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Creating a Secure, Private and Safe Autonomous Future with Quantum Computing and AI Technologies

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ByteSafe’s CTO Raghavan Chellappan offers commentary on creating a secure, private, and safe autonomous future with quantum computing and AI. This article originally appeared in Insight Jam, an enterprise IT community that enables human conversation on AI.

Quantum computing is changing classical architecture, information processing and security frameworks, and offers a path to address key security, privacy, and safety issues in autonomous systems. Emerging technologies such as generative AI (GenAI), 5G expansion and 6G transitions, Augmented and Virtual Reality (AR/VR), Internet of Things (IoT), Blockchain, and Edge Computing, are proliferating at a fast pace, disrupting and revolutionizing whole industries and fundamentally shifting the digital landscape.

Unlike in earlier innovation cycles, these technologies are accelerating and maturing in parallel.  Such an evolutionary pattern coupled with the increasing intersection between the technologies poses significant threats, vulnerability risks, ethical concerns and regulatory challenges to existing applications and growing connected autonomous systems.

Such complexity makes it harder to manage, secure and safeguard the flow of data across distributed environments (cloud, on-premise or hybrid). It’s worth recognizing that quantum technologies can be used in a variety of ways from information processing to data encryption, and if incorrectly implemented, can even facilitate data breaches. As a result, how quantum approaches are used matters.

One-off, non-integrated or silver bullet solutions will not resolve problems as businesses adopt technological advancements. Instead, the solution set should start with a shift in the mindset of how humans engage and collaborate with autonomous systems securely and safely as they adopt and transition into an agentic-driven digital way of life.

In a human-centric approach, users and enterprises go beyond relying on secure, anonymized connections to proactive enhanced data security and protection based on a decentralized, open security framework.

Key Elements in the Transition to Quantum Computing 

Modern architecture embraces greater levels of autonomy to address industry needs for greater productivity. How enterprises design, develop and deploy software applications is changing—moving towards a greater integration of autonomous systems and converging technologies supporting new methods of architectural design. To understand how this works it’s useful to look at the shift from classical to quantum computing.

It is useful to note that regardless of whether they operate in classical or quantum computing environments, autonomous systems need encryption, security, privacy and safety requirements to ensure data are protected.

Architecture and Information Processing

While classical and quantum computing are based on different architectures and process information differently, they also share some common elements.

Classical computing encodes, processes and stores information in bits. A classical bit uses a base 2 numbering system and can only exclusively be in one of two states, as a ‘0’ or ‘1’ akin to flipping a coin (heads = ‘0’ or tails = ‘1’ or vice versa). These two values exist in 2D or two dimensions only and measurements are deterministic in nature.

Classical computers follow sequential operations (i.e., passing one instruction at a time) by applying Boolean algebraic principles—based on binary variables and logical operations (or logical gates)—to process bits (‘0s’ = Off/Fail and ‘1s’ = On/Pass), and manipulate and transform the information depending on a desired calculation (inputs, processing, outputs) and presenting a string of bits as the output.

Interest in “quantum computation” has grown substantially in recent years. Quantum architecture consists of quantum circuits, quantum bits (Qubits), and quantum gates on which all operations are performed. Quantum computing is based on quantum mechanics (including the principles of superposition and entanglement), so even though qubits still rely on “0s” and “1s” a single qubit can be in one of infinitely many superpositions of |0⟩ and |1⟩ states.

Thus, these values can be visualized in “3D” or three dimensions, and quantum qubit measurements are probabilistic in nature rather than deterministic. Quantum computing, with additional layers required to process information, is consequently more complicated compared to classical computing. This complexity in encoding, processing and storing information in qubits makes quantum information more prone to errors, which in turn reduces stability in quantum systems and makes it harder to manipulate compared to classical information.

It’s worth remembering that while qubits are primarily used in processing information, the output still needs to be presented in terms of the binary ‘0s’ and ‘1s’ of classical computing.

Cryptography and Encryption

The cryptographic algorithm (e.g., symmetric or asymmetric) is one of the most basic controls available to protect sensitive information from unauthorized disclosure in many different environments including autonomous systems through encryption. Cryptography uses mathematical algorithms in the transport layer security (TLS) and secure socket shell environments to transform information into a form that’s not readable by unauthorized individuals yet provides authorized individuals with the ability to transform that information back into readable forms again by using a decryption algorithm.

Classical computing uses traditional encryption techniques—such as Rivest-Shamir-Adleman (RSA), Elliptic Curve Cryptography (ECC), Elliptic-curve Diffie-Hellman (ECDH) algorithm, a key agreement protocol, the Elliptic Curve Digital Signature Algorithm (ECDSA), a variant of the Digital Signature Algorithm (DSA) which uses elliptic curve cryptography proposed by the National Institute of Standards and Technology (NIST), and Advanced Encryption Standard (AES)—that rely on complex mathematical computations to secure communications and resist attacks.

Quantum computing relies on Shor’s factorizing algorithm, which is based on modular arithmetic, quantum parallelism, and quantum Fourier transformations, enabling the cracking of large numbers at quicker, exponential paces. Additionally, many of the traditional cryptographic encryption techniques continue to be relevant even with quantum technologies, however they need to be enhanced to work effectively in quantum environments.

Security, Privacy, Protection, and Safety 

Current centralized architectures, infrastructure and data repositories lack transparency in data collection, suffer from distributed processing methods and storage, demonstrate poor management and governance, have limited safety and protection, minimal data privacy protocols, and lax security controls.

The large, centralized data repositories holding an individual’s personal, sensitive and private records, suffering from these key limitations, are therefore prone to cyberattacks and regular breaches. Organizations rely on public-key cryptography to secure their online transactions and communication, and any compromise of these systems (including autonomous) has far-reaching consequences.

Transitioning from classical computing techniques to quantum computing algorithms and adopting AI technologies, including AI agents or Agentic AI solutions, is fundamentally transforming the way in which software/application systems are designed, built, implemented, integrated and operated across the enterprise.

However, the transition (e.g., classical to quantum, changes in software development practices, and use of AI agents) has also opened the doors to high-profile security breaches and data leakages, where large amounts of confidential and sensitive records have been hacked. These hacks occur because emerging technologies like quantum computing, and the use of Agentic AI and multi-agents are also being used to threaten traditional encryption algorithms and methods.

Despite the use of cybersecurity practices, currently used encryption protocols remain vulnerable to quantum attacks thereby elevating risk, compromising confidentiality and integrity of sensitive information systems, and reducing data privacy, protection, and security.

The impact of emerging technologies is not limited to encryption algorithms but also affects data protection and privacy. While data anonymization and pseudonymization techniques which mask certain pieces of data can provide some level of safety and protection against classical attacks, these techniques may be insufficient against quantum attacks.

Thus, there is an urgent need for post-quantum encryption methods and quantum-resistant cryptography to protect existing systems, as we build and migrate to NextGen autonomous systems.

How to Secure and Protect Data in an Autonomous Future

Data security is fundamental to trusting autonomous systems. The current networking infrastructure has significant security vulnerabilities that have remained unresolved for many years. Quantum computing offers the potential to advance security which is critical for autonomous systems. The development of quantum-resistant cryptography and secure multi-party computation protocols requires significant advances in theoretical computer science and mathematics.

Decentralization

Addressing challenges that come with the ubiquitous use of advanced computing technologies requires a strategic shift away from centralized architecture control models used today—like the border gateway protocol (BGP), the standard interdomain routing protocol used, and the public key infrastructure (PKI), a common security protocol—to an open security architecture which is more comprehensive, operates independently of external authority and is decentralized with governance guardrails embedded to enable speed, reuse, and control.

Decentralization is key to the adoption of quantum computing, AI technology and cryptography because it improves user trust, security, and transparency. With decentralized quantum computing decision making and security control is distributed across the enterprise system, allowing the organization to build resistance to censorship, eliminate single points of failure, enable secure and efficient communication, and minimize data manipulation because no one system entity has exclusive control over it.

A decentralized security framework that modifies the current underlying business processes and architecture and uses encryption, anonymization and tokenization techniques underpinned by standards, offers a viable solution that prioritizes software and system-level optimizations.

Unified Approach to Security

In a quantum environment, classical encryption methods, particularly those based on public-key cryptography, do not fully secure information even when using modern digital security frameworks based on cryptographic protocols. Quantum-resistant protocols with quantum key distribution are required to circumvent breaches and securely transmit sensitive data. For example, cryptographic techniques, like lattice-based cryptography and secure multi-party computation protocols are capable of resisting quantum attacks.

While quantum-resistant protocols offer viable solutions and techniques like lattice-based cryptography offers many advantages, there are several challenges associated with implementing these technologies. One of the main challenges is the need for high-performance computing resources to solve lattice problems efficiently.

Another challenge is the lack of standardization and interoperability between different lattice-based cryptographic systems. Overall, further development is needed especially in the areas of data anonymization and tokenization in autonomous systems to ensure these new solutions operate well to secure and protect data.

To future-proof data security a proactive cybersecurity mindset and unified systemic approach are key in detecting and suppressing the propagation of attacks. What is required is a solution that automates workflows, enhances visibility, protection, and compliance and simplifies security by providing a clear view of data security and overall risk.

Such a solution is seen in the Integrated Decentralized Security Framework (IDSF) which can help organizations identify, assess, and manage data security risks across multiple and distributed environments based on elements like:

Elements of an Integrated Decentralized Security Framework (IDSF)

  • Embracing a human-centered process-oriented approach that both harmonizes and enhances trust.
  • Continuous monitoring and improving data security operations.
  • Implementing strong encryption, masking, and tokenization to protect data at rest and in motion.
  • Establishing a quantum/post-quantum ready foundation to protect data against AI and quantum computer powered threats.
  • Ensuring compliance with strict international data protection regulations, privacy laws, and compliance frameworks (GDPR, CCPA, PCI, HIPAA).
  • Promoting policy-driven data governance.
  • Classifying and categorizing data based on sensitivity and business value, while assessing risks.
  • Applying data protection, including encryption, and secure the metadata
  • Building quantum/post-quantum ready controls to counter future AI and quantum-powered threats.
  • Exploring and implementing advanced modern cryptographic techniques and algorithms such as crypto-agility and perfect secrecy that offer a reactive and proactive approaches respectively to secure information and data in computer systems.

These solutions aim to protect data in a quantum world where AI systems reflect the data on which they are trained, and classical encryption algorithms may no longer be secure. There are several new techniques that are in the developmental phase for securing and protecting data in a quantum world. Adopting a decentralized unified framework pivots away from the centralized models and shifts towards user-centric systems that empower individuals to maintain control over their personal data and take back ownership of information.

A decentralized unified framework extends traditional security, by emphasizing a proactive, comprehensive, and adaptive approach based on core security principles to identify new threats, improve capabilities, and manage emergent risks.

Leveraging Strengths of Quantum and Classical Computing

Quantum computing, with its ability to process vast amounts of information simultaneously, is both process and resource intensive. Qubits in particular are sensitive and face significant obstacles in terms of reliability and scalability. Until the technical challenges inherent in this as yet nascent technology are resolved, it would benefit businesses to implement a hybrid computing model where most enterprises leverage the strong suits of each and split tasks between classical and quantum machines.

Classical computers can handle most mundane tasks/operations through classical algorithms allowing the more complex and highly specialized functions to be delegated to a shared quantum computing infrastructure.

Instead of developing separate security solutions for classical, quantum, and AI-driven systems, given the convergence of all three in this current transition period, it would be beneficial to blend classical, quantum and AI techniques to develop unified approaches to security and protection that leverage the strengths of each computing method while minimizing their weaknesses.

To be prepared to lead in the quantum world and set the stage for a post-quantum era, enterprises must work to bridge the gap to a quantum-enabled future. Over time, businesses should transition to quantum computing as needed for relevant complex functions while continuing to leverage their existing classical computing assets.

Final Thoughts

Data security is in a state of transformation and the future lies in the combination of powerful technologies like quantum computers and artificial intelligence (AI) to create value for organizations. The combination of AI and quantum technology involves the convergence of machine learning (M/L), quantum algorithms and quantum computing to create new solutions.

Businesses must decide what proportion of their enterprise relies on classical vs quantum computing and how to integrate AI technologies into their functions and choose to expand their quantum capabilities accordingly while prioritizing security, privacy, protection and safety.

The proposed integrated decentralized security framework (IDSF) enhancements would provide safer and more secure environments, but still require further research and development, in order to make autonomous systems immune to interception and to enhance their security. Furthermore, a unified decentralized ecosystem approach minimizes the risk of data privacy and security losses and allows the individual to retain greater control over their information.



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Industry Leaders Chart the Future of Mobile Innovation at Galaxy Tech Forum

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At Galaxy Unpacked 2025 on July 9, Samsung Electronics unveiled its latest Galaxy Z series devices and wearables — pushing the boundaries of foldable design and connected wellness experiences. These innovations mark the next step in the company’s mission to deliver meaningful, user-centered technology, with Galaxy AI and digital health emerging as key pillars of the journey ahead.

To explore these themes further, Samsung hosted two panels at the Galaxy Tech Forum on July 10 in Brooklyn. Samsung Newsroom joined industry leaders and executives to examine how ambient intelligence and advanced health technologies are shaping the future of mobile innovation.

(Panel One) The Next Vision of AI: Ambient Intelligence

(From left) Moderator Sabrina Ortiz, Jisun Park, Mindy Brooks and Dr. Vinesh Sukumar

The first panel, “The Next Vision of AI: Ambient Intelligence,” explored how multimodal capabilities are enabling the continued evolution of AI in everyday life — blending into user interactions in ways that feel intuitive, proactive and nearly invisible. Panelists discussed the smartphone’s evolving role, the importance of platform integration and the power of cross-industry collaboration to deliver secure, personalized intelligence at scale.

Jisun Park, Corporate Executive Vice President and Head of Language AI Team, Mobile eXperience (MX) Business at Samsung Electronics, opened the conversation by reflecting on Galaxy AI’s rapid adoption. Since the launch of the Galaxy S25 series in January, more than 70% of users have engaged with Galaxy AI features. He then turned the discussion to the next frontier, ambient intelligence — AI that is deeply personal, predictive and ever-present.

Jisun Park from Samsung Electronics

Samsung sees ambient intelligence as AI that is so seamlessly integrated into daily life it becomes second nature. The company is committed to democratizing Galaxy AI to 400 million devices by the end of 2025.

This vision builds on insights from a yearlong collaboration with London-based research firm Symmetry, which revealed that 60% of users want their phones to anticipate needs without prompts — based on daily habits.

“Some see AI as the start of a ‘post-smartphone’ era, but we see it differently,” said Park. “We’re building a future where your devices don’t just respond — they become smarter to anticipate, see and work quietly in the background to make life feel a little more effortless.”

Mindy Brooks, Vice President of Android Consumer Product and Experience at Google, discussed how multimodal AI is moving beyond reactive response to deeper understanding of user intent across inputs like text, vision and voice. Google’s Gemini is designed to be intelligently aware and anticipatory — tuned to individual preferences and routines for assistance that feels natural.

Mindy Brooks from Google

“Through close collaboration with Samsung, Gemini works seamlessly across its devices and connects with first-party apps to provide helpful and personalized responses,” she said.

Dr. Vinesh Sukumar, Vice President of Product Management at Qualcomm Technologies emphasized that as AI becomes more personalized, there is more information than ever that needs to be protected.

“For us, privacy, performance and personalization go hand in hand — they’re not competing priorities but co-equal standards,” he said.

Dr. Vinesh Sukumar from Qualcomm Technologies

Both Brooks and Dr. Sukumar reinforced the importance of tight integration across platforms and hardware.

“Our work with Samsung prioritizes secure, on-device intelligence so that users know where their data is and who controls it,” said Dr. Sukumar.

The AI panel at Galaxy Tech Forum

Moderator Sabrina Ortiz, senior editor at ZDNET, closed the session with a discussion on AI privacy. Panelists agreed that trust, transparency and user control must underpin the entire AI experience.

“When it comes to building more agentic AI, our priority is to ensure we’re fostering smarter, more personalized and more meaningful assistance across our device ecosystem,” said Brooks.

(Panel Two) The Next Chapter of Health: Scaling Prevention and Connected Care

The second panel, “The Next Chapter of Health: Scaling Prevention and Connected Care,” focused on how technology can bridge the gap between wellness and clinical care — making health insights more connected, proactive and usable for individuals, healthcare providers and digital health solution partners. Panelists explored how the convergence of clinical data, at-home monitoring and AI is reshaping the modern healthcare experience.

(From left) Moderator Dr. Hon Pak, Mike McSherry, Dr. Rasu Shrestha and Jim Pursley

Health data is often siloed across systems, resulting in inefficiencies and gaps in care. Combined with rising rates of chronic illness, an aging population and ongoing clinician shortages, the result is a system under pressure to deliver timely, effective care.

Dr. Hon Pak from Samsung Electronics

“Patients and consumers around the world are asking us to hear them, to know them, to truly understand them,” said moderator Dr. Hon Pak, Senior Vice President and Head of Digital Health Team at Samsung Electronics. “And I believe this is the opportunity we have with Samsung, Xealth and partners like Hinge and Advocate. Together, we are creating a connected ecosystem where healthcare can truly make a difference — not just in the life of a patient, but in the life of a person.”

Samsung is addressing this challenge through technological innovation and its recent acquisition of Xealth, a leading digital health platform with a network of more than 500 hospitals and 70 digital health solution providers. Through Xealth, Samsung plans to connect wearable data and insights from Samsung Health into clinical workflows — delivering a more unified and seamless healthcare experience.

Mike McSherry from Xealth

“This , plus your devices — the watch, the ring — are going to replace the standalone blood pressure monitor, the pulse oximeter, a variety of different devices,” said Mike McSherry, founder and CEO of Xealth. “It’s going to be one packaged solution, and that’s going to simplify care.”

This collaboration is designed to empower hospitals with real-time insights and help prevent chronic conditions through early detection and continuous monitoring with wearable devices.

Dr. Rasu Shrestha from Advocate Health

“The reality is that with all of the challenges that exist in healthcare, it is not any one entity that can heroically go in and save healthcare. It really takes an ecosystem,” said Dr. Rasu Shrestha, Executive Vice President and Chief Innovation & Commercialization Officer at Advocate Health. “That’s part of the reason why I’m so excited about Xealth and Samsung — and partners like us — really coming together to solve for this challenge. Because it is about Samsung enabling it. It’s more of an open ecosystem, a curated ecosystem.”

The panel spotlighted the growing shift from hospital-based care to care at home — and the opportunities enabled by Samsung’s expanding ecosystem of connected devices. Data from wearables, including those equipped with Samsung’s BioActive Sensor technology, can provide high-quality input for AI-driven insights.

Paired with Samsung’s SmartThings connectivity and wide portfolio of smart home devices, the company is uniquely positioned to support remote health monitoring and treatment from home.

AI is expected to play a role in reducing clinician workload by streamlining administrative tasks and surfacing the most relevant insights at the right time. Platforms like Xealth offer users a personalized, friendly interface to access necessary information from one place for a more connected healthcare experience.



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DataBahn.ai Announces New Chief Security and Strategy Officer and Two New Sales Leaders » Dallas Innovates

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DataBahn.ai has appointed Preston Wood as chief security and strategy officer of the Dallas-based provider of a security-native data pipeline platform built for modern enterprise workloads.

Wood brings 25 years of leadership experience in cybersecurity to his new role. He will help drive DataBahn’s mission to transform security data management and enable intelligent automation across global enterprises, the company said.

“I’ve always believed that security and IT teams need the right data, at the right time—enriched with context and real-time analytics—to make smarter, faster decisions,” Wood said in a statement. “DataBahn’s platform is uniquely positioned to solve persistent challenges in data discovery, ingestion, and real-time visibility. I’m excited to join a team so deeply focused on customer success and innovation, and I look forward to helping advance DataBahn’s mission to deliver secure, intelligent, and highly scalable data solutions.”

Wood has served as a three-time chief information security officer and two-time chief technology officer at major financial institutions, including Zions Bancorporation, Bank of the West, and City National Bank. The company said that Wood is known for aligning security and technology strategies with business goals, and he has led the development of robust security frameworks, real-time threat detection programs, and advanced analytics initiatives.

At DataBahn.ai, Wood will partner with engineering and product teams to expand the platform’s strategic vision and deepen customer relationships, the company said.

Wood will lead the development of next-generation solutions, such as intelligent, AI-powered Data Broker workflows, that bring automation, context, and precision to enterprise-scale data orchestration, the company said. DataBahn said that Wood will draw on his dual experience as CISO and CTO in serving a dual role: evangelizing DataBahn’s innovation to enterprise customers while channeling next-generation customer requirements back into the product roadmap.

Sales leadership additions

In addition to Wood, DataBahn.ai said it strengthened its go-to-market capabilities with two key sales leadership appointments.

Payman Faed joins as SVP of sales, West, bringing over 15 years of enterprise cybersecurity sales and leadership experience. He has held senior roles at leading MDR and SIEM providers, including Lumifi and Castra. Faed is recognized for building high-performing teams and scaling partner-first go-to-market strategies, the company said.

At DataBahn, Faed will oversee strategic accounts across the Western U.S., accelerate national expansion, and lead a team of account executives focused on customer value and revenue growth.

Trevor Crompton has been appointed vice president of sales, EMEA. Crompton has more than 30 years in the IT industry—nearly half spent building and leading startup organizations across Europe, the Middle East, and Africa—and he brings deep expertise in helping security professionals gain visibility into complex data environments.

At DataBahn.ai, Crompton will lead the company’s expansion in EMEA, helping customers address growing data complexity while reducing storage costs and simplifying operations.

“With the addition of Preston, Payman, and Trevor, we’re assembling a powerhouse leadership team that combines technical excellence, deep customer empathy, and proven go-to-market execution,” Nanda Santhana, co-founder and CEO of DataBahn.ai, said in a statement. “Their collective experience across security, data management, and global GTM strategy positions us to accelerate our growth and deliver even greater value to enterprises worldwide.”


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R E A D   N E X T

  • Fort Worth-based marketing agency The Starr Conspiracy has officially rebranded as TSC, signaling a new era with fresh leadership. CEO Ashley Bernard is steering the agency toward innovation, AI investment, and cutting-edge marketing strategies, with the rebrand unveiled at the 2024 HR Technology Conference & Exposition.

  • Trinity Christian Academy has named Lisa Wong, a former Raytheon engineer and TCA’s director of technology, as its first chief innovation officer. Wong will lead the integration of cutting-edge technology, foster innovation, and prepare students for future careers.

  • Meghan Baivier is the new CFO of the technology infrastructure company that offers innovative, sustainable, and adaptive scale data centers and build-to-scale solutions for global hyperscale and enterprise customers. Aligned also announced the transition of former CFO Anubhav Raj to Aligned’s new chief investment officer.

  • Kekin Ghelani previously held senior positions at Summit Materials, DuPont de Nemours, Celanese, McKesson, and Honeywell.

  • The investment in Kirkland, Washington-based American Binary marks “a significant step towards fortifying digital security as civilization moves toward the quantum computing era,” the Dallas-based private equity firm said.



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Sheriff T.K. Waters discusses AI facial recognition technology use – Action News Jax

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Sheriff T.K. Waters discusses AI facial recognition technology use  Action News Jax



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