Test automation has become a key competitive advantage that directly impacts product quality and development productivity. Building on its proven expertise in V2X technologies, SAESOL Tech has introduced S2X Tester 2.0, an OpenTAP®-based test automation platform.

S2X Tester 2.0 is a plugin-based platform that supports the entire testing workflow within a single environment—from Test Plan design and equipment control to test execution, result analysis, and report generation. Its greatest strength is its flexibility, enabling seamless application across a wide range of industries, including V2X, drones, defense, telecommunications, and embedded systems.

Now, let’s take a closer look at the key features and newly introduced capabilities of S2X Tester 2.0.

S2X Tester 1.0 Achieved OmniAir OQTE Certification

S2X Tester 2.0 introduces an enhanced Test Plan management system with a newly designed hierarchical structure consisting of Test Cases, Test Steps, and Child Steps. This structure enables users to organize test procedures in a logical sequence while designing even the most complex test scenarios with greater clarity and efficiency.

Within a single Test Case, multiple Test Steps can be defined, and each Test Step can contain multiple Child Steps. This hierarchical approach makes it easy to build sophisticated test workflows while maintaining a clear and intuitive structure.

For example, a “Security Authentication Test” Test Case can include Test Steps such as Certificate Request, Digital Signature Verification, and Message Transmission Validation, with each Test Step further divided into detailed Child Steps to represent individual testing actions.

This hierarchical architecture not only improves the visibility and organization of test scenarios but also simplifies test asset reuse and maintenance, providing greater efficiency for managing large-scale testing projects.

S2X Tester 2.0 introduces Test Step reusability, allowing frequently used Test Steps to be created as shared assets and reused across multiple Test Cases. This enables faster development of test scenarios while ensuring greater consistency throughout the testing process.

By managing tests with reusable Test Steps, the same testing logic can be efficiently applied across multiple Test Cases, improving both test asset management and long-term maintainability.

This capability is particularly valuable for repetitive tasks such as authentication procedures and message verification. As projects grow in scale, organizations can significantly reduce test development time while improving operational efficiency through standardized and reusable test workflows.

S2X Tester 2.0 adopts OpenTAP®, a global open-source test automation framework led by Keysight, as its Core Engine for backend control.

OpenTAP® is a proven test automation framework widely used by global test and measurement companies, including Keysight, in real-world testing environments. It provides world-class stability and reliability for equipment control and test scheduling.

By delegating critical low-level control operations to the OpenTAP® engine, SAESOL Tech ensures high system integrity and reliability. Meanwhile, SAESOL Tech’s proprietary technologies focus on delivering differentiated capabilities in user experience (UI), project management, plugin architecture, and test operation workflows.

Most importantly, as S2X Tester 2.0 is built on the OpenTAP® ecosystem, it can seamlessly utilize or integrate various OpenTAP® Test Steps and Test Case assets developed for Keysight environments. This compatibility with existing OpenTAP®-based test assets significantly enhances test asset reusability and improves overall development productivity.

S2X Tester 2.0 enables profile-based management of DUT and Equipment configurations. Test environments can be saved as Profiles and easily loaded or reused whenever needed, allowing users to configure consistent test environments across various projects.

This capability reduces repetitive setup efforts and enables more efficient test operations.

S2X Tester 2.0 adopts a plugin-based architecture that enables flexible expansion of DUTs (Devices Under Test) and Equipment.

Even when new test instruments or testing environments are introduced, they can be easily integrated and utilized through plugins, allowing the platform to adapt quickly to diverse project requirements.

This extensible architecture also provides long-term flexibility in response to evolving test environments and the adoption of new equipment, enhancing the value of S2X Tester 2.0 as a future-ready test automation platform.

S2X Tester 2.0 has evolved beyond a simple feature upgrade into a next-generation test automation platform that supports the entire testing lifecycle within a single environment—from Test Plan design and equipment control to test execution, result analysis, and test artifact management.

Designed for flexible application across a wide range of industries, including V2X, drones, defense, telecommunications, and embedded systems, S2X Tester 2.0 delivers outstanding stability and scalability through its proven OpenTAP®-based test engine and plugin architecture.

SAESOL Tech will continue to enhance the platform in response to evolving technologies and diverse customer requirements, providing a more efficient, reliable, and intelligent test automation environment.

Experience the new standard of test automation with S2X Tester 2.0 and discover a powerful solution designed to redefine test automation across various industries.

During a meeting with Wall Street analysts after visiting CES 2025 in January, Jensen Huang was asked about the pace of development of early-stage quantum computers and stated, “It will take about 20 to 30 years to reach a useful level,” which led to a significant drop in the stock prices related to quantum computing. 

However, Sundar Pichai, the CEO of Alphabet, made a positive forecast at the World Government Summit held in Dubai on February 12, stating that “Quantum computing will be possible in 5 to 10 years”, overshadowing Jensen Huang’s outlook. 

The ‘Willow Chip’ from Google Quantum AI, announced on December 9, 2024, astonished experts by performing calculations that would take 10 trillion 700 billion years on a supercomputer in just 5 minutes, achieving a breakthrough in solving the random number generation problem, which is crucial for modern security infrastructure, using specific quantum algorithms. Sundar Pichai’s confidence undoubtedly stems from such empirical achievements. 

On January 19, Microsoft also announced the Majorana 1, a quantum chip using topological superconductors. According to Microsoft, Majorana 1 is a ‘topology core-based quantum processing unit’ (QPU) designed to scale up to one million qubits on a single chip, with the first product starting with 8 qubits. 

Topological superconductors implemented with indium arsenide and aluminum are praised for preventing damage to quantum information, and for enabling error detection and correction to be digitized and automatically controlled, bringing commercialization one step closer. The powerful capabilities of quantum computers are now within reach. 

Image: Microsoft Majorana 1 chip 

Source: https://azure.microsoft.com/en-us/blog/quantum/2025/02/19/microsoft-unveils-majorana-1-the-worlds-first-quantum-processor-powered-by-topological-qubits/ 

In this rapidly changing security technology environment, we examined three key technological advancements that the C-ITS and automotive industries must prepare for. 

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C-ITS (Cooperative Intelligent Transport Systems) is a core technology that can dramatically enhance traffic efficiency and safety, but it also faces the challenge of being exposed to various security threats. C-ITS is a complex system where various components such as vehicles, road infrastructure, and central systems are interconnected and exchange information, making it difficult to ensure effective security with traditional perimeter-based security methods. Data tampering, unauthorized access and control, denial-of-service attacks, and privacy violations are major security threats to C-ITS, which not only increase the risk of malfunctions and accidents but can also lead to social disruption and various side effects due to personal information leaks. 

Zero Trust is a security paradigm based on the principle of ‘never trust, always verify,’ which considers all access and communication as security threats. It enhances security through measures such as least privilege access, micro-segmentation, and continuous verification. Applying Zero Trust in the C-ITS environment can overcome the limitations of existing security methods and build a safer and more reliable future transportation system. 

The 5GAA (5G Automotive Association), which includes various global companies from the automotive, information and communication, and electrical and electronic industries, is researching a trust-building model centered on Dynamic Trust Assessment to address internal vehicle security threats, V2X communication vulnerabilities, and road infrastructure attacks. This approach aligns with the principles of zero trust and can further enhance the cybersecurity framework in the C-ITS environment. 

The emergence of generative AI is completely changing the mindset regarding security. Attackers use AI to perpetrate breaches, while companies use AI to defend against such attacks. Since AI serves as both a sword and a shield, it is not possible for one side to benefit exclusively. From a defensive perspective, AI helps strengthen defenses by improving vulnerabilities that had not been previously considered, identifying subtle attacks, and reducing response times. On the other hand, from an offensive perspective, it enables increasingly sophisticated attacks and assists in automatically generating code equipped with new attack techniques. Defenders and attackers are gradually escalating an arms race that will continue until one side becomes exhausted and gives up. 

In relation to automobiles, enhancing the security of autonomous driving assistance systems has emerged as the biggest issue. While AI is used as a core technology in autonomous driving systems, it can also become a target for hacking. In other words, a malicious attacker could manipulate AI algorithms or tamper with data to cause vehicle malfunctions, making it crucial to verify the integrity during the deployment of AI models and to develop technologies that defend AI models from external attacks. 

So, what strategies should be used to enhance AI security? Three main considerations can be made. 

According to Cloudflare’s <Year in Review 2024>(https://radar.cloudflare.com/year-in-review/2024) report, global internet traffic has increased by 17.2%, and due to the rapid response to new technologies, post-quantum encryption has reached 13% of TLS 1.3 secure traffic. This change is driven by the growing need for post-quantum encryption to prepare for quantum computing attacks, as powerful quantum computers like Google’s Willow quantum chip and Microsoft’s Mayonara continue to be developed. https://radar.cloudflare.com/year-in-review/2024 

To this end, both security companies and browser vendors are moving quickly. Google Chrome and Mozilla Firefox have already released versions with post-quantum encryption features that are quantum-resistant, while Apple Safari is also in testing, and security infrastructure companies like Cloudflare are fundamentally enabling post-quantum encryption for their customers. In quantum security, it is essential to examine three major technologies. 

✅ Post-Quantum Cryptography (PQC): The currently widely used public key cryptographic methods (such as RSA, ECC, etc.) have vulnerabilities that could be easily decrypted once quantum computers are developed. Therefore, encryption techniques that are secure against future quantum computer attacks are being researched. This technology can be applied in all areas where current encryption technologies are used, including blockchain, secure communication, data protection, and digital signatures. Following standardization efforts, implementations in various programming languages ​​are emerging (eg, the post-quantum cryptography standards JEP 496/497 in Java, https://www.infoq.com/news/2024/12/java-post-quantum/) https://www.infoq.com/news/2024/12/java-post-quantum/ 

✅ Quantum Key Distribution (QKD):   A technology that securely shares cryptographic keys between two users using the principles of quantum mechanics. Unlike traditional cryptographic methods, QKD is based on physical principles rather than mathematical computational complexity, theoretically providing secure communication that is impossible to eavesdrop. Until observed, it does not have a definite value, and the uncertainty principle, which states that the value is determined at the moment of observation, along with the no-cloning theorem that prevents perfect replication of quantum states, enhances its stability. 

✅Quantum Random Number Generator (QRNG):   True randomness is required to eliminate predictable factors in the encryption process. Traditional methods generate random numbers using deterministic algorithms that rely on unpredictable initial values. In fields where security is critical, there is a need to address situations where such methods do not guarantee perfect randomness. Quantum random number generators can produce truly random numbers by utilizing the uncertainty principle of quantum mechanics and the property of quantum superposition, thereby enhancing security. 

There is a trend of evolving from fixed robots, such as assembly robots or cooking robots, to mobile robots like unmanned vehicles, delivery robots, and combat robots. Therefore, to ensure smooth control of these mobile robots, it is necessary to utilize the mentioned C-ITS infrastructure to exchange information in real-time. Consequently, applying zero trust security to robots is essential. 

Of course, applying zero trust to robots can dramatically enhance security levels, but the characteristics of the robots themselves must not be overlooked. A few additional considerations are summarized as follows. 

✅ Minimizing the impact on robot performance: The application of zero trust security policies may lead to a decrease in robot system performance. It is essential to apply a zero trust architecture and technologies that minimize performance impacts, considering the real-time performance requirements of robots, such as real-time control and high-speed data processing. 

✅ Supporting various robot platforms and operating environments: A flexible and scalable zero trust architecture should be designed, taking into account various manufacturers, diverse functionalities, and different communication methods of robot platforms and operating environments. 

✅  Compliance with Standards and Regulations:  A Zero Trust system must be established in compliance with international standards related to robot security (such as ISO TR 23482-2, IEC 62443, etc.) and domestic regulations. 

✅  Anomaly Detection Based on Robot Abnormal Behavior:  The robot’s behavior patterns, movement paths, and API call patterns must be analyzed using machine learning to detect abnormal behaviors in advance. 

💡 Respond to Next-Generation Security Threats with SAESOL Tech ! 

In this rapidly changing cybersecurity environment, SAESOL Tech has completed preparations to meet advanced security requirements by meticulously establishing an overall security system in anticipation of Zero Trust 2.0 to respond to next-generation security threats. 

In addition, we are conducting research on next-generation encryption technologies and security architectures that closely analyze the latest technological trends in AI-based security and quantum security. Based on this, we actively participate in the establishment of global and industry standards, leading the migration of the C-ITS and V2X security market. 

SAESOL Tech prioritizes the protection of all users’ personal information beyond next-generation mobility security. We will take the lead in creating a safer future and a trustworthy communication environment through continuous technological innovation.