qubit register, but you can't read that out directly into a classical computer. So what do you do with it?" And that's not all. "You can't copy quantum information. That's great for security but terrible for computing," says Oliver. With technology this imperfect – and let's face it, confusing to anyone without a computer science PhD – the business benefits are less obvious. Henning suggests looking at the bigger picture. "There is value in investing in quantum computing already, but not in profit and loss terms." Is quantum a security threat? A 2022 study claimed that it will soon be possible to crack the most established crypto algorithm by combining classical and quantum computing. It comes down to the role giant prime numbers play in encryption. Oliver says, "The first big quantum computing application was for factoring large prime numbers. It has no practical use except that we use large prime numbers for encryption. But security people now know it's not a good base for security, and they're looking at alternatives. It must be something quantum computers are bad at." Dr. Amin Hasbini, Head of Research Centre Middle East, Turkey and Africa for Kaspersky's Global Research and Analysis Team agrees the cybersecurity industry is one step ahead. "Quantum computing will also make encrypted data harder to hack, but hackers will find ways to adapt as they always have." Henning sees the need for improved encryption as a quantum business opportunity. "Quantum cryptography is a whole new industry. It's a major area of active investment." He doesn't see hackers accessing quantum tech just yet. "This is elaborate technology – not something you can steal and easily operate." Oliver thinks one quantum quirk might foil decryption attempts. "The error rate for quantum computers is huge compared to classical computers. You're likely to hit an error with any big circuit. You'd need a very large quantum computer, and we're nowhere near that." What will quantum computing's future look like? What are the next steps to unlocking the potential of quantum computing? Henning says, "The first machines will be hybrid by design because programming them will require a classical computer. Several technologies will need to come together to operate them successfully. They must intelligently break down a problem into what suits each technology and then put the overall result together." He suggests business leaders embrace the future. "This revolution is coming – not tomorrow, but in a foreseeable timeframe. It may make sense to set up a smaller team to scout the technology and identify use cases. Look for opportunities to partner with quantum startups. Your business can bring the knowledge of problems that need solving." Oliver agrees it's not about having all the expertise in-house. "Build partnerships with specialists who understand how to get the most of it." Quantum computers can't do much today, but their potential is undeniable. Businesses exploring this new realm are investing in a reputation for innovation and the possibility of solving today's hard problems. Difficulty accessing and using the technology should keep hackers at bay for now, but cyber researchers are working on new encryption methods that quantum computers can't crack.
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Predictions for Earth 2050: How will cybersecurity change?

  • min read
    • If you're like me, having a long-term vision is a wonderful aspiration… frequently quashed by today's more screamingly imminent 'to do' list. Five-year plan?  I'm still working on the next five days. But the next five minutes? That's a no-brainer: let's get immersed in the futuristic predictions for the world in 2050, and the evolving role of cybersecurity in it. Cyber-immunity will intuitively protect our systems Predicted by: Eugene Kaspersky, CEO, Kaspersky In 2050, digital systems have moved up to a whole new level. They're no longer assistants making life easier for us mere mortals, they've become the basis of civilization – the very framework keeping the world functioning properly. This quantum leap forward has generated new requirements for the reliability and stability of artificial intelligence (AI). Since the romantic era around the turn of the 21st century, cyberattacks are not yet extinct, but they're now only a threat to outliers who reject modern standards of digital immunity. One of the pillars of cyber-immunity is digital intuition, the ability of AI systems to make the right decisions in conditions where the source data is insufficient to make a rational choice. There's no mysticism here: digital intuition is the logical continuation of machine learning. When the number and complexity of related self-learning systems exceeds a certain threshold, the quality of decision-making rises to a level that eludes rational understanding. An intuitive solution results from the superimposition of the experience of a huge number of machine-learning models, much like the result of the calculations of a quantum computer. Digital intuition – with its ability to instantly, and correctly, respond to unknown challenges –has helped build the digital security standards of this new technological era. The robot servants are uprising Predicted by: Vitaly Kamluk, Director, Global Research & Analysis Team, Kaspersky Busy workers rejoice! Help for your home is arriving. A robot servant will cook your meals, do your laundry and clean your apartment. These autonomous systems will be able to carry out many complex tasks using the processing power of a central intelligent system, and in tricky situations, they'll switch to remote technical support managed by real people. There will be mass attempts to hack these helpful robots by labor rights activists and criminals trying to blackmail their owners. Since the servants will all be equipped with cameras, microphones and sensors, they offer a unique viewing platform for home-based espionage. Expect compromises of the manufacturers' infrastructure and the implantation of malicious code in devices with the aim of enacting, en masse, attacks that could be serious. The man(less) mining machine Predicted by: Andrey Nikishin, formerly Future Technologies Project Director, Kaspersky Mining is a fully automated process; people are not needed and former miners regain their health. One robot extracts rock from the soil, the second cleans it, the third guards the perimeter, while the fourth delivers the purified ore to industrial consumers. A hacker who gains access to the system can re-program individual robots so they take a small amount of the platinum ore to an unauthorized place. The guard robots are also hacked, so they're unaware of this theft. The big reveal of dynamic clothes Predicted by Vladislav Biryukov, Head of Consumer Social Media, Kaspersky Dynamic clothing is à la mode. The fabric's characteristics – color, pattern, lighting, transparency, and in advanced models, even the cut and length – can be automatically changed. Some people now wear shirts or dresses with variable transparency levels, which allows them to reveal more at any moment they choose. Few people 'program' their clothes by themselves; most enjoy free fashion patterns or, for the fashionistas, expensive programs from well-known designers. Initially lacking security, the process of getting a smart clothing upgrade has led to the emergence of a new kind of extortion. "Heading to a business meeting, sir? Transfer 10 bitcoins to this account number now, or we'll expose you!". The naked truth in the boardroom. Awkward. Not quite the transparency in business we were hoping to achieve in 2050. A quantum (computing) leap threatens cryptography Predicted by Alexey Malanov Cryptography is widely used in many spheres of online activity. It's no exaggeration to say that the world will experience a huge shock if suddenly everything that's encrypted today is unlocked. How cryptography works: some operations can be easily carried out in one direction, but they're very difficult to reverse. For example, an image can be quickly transformed into a picture puzzle, but to arrange all of the pieces back into the picture takes much longer. Modern public-key cryptography is based on this principle: I know two numbers, I have multiplied them and told everyone the answer. Now everyone can encrypt a message for me using the result of the multiplication, but only I can decipher this using the original multipliers. There are already quantum computers that allow you to quickly solve problems that seem to be circuit-breaking for conventional computers, like how to de-compose a composite number. The only obstacle to the end of the digital world – let's call it 'cryptocalypse' – is that quantum computers can only work with small numbers. But by 2050, quantum computing will allow security services or master criminals to access universal decryption, and they may choose to do bad things with it. For example, if a villain steals your credit card, he or she will immediately know your PIN. The ability to decipher brings with it the opportunity to forge: an ATM informs the bank one thousand dollars are withdrawn, but the villain falsifies the message to say only 10 dollars were taken out. We will need to develop new safety standards – fast. On the bright side, encryption helps with verification so you can be sure you're actually on your real bank's website, not a cleverly cloned fake, when you wire the ransom to keep your business suit from turning into your birthday suit. Phew! One challenge solved.
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