Scientists at the Institute of Nano Science and Technology (INST) have created a novel ink designed to combat counterfeiting. This innovative ink is aimed at preventing the duplication of currency, certificates, branded goods, and medicines. The development comes at a time when counterfeiting is on the rise globally, posing a significant threat to economies and businesses.
The team of scientists focused on rare earth ions with luminescent properties, known for their characteristic emissions of bismuth, a chemical element. Utilizing these properties, they synthesized a first-of-its-kind security ink based on luminescent nanomaterials with rare earth doping. This ink exhibits excitation-dependent luminescence, meaning it gives visible emission under both ultraviolet and near-infrared light.
The new ink offers enhanced security features through its ability to display different colors under various light wavelengths. Specifically, the ink appears vibrant blue under 365 nm light, pink under 395 nm light, and orange-red under 980 nm near-infrared (NIR) light. It remains effective under a range of light, temperature, and humidity conditions, making it a robust solution for security purposes.
The scientists used a simple co-precipitation method to synthesize the luminescent nanomaterial at 120 degrees Celsius. The nanomaterials were then dispersed into commercially available PVC ink. The mixture was used to create patterns and letters through a screen-printing technique. When the printed patterns are exposed to different wavelengths of light, they show the desired color changes, proving the effectiveness of the ink.
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The team also enhanced the encryption and decryption capabilities of the ink by combining rare earth ions with well-known luminescent properties and bismuth with characteristic emissions. This improved its security potential, making it a powerful tool against counterfeiting.
The luminescent ink made from these nanomaterials can also be applied to fake-proof various items, including currency, certificates, medicines, and branded products. This allows both consumers and manufacturers to easily verify the authenticity of their items, providing a simple yet powerful tool to detect counterfeits.
In addition to its security applications, the ink also has potential uses in other areas. For example, it could be used in the production of high-contrast bioimaging nanoprobes, which are used in medical imaging to visualize biological processes at the cellular and molecular level. The ink’s luminescent properties could enhance the contrast and clarity of these images, potentially improving diagnostic accuracy.
The development of this ink also has implications for the recovery of rare-earth metals. These metals are critical to the high-tech society we live in, being an essential component of mobile phones, computers, and many other everyday devices. However, increasing demand and limited global supply mean we must urgently find a way to recover these metals efficiently from discarded products. The use of environmentally friendly chemicals to recover rare-earth metals, as demonstrated in the production of this ink, could be a step in the right direction.
I’ve been using Samsung’s latest Galaxy Tab S10 Ultra 5G, a mean machine that’s a giant slab of metal and glass beautifully fused together demonstrating Samsung’s engineering prowess. It’s been two weeks with this bad boy and it has been put through various tests and trials to assess its use-case, but more importantly, if it lives up to the hype.
Samsung launched the Galaxy Tab S10 Ultra a month ago, carrying a premium price tag of Rs. 1,08,999 for the base model and it goes as high as Rs 1,33,999. You get to pick a Wi-Fi model or 5G variant with 12GB+256GB or 12GB+512GB configurations. And courtesy of Samsung, we got the 12GB+256GB 5G model in Moonstone Gray for testing. It’s priced at Rs 1,22,999. Let’s see what this machine is truly made of.
Unboxing: Samsung continues the minimalistic, eco-friendly packaging for the Galaxy Tab S10 Ultra, which means no plastic and no adapter. You get the tablet, an S Pen, a USB Type-C data cable and an eject PIN. Watch the unboxing video below:
Design
Samsung Galaxy Tab S10 Ultra’s 14.6-inch Dynamic AMOLED 2X display is the highlight of the design, framed by ultra-slim bezels that give it a sleek and modern look. At just over 5mm in thickness, this tablet strikes a balance between size and portability, though its substantial 700g weight and wide frame may not suit for one-handed use.
Samsung Galaxy Tab S10 Ultra reviewIBT
Samsung uses Armor Aluminum in construction, which adds durability, and the IP68 rating means it’s water- and dust-resistant—ideal for users on the go. Despite the durability, I’d advise using a case to add a bit of thickness as it would get easier to carry it around or even lifting it without efforts when placed on a tabletop.
The lock/power and volume buttons are placed on the top when held horizontally. This positioning is Samsung’s subtle way of pushing users to use it this way, which makes sense as most tasks are best handled in that orientation. Be it gaming or consuming multimedia, the speakers are positioned strategically to give you the best audio output. Even the magnetic connectors are at the bottom to connect your keyboard case. Interestingly, the right way of holding the tablet vertically is by putting that camera notch to the right and make sure the Type-C port is at the bottom. Wonder why? Well, there’s a fingerprint scanner placed at the bottom when held vertically, but it goes on the right in the horizontal position.
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Samsung Galaxy Tab S10 Ultra reviewIBT
Samsung Galaxy Tab S10 Ultra reviewIBT
On the rear, there are dual cameras sitting individually and along the same line you’ll find the magnetic holder for your S-Pen and Samsung’s logo. The antenna lines do not disrupt the tablet’s aesthetics in anyway.
The tablet comes in Moonstorm Gray and Platinum Silver, and we got the former, exudes a premium feel and look.
Display
The display quality on the Galaxy Tab S10 Ultra is exceptional and my favourite part of the tablet. Complete with a 2960 x 1848 resolution and vibrant colors typical of AMOLED screens. It’s a dream device for media consumption, gaming, and creative tasks.
Samsung Galaxy Tab S10 Ultra reviewIBT
One standout feature is the anti-reflective coating, a blessing for anyone using the tablet in bright environments. Using the tablet outdoors on a bright sunny Sunday was effortless. Additionally, the tablet also gets HDR10+ support for that rich contrast and depth in compatible content.
If you’re after a really good tablet to consume multimedia, the Tab S10 Ultra is the ultimate choice. Even gamers and artists will find this display to be remarkable. So that’s the target audience for the Tab S10 Ultra.
Performance
Under the hood, the Galaxy Tab S10 Ultra packs the MediaTek Dimensity 9300 Plus chipset with 12GB of RAM, and this setup ensured smooth performance while gaming, multitasking, or handling intensive applications. Having used the tablet daily, there were no hiccups whatsoever. It handled apps and multi-tasking with ease. Running graphics-intense games wasn’t too hard on the chipset as well. The positioning of the fingerprint scanner may be a bit odd, but it works efficiently. I’d rather have it on the side panel, but given the large size of this tablet, locating it would be a problem. So, Samsung did the right thing.
Samsung Galaxy Tab S10 Ultra reviewIBT
The tablet comes with generous storage options, starting from 256GB up to 1TB, with a microSD card slot allowing for up to an extra 1.5TB of storage. Samsung sent us the 512GB variant, and that’s a lot of space to fill during the review period. But the best part of this tablet is it came with 5G compatibility, so if you have a SIM in, you’ll be connected on the go. The ease of attending con-calls, continuing online projects and editing a copy on CMS was all seamless.
Samsung Galaxy Tab S10 Ultra reviewIBT
To make sure the tablet is designed to handle all tasks without breaking a sweat, Samsung’s advanced cooling system ensures cooling during extended use. That sizable vapor chamber on that massive tablet prevented overheating at all times.
Samsung Galaxy Tab S10 Ultra reviewIBT
S-Pen
The S Pen is a standout feature on the Galaxy Tab S10 Ultra, which attaches magnetically to the back of the tablet for wireless charging. After using it for various tasks, doodling and all, it’s clearly highly responsive, making it ideal for note-taking, sketching, and more.
Samsung Galaxy Tab S10 Ultra reviewIBT
The low latency and pressure sensitivity of this S-Pen makes all the difference, even professionals will agree. As usual, there is the Air Command menu to quickly access features like Smart Select and Screen Write.
Samsung Galaxy Tab S10 Ultra reviewIBT
Software
Samsung’s One UI 6.1 over Android 14 is super clean and intuitive with plenty of customizable options. Yes, there are some pre-loaded Samsung apps that serve as an alternative to Google’s suite, but they have their own value. More importantly, the entire AI suite has been retained, and it makes more sense on this tablet than on a phone, especially that drawing assist feature. There’s just so much you can do with Galaxy AI on this massive screen.
Samsung Galaxy Tab S10 Ultra reviewIBT
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Samsung Galaxy Tab S10 Ultra reviewIBT
Samsung Galaxy Tab S10 Ultra reviewIBT
Samsung Galaxy Tab S10 Ultra reviewIBT
One UI’s multitasking capabilities truly shine on the S10 Ultra, with support for split-screen mode that allows up to three apps at once. The Samsung DeX mode takes things a step further, transforming the tablet into a laptop-like setup, complete with taskbars and resizable windows when paired with a keyboard cover, which is sold separately.
Battery
The 11,200mAh battery inside the Galaxy Tab S10 Ultra is a strong USP. It lasts really long if the tablet is used like a tablet. But if you’re spending all day on the tablet, it will easily surpass your daily needs with some juice left for the next day as well. In our tests, if offered around 8 to 9 hours of screen-on time in mixed-use scenarios.
But that massive battery is no match for the 45W fast-charging capability. It takes about two hours to fully charge the tablet, which is acceptable for a device of this size.
Cameras
This tablet gets two cameras on the back and two on the front, which is already an upgrade for a tablet. With that 13MP wide and 8MP ultra-wide lenses on the back, you can actually take photos that aren’t tablet quality. Of course, it is most suitable for document scanning and works well in low light as well.
Samsung Galaxy Tab S10 Ultra reviewIBT
The front cameras work perfectly for video-conferencing, offering clear imagery. It can be better than your laptop as well. Even when I wasn’t on the move, I chose taking con-calls on the Tab S10 Ultra, which is quite a complement.
Verdict
Samsung Galaxy Tab S10 Ultra reviewIBT
Samsung Galaxy Tab S10 Ultra is an impressive piece of tech, with a design and performance that rivals many laptops. It has a beautiful display, powerful chipset, advanced S Pen features, and versatile software, which makes it an excellent choice for productivity and entertainment.
The sleek design looks very premium, but it may not be the most ideal device for prolonged one-handed use. However, if you’re looking for a high-end tablet, the Galaxy Tab S10 Ultra checks all the right boxes.
India is on the brink of a significant shift in its automobile sector, with major conglomerates Tata and JSW groups planning to invest over $30 billion in the electric vehicle (EV) sector over the next decade. This move comes in response to the Indian government’s push for higher EV production and greater localisation of supply chains, which are key to achieving the target of 30 per cent EV penetration by 2030.
The report by S&P Global Ratings estimates that about $10 billion of this investment will be in South and Southeast Asia (SSEA). As the world’s most populous country, India’s vast market potential is attracting substantial EV-related investment. The adoption of EVs in India is expected to progress with model launches that bring prices more in line with internal combustion engine (ICE) models, and with the improvement of charging infrastructure.
The Indian government recently launched the PM Electric Drive Revolution in Innovative Vehicle Enhancement (PM E-DRIVE) scheme, with a financial outlay of Rs 10,900 crore over two years. This scheme is expected to play a pivotal role in accelerating EV adoption and building critical charging infrastructure nationwide, contributing to a cleaner and more sustainable future.
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The transition from ICE in India will initially be more about a shift to alternate fuels rather than pure electrification. Government policies on imports and foreign investment will continue to play a critical role in India’s vehicle electrification.
Hyundai Motor Co. (HMC) and Kia, which combined rank as the second-largest carmaker in India, are also planning to invest in local EV production. Hyundai plans to launch its first fully electric model made in India in January 2025. The company recently completed an initial public offering in India, and part of the proceeds will be used to further their growth and improve its product offerings in the Indian market.
Tata Motors, part of the Tata group, has announced plans to invest about $1 billion in a new EV plant in the south Indian state of Tamil Nadu. Its parent entity, Tata Sons Pte. Ltd., has also announced an investment in a lithium-ion battery plant in the northwestern state of Gujarat, with an initial capacity of 20 gigawatt hours. This plant will support further development of the EV supply chain in the region.
The report estimates that rated carmakers will be spending more than $20 billion building electric vehicle (EV) production in South and Southeast Asia for the next few years. This massive investment in the EV sector by major Indian conglomerates is a clear indication of the country’s commitment to sustainable mobility and the government’s push for a greener future.
In the growing digital landscape, Harish Kumar Reddy Kommera explores the impact of artificial intelligence (AI) on human resources (HR) management in his latest work. This article delves into how AI is reshaping HR practices, enhancing efficiencies, and driving data-informed decision-making across various HR functions.
Recruitment and Hiring: Faster and Smarter
AI is transforming recruitment by streamlining talent searches and reducing time-to-hire. Automated resume screening quickly analyzes numerous applications to identify top candidates, while machine learning predicts potential based on past data and natural language processing goes beyond simple keyword matching. AI-driven tools also automate interview scheduling and reminders, cutting administrative tasks and freeing HR to focus on strategic activities. While AI boosts efficiency, human judgment remains essential to ensure fair and empathetic hiring.
Onboarding: Personalizing the New Hire Experience
AI has improved onboarding by delivering personalized training programs tailored to roles and learning preferences, creating a more adaptive experience. It customizes training based on job needs and recommends cultural integration activities. AI-powered virtual assistants enhance onboarding with 24/7 support, task automation, and better information access. This approach accelerates integration, boosts productivity, and increases retention, but balancing AI efficiency with human relationship-building is crucial for success.
Performance Management: Data-Driven and Continuous
AI is transforming performance management by replacing traditional annual reviews with real-time feedback systems that track productivity, analyze trends, and recommend personalized development plans. Its ability to predict performance issues and suggest proactive solutions gives organizations a strategic edge in talent management. By relying on objective data and detecting inconsistencies, AI helps reduce bias, making evaluations more consistent and fair while fostering a culture of continuous improvement. However, human interpretation and empathy remain essential for effectively managing individual growth.
Enhancing Employee Engagement Through Insights
AI provides valuable insights into employee engagement by using sentiment analysis to gauge morale, satisfaction, and productivity, identifying trends across data sources for proactive interventions. This continuous monitoring outperforms traditional annual surveys, enabling timely improvements to workplace culture. It also supports personalized employee development by identifying skill gaps and recommending tailored learning resources, enhancing engagement by aligning career growth with individual aspirations and organizational goals. However, meaningful human interaction remains essential for fostering strong relationships.
Automating Administrative Tasks: The Efficiency Advantage
AI is transforming routine HR tasks like payroll, benefits administration, and policy management by automating processes and enabling real-time management with minimal human intervention. Its ability to detect anomalies enhances accuracy and reduces errors, while automation in drafting and refining policies eases the administrative load. This shift allows HR teams to focus on strategic projects, though human oversight remains crucial for handling complex scenarios and ensuring regulatory compliance.
Proactive Workforce Planning with Predictive Analytics
AI-powered predictive analytics is transforming workforce planning by integrating data from diverse sources to forecast human capital needs, enabling organizations to model business scenarios, predict skill shortages, and proactively plan hiring and training. It also aids in managing talent retention through attrition prediction by identifying at-risk employees. This data-driven approach supports more strategic decision-making, ensuring organizations are prepared for changing business landscapes. However, combining AI insights with human expertise is essential for developing comprehensive workforce strategies.
Harish Kumar Reddy Kommera concludes that the future of HR lies in balancing AI-driven efficiency with human-centered management. While AI enhances HR by automating tasks, offering data-driven insights, and enabling strategic decision-making, it should augment rather than replace human capabilities. Organizations must ensure responsible AI use, address ethical concerns, and equip HR professionals to collaborate with AI. By combining AI’s strengths with human expertise, companies can create a more efficient, fair, and engaging workplace, providing a roadmap for harnessing AI’s potential while preserving the essential human touch.
Artificial Intelligence (AI) is revolutionizing healthcare, particularly in diagnostics, by augmenting the skills of medical professionals rather than replacing them. Rajesh Basa‘s work delves into the evolving role of AI in healthcare diagnostics, emphasizing its potential to significantly improve accuracy and patient outcomes while tackling pressing challenges like data privacy and ethical considerations. This article highlights key innovations, technologies, and future directions shaping AI’s integration into medical diagnostics.
Enhancing Diagnostic Accuracy with AI
AI’s role in healthcare diagnostics is rapidly growing, with the market projected to reach $187.95 billion by 2030. AI systems are achieving notable success in medical imaging, often matching or surpassing human experts in detecting diseases. For instance, AI has shown high sensitivity in identifying lung nodules from CT scans and excels in detecting brain hemorrhages, helping to reduce diagnostic delays and errors. By processing large datasets, such as patient records and medical images, AI detects subtle patterns missed by humans, enabling more precise and timely diagnoses. This synergy enhances diagnostic accuracy and improves patient care.
Key Technologies Driving AI in Diagnostics
Several advanced technologies drive AI’s progress in healthcare diagnostics: Natural Language Processing (NLP) interprets clinical notes and records with 90% accuracy, extracting crucial information for decision-making. Computer vision rapidly analyzes vast numbers of medical images, like X-rays and MRIs, achieving 97% sensitivity in detecting conditions such as pneumonia. Deep learning enhances pattern recognition, diagnosing ailments like diabetic retinopathy with 97% accuracy. These evolving technologies continually push the limits of diagnostic precision.
Addressing Challenges in AI Integration AI’s promise in healthcare comes with challenges that must be addressed:
Data Privacy and Security: AI needs access to sensitive patient data, requiring strong protections under regulations like HIPAA and GDPR.
Ethical Considerations: AI’s role in decision-making raises concerns about accountability and bias, highlighting the need for transparency and guidelines.
Workflow Integration: AI tools must complement existing healthcare processes seamlessly.
Training: Continuous education is essential to help medical staff effectively use AI-assisted diagnostics.
Innovations in Medical Imaging
AI’s impact on medical imaging is significant, with advanced techniques like Convolutional Neural Networks (CNNs) and Generative Adversarial Networks (GANs) transforming image analysis. CNNs have shown greater accuracy than radiologists in detecting conditions such as brain tumors, while GANs generate synthetic images to enhance training datasets. Additionally, AI models using attention mechanisms improve the localization of abnormalities, making diagnostics more precise. Federated learning, which trains AI on decentralized data without compromising privacy, further boosts accuracy and robustness in medical imaging.
The Path Forward: Future Directions Looking ahead, AI’s role in healthcare will likely expand in several transformative ways:
Personalized Medicine: AI-driven genomic analysis holds the potential to tailor treatment plans to individual patients, improving outcomes by predicting responses to therapies with high accuracy.
Continuous Learning Systems: AI models capable of continuous learning will adapt to new medical knowledge over time, maintaining high levels of diagnostic performance even as clinical practices evolve.
Transparent AI Systems: Increasing the transparency of AI decisions through explainable AI techniques will help build trust among healthcare professionals and patients, encouraging the widespread adoption of AI tools.
As AI continues to evolve, balancing technological advancement with ethical considerations will be crucial in ensuring equitable and responsible implementation. By addressing these challenges and leveraging AI’s strengths, healthcare can move closer to a future where diagnostic errors are minimized, and patient care is significantly enhanced.
In conclusion, Rajesh Basa’s insights into the integration of AI in healthcare underscore the transformative potential of human-AI collaboration in diagnostics. As AI technologies advance, ongoing research and collaboration across the healthcare ecosystem will be essential in harnessing AI’s full potential to improve patient outcomes and streamline medical practices.
A recent study published in international journal ‘Frontiers in Medical Technology’ has highlighted the impact of AI-powered early warning system (EWS) that could predict patient health deterioration up to 16 hours in advance, thereby providing healthcare professionals with a critical window to intervene early and potentially save lives.
Representative photo courtesy: Pixabay/geralt
One of the largest observational studies of its kind in Indian tertiary care, the study was conducted at King George’s Medical University (KGMU), Lucknow. The research team studied the impact using health AI startup Dozee’s AI-Powered Remote Patient Monitoring and Early Warning System.
In an event organised on Friday, October 25, a team from KGMU and Dozee’s clinical research team presented the key findings of the study and its implications.
Dr Himanshu Dandu, Professor in the Department of Medicine at KGMU, emphasised the technology’s potential to enhance critical care in resource-constrained environments.
“This system enables early detection and continuous patient monitoring, providing a scalable and affordable solution tailored to the demands of healthcare systems facing heavy patient loads. The ability to detect signs of patient health deterioration can significantly improve their survival rates,” Dr Dandu said.
In a nation with 2 million hospital beds, where approximately 1.9 million patients in general wards rely on manual spot checks for monitoring, Dozee’s AI-powered EWS has the potential to transform care across 95 percent of hospital capacity, delivering life-saving continuous monitoring that ensures world-class healthcare at a fraction of the cost of ICU services, said Gaurav Parchani, CTO & co-founder of Dozee.
According to him, this early detection holds the potential to save 21 lakh lives annually and reduce healthcare costs by Rs 6,400 crore.
The study monitored over 700 patients across 85,000 hours.
In the rapidly evolving field of artificial intelligence, constant innovation is redefining the limits of technology. Subash Patel, a leading expert in model optimization, introduces an in-depth analysis of Low-Rank Adaptation (LoRa), a cutting-edge technique poised to transform deep learning model optimization. LoRa offers a novel approach to fine-tuning large models, particularly in resource-constrained environments, by significantly reducing the number of trainable parameters without sacrificing performance. This breakthrough has the potential to make advanced AI models more efficient and widely deployable.
Optimizing Models for Efficiency
Deep learning models are known for their immense size and complexity, often comprising millions or even billions of parameters, which require significant computational resources to train and deploy, especially in real-world scenarios such as mobile devices or edge computing platforms. LoRa addresses these challenges by introducing an innovative approach that reduces the number of trainable parameters while maintaining model performance. While traditional optimization techniques like pruning and quantization have been used to mitigate excessive memory usage and high computational costs, they come with trade-offs that can affect performance. LoRa, by leveraging low-rank matrix factorization, reduces model size with minimal compromise on accuracy, offering a solution that preserves the model’s original structure.
Understanding Low-Rank Adaptation
At its core, LoRa works by decomposing large neural network weight matrices into smaller matrices, significantly reducing the number of parameters. For example, in the case of the BERT-large model—a widely used natural language processing (NLP) architecture—LoRa can achieve a 99.5% reduction in trainable parameters without sacrificing performance. This is particularly valuable for fine-tuning models in task-specific applications, where maintaining performance while reducing computational overhead is critical. The low-rank factorization technique is especially useful in models where memory and computational power are limited, as it optimizes models without altering their architecture, facilitating deployment on devices like smartphones or in real-time applications such as speech recognition or autonomous driving systems.
LoRa in Action: Enhancing Real-World Applications
LoRa’s impact extends across multiple domains, including NLP, computer vision, and speech recognition. In NLP, where models like GPT and BERT are prominent, LoRa enables fine-tuning for specific language tasks with far fewer parameters, allowing faster and more efficient model deployment, especially in scenarios involving low-resource languages or domain-specific content. In computer vision, LoRa has shown promise in compressing convolutional neural networks (CNNs) for image classification, with fully connected layers—often consuming a significant portion of model parameters—benefiting the most from its low-rank factorization, achieving high compression without sacrificing accuracy. Similarly, in speech recognition, LoRa has proven effective in compressing recurrent neural networks (RNNs) and long short-term memory (LSTM) models, enabling faster inference times and improved accuracy, making these systems more accessible for real-world applications.
Benefits and Trade-offs of Low-Rank Adaptation
LoRa excels by reducing computational load while preserving model performance, making it highly efficient for fine-tuning and deploying models across a wide range of devices and applications. By minimizing the number of trainable parameters, LoRa improves inference speed and reduces memory usage, making it ideal for resource-constrained environments. Unlike pruning, which can modify a model’s structure, LoRa retains the architecture, ensuring easier integration and interpretability. However, LoRa presents challenges, including increased training complexity, as hyperparameters require careful tuning for optimal results. Additionally, aggressive parameter reduction may lead to accuracy loss in some tasks, and determining the ideal rank for each layer demands empirical tuning and precise adjustments.
In conclusion, Subash Patel’s paper on Low-Rank Adaptation presents a significant step forward in the field of model optimization. By reducing computational requirements and maintaining performance, LoRa opens new possibilities for deploying AI systems in real-world environments. As research in this area continues to evolve, LoRa & it’s fundamentals is set to become a cornerstone of deep learning optimization, helping to make powerful AI models more accessible and efficient across industries.
Tata Consultancy Services (TCS) on Tuesday announced a 15-year deal with Ireland’s Department of Social Protection (DSP) to provide digital solutions for the automatic enrolment of nearly 800,000 workers in that country.
Building on its experience of delivering similar national programmes, TCS will partner with the DSP to launch Ireland’s ‘Auto Enrolment Pensions Scheme‘, providing workers with a retirement savings platform.
“TCS has a wealth of relevant experience, having provided similar services in other countries. My officials and I will be working hard alongside TCS, the Revenue Commissioners and payroll software developers to make sure that My Future Fund is delivered on time and to the highest standard,” said Heather Humphreys, Minister for Social Protection.
Leveraging its TCS BaNCS platform and ecosystem, the IT services major will oversee the administration of the scheme, enabling seamless enrolment, record management, and benefit disbursement. Services will be delivered through TCS’ Global Delivery Centre in Letterkenny, Co Donegal, Ireland.
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“TCS has expertise and experience in delivering critical transformation projects in the UK and Ireland. We will leverage this experience and our knowledge of the market to make the pension system more accessible, transparent and efficient for workers in Ireland,” said Vivekanand Ramgopal, President, BFSI Products and Platforms.
The project follows the passing of the Automatic Enrolment Retirement Savings System Bill in Ireland earlier this year and the conclusion of a rigorous tender process by the Department of Social Protection.
The “My Future Fund” pension scheme will enable thousands of workers to save and invest for their future.
The system will benefit everyone involved, from employers and operational staff to pensioners, by improving pension record management, timely payments, effective scheme finance management, and providing easy digital access to information.
TCS set up operations in the UK and Ireland nearly 50 years ago and works with 200 of the region’s best-known businesses, including British Airways, Primark, Aviva, Sainsbury’s, Nationwide, M&S, Asda and Boots.
The Indian government has issued a stern warning against the creation and use of illegal payment gateways. These gateways, set up using mule bank accounts, are the handiwork of transnational organized cybercriminals and are being used to facilitate money laundering services. The alert was issued by the Indian Cybercrime Coordination Center (I4C), operating under the Ministry of Home Affairs (MHA).
The I4C has advised citizens against selling or renting their bank accounts, company registration certificates, or Udhyam Aadhaar Registration certificates to anyone. The ministry has warned that illicit funds deposited in such bank accounts could lead to legal consequences, including arrest. Banks are being urged to deploy checks to identify misuse of bank accounts that are used for setting up these illegal payment gateways.
The alert comes in the wake of recent nationwide raids conducted by the Gujarat and Andhra Pradesh Police. These operations revealed that transnational criminals have created illegal digital payment gateways using mule or rented accounts. These illegal infrastructures are being used to launder the proceeds of various cybercrime activities.
The I4C’s analysis, based on information received from State Police Agencies, has identified that current and saving accounts are being scouted through social media platforms, primarily Telegram and Facebook. These accounts belong to shell companies, enterprises, or individuals and are controlled remotely from overseas.
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These mule accounts are then used to create illegal payment gateways, which are given to criminal syndicates for accepting deposits on illegal platforms. These platforms include fake investment scam sites, offshore betting and gambling websites, and fake stock trading platforms.
The ministry has noted that the proceeds of such crimes are immediately layered into another account as soon as they are received. The bulk payout facility provided by banks is being misused for this purpose. Some of the payment gateways identified during the operation include PeacePay, RTX Pay, PoccoPay, and RPPay. These gateways are believed to be providing money laundering as a service and are operated by foreign nationals.
This is not the first time that such a cybercrime has come to light. In the past, there have been instances where cybercriminals have used similar tactics to facilitate illegal activities. However, the scale and sophistication of these operations have increased significantly, making it a matter of grave concern for the authorities.
The government’s alert is a step in the right direction to curb such activities. It not only raises awareness among the public but also puts the onus on banks to implement stringent checks to prevent the misuse of bank accounts. The collaborative efforts of the MHA and LWAs are commendable in their pursuit of a Cyber Secure Bharat.
The fight against such transnational cybercriminal activities is far from over. It requires continuous vigilance, technological advancements, and international cooperation to effectively combat these threats. The government’s alert serves as a reminder of the challenges that lie ahead in the path of ensuring a secure digital environment for all citizens.
As we enter the age of quantum computing, the implications for cryptographic security are profound. Samikya Reddy Balguri, a notable researcher in the field, delves into the challenges posed by quantum computing and the mitigation strategies required to ensure secure systems. This article explores the innovations that address vulnerabilities in traditional cryptography and outlines the potential for quantum-resistant cryptographic systems.
The Quantum Leap: Redefining Computational Capabilities
Quantum computing marks a revolutionary change in solving computational problems. Unlike classical computers that use binary bits, quantum computers rely on qubits, which can exist in multiple states simultaneously through superposition. This allows them to process vast information exponentially faster, especially for tasks like breaking encryption. While quantum computing’s principles of superposition and entanglement offer solutions for complex challenges in areas like simulation and machine learning, they also threaten the security of current cryptographic algorithms.
The Threat to Current Cryptographic Systems
Quantum computing threatens public key cryptography systems like RSA, ECC, and Diffie-Hellman, which rely on the difficulty of factoring large numbers or solving discrete logarithms—tasks quantum algorithms like Shor’s could solve quickly. This poses risks to financial, personal, and governmental data. Symmetric key cryptography, while more resilient, also faces risks as Grover’s algorithm could reduce security by half for algorithms like AES-128. To maintain security, future systems will need larger key sizes, potentially affecting performance and compatibility.
Post-Quantum Cryptography: A Solution for the Future
In response to the quantum threat, researchers are developing quantum-resistant cryptographic algorithms, a field known as post-quantum cryptography, aimed at securing systems against quantum computing power. Several promising approaches are emerging:
Lattice-Based Cryptography: This method relies on the hardness of mathematical problems like the Shortest Vector Problem (SVP), making it challenging for both classical and quantum computers. Its small key sizes and efficient implementation position it as a key player in future security.
Hash-Based Signatures: These signatures, such as XMSS and SPHINCS+, depend on secure hash functions, offering strong protection against quantum attacks.
Code-Based Cryptography: The McEliece cryptosystem, an older approach, requires large key sizes but delivers fast encryption and decryption, making it a reliable option for certain applications.
Overcoming Challenges in Adoption
Transitioning to quantum-resistant cryptography faces several challenges. Compatibility with existing systems is a major concern, as many cryptographic infrastructures are deeply embedded and require careful updates, testing, and certification for a smooth transition. Long-lived systems will need thorough evaluation to avoid disruptions. Performance is another issue, as many quantum-resistant algorithms require larger key sizes and more computational resources, which can degrade performance, especially in resource-constrained environments like IoT devices. Balancing security needs with operational efficiency is crucial for organizations upgrading their cryptographic systems.
The Road Ahead: Hybrid Systems and Beyond
As post-quantum cryptography progresses, hybrid systems are emerging as a temporary solution, combining classical cryptography with quantum-resistant algorithms to protect against both quantum and classical threats. This allows for a gradual transition to quantum-secure systems. Quantum Key Distribution (QKD), relying on physical laws rather than algorithms, also offers a potentially unbreakable communication method. The evolution of post-quantum cryptography will require ongoing collaboration between researchers, industries, and governments, with efforts like NIST’s playing a crucial role in standardizing quantum-resistant algorithms before quantum computing becomes widespread.
In conclusion, as quantum computing inches closer to becoming a practical reality, the need for robust cryptographic security becomes more pressing. Samikya Reddy Balguri’s work in exploring quantum-resistant solutions sheds light on the urgent need to address vulnerabilities in traditional cryptographic systems. By focusing on lattice-based cryptography, hash-based signatures, and code-based cryptography, researchers are taking proactive steps to secure the future of digital communications. With ongoing research and standardization efforts, the path to a quantum-resistant future is becoming clearer—one that requires collaboration, innovation, and preparedness.
