AI - PATECCO GmbH

How to protect digital identities in the era of AI?

Making online transactions increasingly secure, despite the rise in cyberattacks and data theft, has been a growing challenge for our economy since the pandemic. More and more companies feel that their existence is threatened by cyber-attacks. Identity fraud and other online threats are also becoming increasingly sophisticated. According to a recent study, digital identities pose one of the greatest threats to the compromise of IT systems. In the financial sector for example, numerous attacks have recently been successful because employees with privileged access rights have been spied on and digital identities have been stolen through phishing campaigns. Therefore there is an urgent need to better protect our identities from theft and damage in the digital age. After all, our identity is the centrepiece of our online lives. Data leaks, malware or insecure networks and connections are a gateway to identity theft. AI will further accelerate this by generating code that only experienced hackers could create. AI-generated forgeries will become increasingly authentic and easy to use against victims. Identity protection will become one of the most important elements of data security. To better protect themselves in a digitally hostile environment in the future, organisations should push for a digital approach to data protection and risk management. What does identity involve and how we can protect it? Our online identity consists of several layers. On the one hand, there is our personal data that we use to verify ourselves, such as email, place of birth, date of birth and name. But it also includes things like bank details and other tokens – even biometric data. The following basic steps help protect identities from AI-powered risks. These are principles that, if followed, can provide identity protection for individuals, as well as legal obligations that companies must fulfil to mitigate risk and protect both customers and employees: The online identity check at a glance There are various ways in which users can have their identity verified online. This can be done through the use of facial recognition tools, video calls and the presentation of personal information. The use of multiple forms of proof increases the level of trust and security. For example, linking transactions to a one-off secure onboarding can provide a high level of trust – as long as this onboarding is thorough and verified. One example: passports. Official auditors rely on a few measures to verify them, but they trust them because the onboarding process for securing a passport is rigorous. Real-time ID verification: It enables organisations to access and process customer information in seconds. This is particularly useful when checking IDs or financial transactions, as it can ensure that a company has up-to-date information. Verifying the identity of signatories is important to help organisations reduce fraud and money laundering and provide a frictionless experience for signatories, as today a fast and mobile-friendly online process is crucial for customers. Biometrics: These are fingerprint or facial recognition. Biometric technology is the frontrunner among identity verification tools and is used, for example, to unlock smartphones. As biometric technologies have already proven to be beneficial for personal security and ID verification, it stands to reason that they will also provide a secure way to verify electronic signatures in the near future. They also assure companies that no unauthorised person can gain access to personal data. Verification of identity without ID: There are various alternatives for authenticating a signature without the need for ID. If the signatory does not have an ID card to hand, knowledge-based verification can be used. Alternatively, authentication via mobile phone will be used more frequently in future to re-authenticate a known user. This involves sending an access code or text message to a mobile phone number or using the phone itself as an authentication vector and ID. Reducing fraud with AI While AI can increase the scope and scale of cyber risks, it also plays an important role in risk mitigation: in the future, AI will support identification during initial onboarding and all subsequent steps by providing a layer of assurance that looks for evidence of trust or signs of deception. It is important that customers perceive a company’s digital signature process as secure, as a positive and secure customer experience will influence whether they want to continue using the company’s services. There are also many use cases where AI is already being used to detect fraudulent activity – such as detecting relevant signals or patterns of unlikely user behaviour on a platform based on previous experience. However, the ideal scenario is to utilise both humans and AI to increase security and trust. Both can bring risks, but together they help to optimise resilience to cyber-attacks and strengthen identity protection. To summarise, simple changes to processes, a clear understanding of digital identity protection and regular employee training on cyber security and data protection can often lead to significant improvements in corporate security.

The Future of Cloud Computing: Top Trends to Watch in 2024

Uncategorized / Von Ina Nikolova

As we delve deeper into the digital age, cloud computing continues to evolve at a rapid pace, reshaping the landscape of technology and business operations. With each passing year, new advancements and innovations emerge, driving the transformation of how we store, process, and manage data. In 2024, the realm of cloud computing stands on the cusp of groundbreaking developments that promise to redefine the way organizations leverage technology to streamline operations, enhance agility, and drive innovation. In this exploration of the future of cloud computing, we delve into the top trends poised to shape the industry in 2024 and beyond, offering insights into the potential impact and opportunities that lie ahead. From hybrid cloud architectures to AI-driven automation and security advancements, the journey into the future of cloud computing promises to be both exciting and transformative. Trend 1: Multicloud orchestration for complex cloud environments in companies A multicloud orchestrator harmonises server workloads, storage capacities and virtual machines, enabling companies to distribute workloads efficiently, optimise the use of resources and reduce costs. By distributing capacities across different clouds, companies can also increase resilience and thus their reliability and performance. A multicloud orchestrator can also help to streamline automated tasks in a workflow and ensure that they have the required access or authorisation to execute a workload. Overall, a multicloud orchestrator allows companies to maximise the benefits of different cloud platforms, adhere to compliance policies and security protocols and maintain an overview of resource utilisation and usage in a multicloud architecture. In view of the ever-increasing demand for greater efficiency, reliability, security and lower costs, multicloud orchestration will play a key role for companies in the future. Trend 2: Increasing cloud automation In the future, companies will increasingly rely on cloud automation to make standardised business processes more efficient: This automation extends across a variety of software tools and software-based methods. With their support, companies can counter the shortage of IT specialists, reduce the workload of IT teams and also minimise human error in the management of cloud services. By automating the scaling, resource management and provisioning of workloads in the cloud, organisations can not only operate more efficiently, but also reduce costs and accelerate time to market for new products. It is important to emphasise that cloud automation is not an integral part of a particular cloud solution that companies can simply add on. Rather, these are measures that should be implemented by companies. To fully utilise the benefits of cloud automation, it is therefore crucial that companies automate their existing IT with cloud technologies now, replace existing applications with cloud-native developments and develop modern API sets and company-specific DevOps principles. Among other things, these measures make a significant contribution to the standardisation of processes and security measures and enable companies to successfully overcome various challenges in dynamic and complex cloud environments in the future. Trend 3: Optimising cloud infrastructure for maximum performance The optimisation of existing cloud infrastructure, applications and services is becoming increasingly important in view of the continuous financial and time expenditure for the management, expansion and scaling of resources and cloud capacities. A future-oriented cloud and data management strategy will be crucial for companies of all sizes and in all industries in order to rationalise capacities, use existing resources more efficiently and avoid shadow IT. Increased implementation of advanced cost monitoring and analysis tools will play a key role in reducing costs. The regular adjustment of security configurations enables companies to continuously adapt their cloud environment to industry-specific compliance requirements. The trend towards cloud optimisation as a continuous process helps companies to exploit the full range of cloud benefits and increase their overall performance while optimising costs and resources for a sustainable future. Trend 4: Increasing use of observability tools Hybrid multi-cloud systems are highly interoperable, but also susceptible to additional vulnerabilities, particularly cybersecurity risks via third-party or fourth-party providers. Companies should therefore increasingly move towards cloud observability, which goes beyond mere monitoring. Observability tools use automated monitoring systems to identify the causes of problems and anomalies, create root cause analyses and provide predictive insights. This in-depth analysis is based on logging data, metrics and traces that provide a comprehensive understanding of system interactions. A combination of monitoring and observability is a proactive and effective strategy for troubleshooting and optimisation and will become imperative for businesses, especially in the face of increasingly sophisticated, AI-driven cyberattacks. As public cloud services share computing services from different customers, highly regulated companies in particular will therefore increasingly opt for a private cloud, which they can control more easily and with which they can comply with local industry and government regulations and compliance requirements. Trend 5: Private Cloud Private cloud environments can be tailored specifically to company’s needs, providing customised scalability, effectiveness and more reliable performance. In the long term, the use of private clouds therefore often leads to lower total cost of ownership – also because companies only pay for the infrastructure they use. A private cloud therefore combines many of the benefits of cloud computing with the control and security of an on-premise infrastructure, which in some markets will be crucial for companies to achieve a target-oriented IT and cloud architecture. The cloud at a turning point With the increased use of AI, edge computing and the development of even more powerful cloud platforms, the cloud technologies of tomorrow will not only drive digital transformation, but also herald an era of intelligent, autonomous and highly adaptive IT landscapes. For companies, the cloud must therefore be a business case that goes beyond purely technical issues. System integrators can help to develop a suitable, efficient cloud strategy and support companies in not being left behind in the new era of cloud technologies.

How Artificial Intelligence Helps Minimizing Cyber Risks

Uncategorized / Von Ina Nikolova

The digital age has opened up numerous opportunities for us, but at the same time we are exposed to entirely new cyber threats. Never before we have been as connected as we are today – across all sectors and areas of life, in industry, business and society. Especially through the Internet of Things and artificial intelligence, processes are becoming more and more automated and optimized. The challenge for cybersecurity is that every exchange of data must be secured and protected from unauthorized access. Furthermore, cybercriminals are constantly looking for ways to compromise networks and steal sensitive data. These techniques are becoming increasingly advanced and can be difficult to detect by humans or traditional defense solutions. For this reason, organizations are looking to AI techniques to strengthen their cybersecurity defense plan. Artificial intelligence in cybersecurity can help companies understand and defend against these threats. How can companies protect themselves against cyber risks? As already mentioned, the application of AI has significantly impacted people’s lives. We now have machines that can drive cars, understand verbal commands, distinguish images, and play games. This is the reason why AI and machine learning have become indispensable to information security, as these technologies are able to quickly analyze millions of data sets and detect a wide range of cyber threats – from malware threats to phishing attacks, ransomware and zero-day vulnerabilities. These technologies are constantly learning, using data from past cyberattacks to identify potential threats. Regarding IT security, companies must ensure that they develop and operate a holistic security concept. In addition to using the appropriate protection products such as firewalls, virus protection or backups, this also includes active management of the IT components. All network components must not only be permanently patched and updated, but also continuously monitored. This ensures that security gaps are detected as quickly as possible. IT monitoring tools can be used not only to continuously monitor networks, servers, applications and other IT components to ensure that they are functioning properly, but to measure the performance of IT systems and detect security incidents, as well. Active monitoring is usually difficult for companies to implement, which is why support from a managed service provider is advisable. AI for cybersecurity can help you detect threats masquerading as normal traffic, and can process and analyze a large amount of data more thoroughly and in less time. A managed service is responsible for the provision and management of a company’s IT infrastructure. In doing so, we ensure that the customer’s IT infrastructure is always available and functional. Integrated services such as update management and monitoring, significantly increase the IT security. Of course the MSP use special software and AI-supported tools to ensure that potential attackers do not take advantage of artificial intelligence. Proper vulnerability management is the best way to secure an organization’s network. As mentioned earlier, a lot of traffic flows through an organization’s network, and it is imperative to detect, identify, and protect that traffic from malicious access. Unlike human security personnel, AI can quickly learn network behavior to identify vulnerabilities in the system, allowing organizations to focus on ways to mitigate those risks. In this way, vulnerability management can be improved and the enterprise can secure its network systems in a timely manner. Given the speed at which cyber threats evolve, it’s a fact that traditional rules-based security systems can’t keep up. This is where AI systems come into play. AI technologies are equipped with advanced algorithms that detect malware activity, perform pattern recognition and identify anomalous behavior before the system is compromised. Machine learning algorithms can learn from historical data and behavior patterns to identify new and emerging threats, including malware, ransomware, and phishing attacks. AI systems can help identify your IT inventory, a documented record of all tangible and intangible assets. Cybercriminals are always trying to target these assets. Using AI in cybersecurity, you can predict how and when a cyberattack will occur and plan accordingly to allocate resources to the most vulnerable areas. One of the key benefits of incident response automation is its ability to significantly reduce the time it takes to detect, respond to security threats and remediate security incidents. AI and ML-powered tools can monitor network traffic, user behavior, and system logs to detect unusual activities that may indicate a cyberattack. This allows organizations to identify potential threats much more quickly than would be possible using manual methods, enabling them to take action before any significant damage is done. Cyberattacks are becoming more advanced, and cybercriminals are finding more creative ways to carry out their evil plans. That’s why companies are turning to AI to strengthen their defenses and mitigate cyber risks. AI offers so many cybersecurity benefits, including vulnerability management, risk prediction, threat detection, and network traffic monitoring. We hope this article has given you some insight into the use of AI in cybersecurity.