#Homomorphic Encryption

[sageuniversitybpl]

Mathematics in Cryptography: Securing the Digital World

[wuggen]

God, homomorphic encryption is so fucking cool

[cyber-sec]

Apple Unveils Homomorphic Encryption Package for Secure Cloud Computing

Source: https://hackread.com/apple-homomorphic-encryption-secure-cloud-computing/

More info: https://www.swift.org/blog/announcing-swift-homomorphic-encryption/

Repo: https://github.com/apple/swift-homomorphic-encryption

[hackernewsrobot]

Swift Homomorphic Encryption

https://www.swift.org/blog/announcing-swift-homomorphic-encryption/

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[marketers12]

Securing Data with Math: A Deep Dive into the Homomorphic Encryption Market

The homomorphic encryption market encompasses technologies and solutions that enable computations on encrypted data without the need to decrypt it. This field is crucial for ensuring data privacy and security, particularly in industries that handle sensitive information, such as finance, healthcare, and cloud computing. The market includes a variety of encryption schemes, tools, and services that support secure data processing, analytics, and sharing while maintaining confidentiality. The scope of the market extends from research and development in cryptographic methods to commercial applications in data security, compliance, and privacy-preserving computation.

Drivers, Restraints & Opportunities in homomorphic encryption market

The homomorphic encryption market is driven by the increasing need for data privacy and security, particularly in sectors like finance, healthcare, and government, where sensitive information must be protected during processing and storage. The rising adoption of cloud computing and big data analytics also fuels demand, as homomorphic encryption enables secure data operations without exposing the underlying data. However, the market faces restraints such as the high computational complexity and performance overhead associated with current encryption schemes, which can limit widespread adoption. Despite these challenges, significant opportunities exist with advancements in cryptographic research and the growing interest in privacy-preserving technologies, which could lead to more efficient and scalable solutions, expanding the market potential.

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Market Segmentation

Homomorphic Encryption Type Outlook

Fully

Additive

Partial

Multiplicative

Homomorphic Encryption Application Area Outlook

Banking and Finance

Healthcare

Government

Industrial

Competitive Landscape

IBM (US),

Microsoft (US)

SAP (Germany)

Oracle (US)

Intel (US)

Google LLC (US)

Cosmian Tech (France)

CryptoExperts SAS (US)

Duality Technologies Inc. (US)

Enveil Inc. (US)

Inpher, Inc. (US)

Netskope, Inc. (US)

Thales Group (France)

Zaiku Group Ltd.

Market adoption barriers:

Market adoption of homomorphic encryption faces several barriers, primarily due to the high computational overhead and complexity associated with existing encryption schemes, which can significantly slow down data processing compared to traditional methods. Additionally, the lack of standardized protocols and interoperability between different homomorphic encryption systems hinders widespread implementation. Limited awareness and understanding of the technology among potential users, along with concerns about integration with existing infrastructure, further challenge adoption. These barriers make it difficult for organizations to justify the costs and resources required to implement homomorphic encryption, especially in environments where performance and efficiency are critical.

Future outlook

The future outlook for the homomorphic encryption market is promising, driven by increasing concerns over data privacy and security in an increasingly digital world. As technology advances, the computational efficiency and scalability of homomorphic encryption are expected to improve, making it more viable for widespread adoption across various industries. With growing investments in research and development, as well as interest from major tech companies, we can anticipate more robust and user-friendly solutions emerging in the market. The integration of homomorphic encryption into cloud services, big data analytics, and artificial intelligence will likely expand its applications, positioning it as a key component in the future of secure data processing. As regulatory pressures for stronger data protection continue to rise, the market is expected to see accelerated growth, with more organizations adopting homomorphic encryption to meet compliance requirements and enhance data security.

Recommendations for stakeholders of homomorphic encryption market

Stakeholders in the homomorphic encryption market should focus on collaborative efforts to overcome technical challenges and drive standardization, which will facilitate broader adoption. Investing in research and development is crucial to enhance the efficiency and scalability of homomorphic encryption solutions. Stakeholders should also prioritize educating potential users about the benefits and applications of this technology, helping to demystify its complexity and promote its value in securing sensitive data. Building partnerships across industries, particularly with cloud service providers and regulatory bodies, can further accelerate market growth by integrating homomorphic encryption into mainstream security practices and ensuring compliance with evolving data protection regulations.

Browse In-depth Market Research Report:

[educationtech]

8 Emerging Cybersecurity Trends to Watch Out in 2024 - Arya College

The landscape of cybersecurity Trends is evolving rapidly, and IT professionals must stay informed about IT Security trends in 2024 to effectively protect organizations from emerging threats. As we move into 2024, several key trends are shaping the cybersecurity environment, driven by advancements in technology, changes in regulatory landscapes, and the evolving tactics of cybercriminals.

1. Integration of Artificial Intelligence and Machine Learning

Artificial Intelligence (AI) and Machine Learning (ML) are becoming central to cybersecurity strategies. These technologies enhance threat detection and response capabilities by analyzing vast amounts of data in real time, identifying anomalies, and predicting potential security breaches. In 2024, organizations will increasingly rely on AI-driven security solutions to automate responses to threats, reducing the time it takes to mitigate attacks.

2. Proliferation of Ransomware Attacks

Ransomware remains a significant threat, with attackers increasingly targeting critical infrastructure and high-profile organizations. In 2023, ransomware affected 66% of organizations, highlighting the urgency for robust ransomware mitigation strategies. IT professionals must prioritize implementing multi-layered defenses, including regular backups, employee training, and proactive threat hunting to mitigate risks associated with ransomware attacks.

3. Supply Chain Security

Supply chain attacks are on the rise as cybercriminals exploit vulnerabilities within third-party vendors and partners. In 2024, organizations must enhance their supply chain risk management practices by conducting thorough vendor assessments and implementing stringent security protocols throughout their supply chain ecosystems.

4. Emphasis on Cloud Security

As organizations increasingly migrate to cloud environments, ensuring robust cloud security becomes paramount. This includes implementing strong identity and access management, continuous monitoring, and encryption of sensitive data stored in the cloud.

5. Adoption of Zero Trust Security Models

The Zero Trust security model, which operates on the principle of "never trust, always verify," is gaining traction as a fundamental approach to cybersecurity. In 2024, organizations will increasingly adopt zero-trust architectures, which require strict identity verification for every individual and device attempting to access resources, regardless of whether they are inside or outside the network perimeter.

6. Regulatory Compliance and Governance

With the increasing frequency of data breaches, regulatory compliance is becoming a critical focus for organizations. New regulations, such as the EU’s NIS2 Directive and changes by the SEC regarding material cybersecurity breaches, are prompting organizations to reassess their cybersecurity governance structures.

7. Enhanced Focus on Cybersecurity Training and Awareness

As cyber threats become more sophisticated, the need for comprehensive cybersecurity training for employees is more critical than ever. In 2024, organizations will invest in ongoing training programs to educate employees about recognizing phishing attempts, secure password practices, and safe internet usage. A well-informed workforce is a vital line of defense against emerging cyber threats, and organizations will prioritize fostering a culture of cybersecurity awareness.

8. Privacy-enhancing technologies (PETs)

With growing concerns about data privacy, Privacy-Enhancing Technologies (PETs) are emerging as essential tools for organizations. These technologies, such as homomorphic encryption and differential privacy, allow data to be processed while maintaining its confidentiality. In 2024, organizations will increasingly adopt PETs to comply with privacy regulations and protect sensitive information from unauthorized access. How is the cybersecurity market expected to consolidate in the coming year. The cybersecurity market is expected to see significant consolidation in the coming years, driven by several key factors: Fragmentation and Opportunity for Consolidation.

Conclusion

The cybersecurity landscape in 2024 presents both challenges and opportunities for IT professionals at Arya College of Engineering & IT, Jaipur. By staying informed about these trends and adopting proactive security measures, organizations can enhance their resilience against evolving cyber threats. Emphasizing AI and ML, strengthening supply chain security, adopting Zero Trust models, and ensuring regulatory compliance are all critical components of a robust cybersecurity strategy. As cyber threats continue to evolve, the Future of IT with IT professionals must remain vigilant and adaptable to safeguard their organizations effectively.

[ai-news]

Ensuring data privacy and security during computational processes presents a significant challenge, particularly when using cloud services. Traditional encryption methods require data to be decrypted before processing, exposing it to potential risks #AI #ML #Automation

[coinmystique]

This industry-first confidential good contract platform powered by totally homomorphic encryption (FHE) is advancing the technical capabilities of Ethereum (ETH) with an extra layer of privateness.Fhenix competes seed funding, raises $7 million from high VCsFhenix, a completely confidential EVM-compatible blockchain powered by totally homomorphic encryption (FHE), efficiently completes its seed funding spherical. A complete of $7 million was raised from a few blue-chip VCs. Blockchain enterprise heavyweights Multicoin Capital and Collider Ventures co-led the spherical for Fhenix.Picture by FhenixThe spherical yielded contributions from Node Capital, Bankless, HackVC, TaneLabs and Metaplanet, whereas Tarun Chitra and Robert Leshner’s Robotic Ventures additionally backed the platform in its fundraising efforts.Contemporary funds might be used to assist the launch of Fhenix public testnet this 12 months and the progress of the decentralized software (dApp) ecosystem on Fhenix.Former Intel officer Man Zyskind, Fhenix and Secret founder, stresses the pivotal significance of totally homomorphic encryption (FHE) for bringing Ethereum (ETH) and EVM ecosystems to the following stage:Fhenix addresses an enormous drawback within the Ethereum ecosystem: a scarcity of encryption for commercially delicate information. Fhenix offers customers the arrogance to place delicate information on public blockchains whereas additionally giving builders the instruments to compute and rework that information for the primary time. The acute want for information confidentiality is quickly rising which is driving demand for progressive applied sciences like FHE and fostering collaborations between complementary blockchains resembling Fhenix and Secret to make sure a safer and privacy-centric future.Fhenix’s progressive method envisages bringing information encryption to the phase of good contracts, transactions and on-chain belongings for the primary time in Web3.Exploring alternatives of fhEVMMan Itzhaki, Fhenix’s CEO, is bound that the utilization of FHE will clear up main challenges within the sphere of information switch and possession for individuals and establishments:By harnessing the ability of FHE, we will clear up one of many final remaining challenges in web3, and permit customers to not solely personal their information, but additionally management who they share their information with.  With Fhenix’s encrypted good contracts, we will empower builders to make use of encrypted blockchain as an enabler for brand spanking new enterprise alternatives, together with on chain trustless gaming, non-public voting for DAOs, on chain privacy-preserving AI and rather more.The fhEVM protocol was initially developed by Zama, the main cryptography firm constructing open supply homomorphic encryption options for blockchain and AI, and was built-in immediately into the Fhenix Community by a strategic partnership.Fhenix community kicked off its non-public devnet in July 2023. The community acts as a safe risk-free playground for all fanatics of good contracts. Builders can experiment with a brand new era of privacy-centric dApps.Supply: https://u.right this moment/fhenix-raises-7-million-in-seed-funding-multicoin-capital-led-round

[logicluxe]

The Future of Data Encoding: Trends and Innovations

Data encoding is a rapidly evolving field that continues to undergo significant changes and advancements to meet the evolving needs of data management and security. In this article, we will explore the future trends and innovations in data encoding, including the adoption of artificial intelligence and machine learning technologies, and their impact on data security and privacy.

One of the emerging trends in data encoding is the integration of artificial intelligence (AI) and machine learning (ML) technologies to automate and optimize data encoding processes. AI-powered data encoding tools can intelligently identify patterns and anomalies in data sets, automatically detect errors, and enhance data quality and accuracy. By leveraging AI and ML technologies, data encoders can streamline data encoding tasks and improve operational efficiency within organizations.

Another trend in data encoding is the use of blockchain technology to enhance data security and integrity Fully Undetectable Crypter. Blockchain enables organizations to create a secure and tamper-proof distributed ledger that stores encoded data in a decentralized and encrypted format. By leveraging blockchain technology, data encoders can ensure the immutability and transparency of encoded data, thereby enhancing data security and trustworthiness.

Data encoding technologies are also evolving to meet the demands of big data and the Internet of Things (IoT) by developing scalable and efficient encoding solutions that can process and encode massive volumes of data in real-time. Data encoders are exploring innovative encoding techniques such as differential privacy and homomorphic encryption to protect data privacy and confidentiality in the era of big data and IoT.

In conclusion, the future of data encoding is characterized by the adoption of advanced technologies such as artificial intelligence, blockchain, and innovative encoding techniques to enhance data security, privacy, and integrity. By embracing these trends and innovations, data encoders can play a pivotal role in shaping the future of data encoding and contributing to the development of secure and resilient data management practices within organizations.

[surajheroblog]

Privacy-Preserving Data Science: A Delicate Balance

In the ever-evolving landscape of data science, striking a balance between extracting valuable insights and safeguarding user privacy is paramount. As organizations collect and analyze vast amounts of data, the ethical responsibility to protect individuals becomes increasingly critical. In this blog post, we delve into the delicate dance of privacy-preserving data science and explore techniques to maintain this equilibrium.

1. Understanding Privacy Risks in Data Science

1.1. The Data Goldmine

Data science thrives on data—rich, diverse, and abundant. However, this treasure trove comes with risks. We discuss the potential privacy pitfalls when handling sensitive information and the legal implications.

1.2. Privacy Threats: From Re-identification to Inference Attacks

Learn about re-identification attacks, attribute disclosure, and how seemingly innocuous data points can reveal personal details. We also explore the concept of differential privacy as a protective measure.

2. Privacy-Preserving Techniques

2.1. Anonymization and Masking

Discover methods to anonymize data while retaining its utility. We cover k-anonymity, l-diversity, and t-closeness, along with practical implementation examples.

2.2. Homomorphic Encryption

Dive into the fascinating world of homomorphic encryption, where computations can be performed on encrypted data without decryption. Explore its applications in secure data analysis.

3. Privacy-Aware Machine Learning

3.1. Federated Learning

How can we train models collaboratively without sharing raw data? Federated learning offers a solution. We discuss its benefits, challenges, and real-world use cases.

3.2. Differential Privacy in Model Training

Embed privacy directly into machine learning algorithms. Understand ε-differential privacy and its impact on model accuracy, fairness, and robustness.

4. Balancing Utility and Privacy

4.1. The Trade-Off: Accuracy vs. Privacy

Explore the trade-offs between accurate models and privacy guarantees. We delve into the concept of privacy budgets and model performance under differential privacy constraints.

4.2. User Consent and Transparency

Transparency is key. Learn how to communicate privacy practices to users effectively. We discuss privacy policies, informed consent, and user-centric design.

Conclusion

As data scientists, we hold immense power—the power to extract knowledge from data and the power to protect individual rights.

Enroll in our data science course institute and take your data science skills to the next level. Explore privacy-preserving techniques, learn from industry experts, and earn your certification. 

[hackernewsrobot]

The Rise of Fully Homomorphic Encryption

https://queue.acm.org/detail.cfm?id=3561800 Comments

[lovelypol]

Securing Distributed Storage and Processing Frameworks

Big Data Security is a critical area of focus as organizations increasingly rely on vast and complex datasets to drive decision-making and innovation.

Ensuring the security of big data involves addressing several key challenges, including data privacy, integrity, and availability. Advanced encryption techniques, such as homomorphic encryption, are employed to protect data at rest, in transit, and during processing, allowing computations to be performed on encrypted data without compromising its confidentiality. Access control mechanisms, including role-based access control (RBAC) and attribute-based access control (ABAC), are crucial in managing permissions and ensuring that only authorized users can access sensitive data. Additionally, the implementation of robust data masking and anonymization techniques helps in safeguarding personally identifiable information (PII) and complying with regulatory requirements such as GDPR and CCPA. Big data environments often utilize distributed storage and processing frameworks like Hadoop and Spark, necessitating comprehensive security measures across multiple nodes and clusters. Security information and event management (SIEM) systems are deployed to monitor and analyze security events in real-time, enabling the detection and mitigation of potential threats. Machine learning algorithms play an increasingly significant role in identifying anomalous patterns and predicting security breaches before they occur. As cyber threats continue to evolve, continuous vulnerability assessments and penetration testing are essential to maintain the security posture of big data infrastructures. The future of big data security lies in the integration of advanced technologies such as blockchain for immutable audit trails and zero-trust architectures to minimize the attack surface and enhance overall data protection. #BigDataSecurity #Encryption #DataPrivacy #AccessControl #DataMasking #Anonymization #GDPR #CCPA #DistributedStorage #SIEM #MachineLearning #CyberSecurity #ThreatDetection #VulnerabilityAssessment #Blockchain #ZeroTrust #DataProtection #HadoopSecurity #SparkSecurity #DataIntegrity #Compliance #DataGovernance #SecurityArchitecture #InformationSecurity #TechInnovation

[albertpeter]

How Is Blockchain Technology Advancing Cryptocurrency Development in 2024?

Blockchain technology, since its inception, has been synonymous with cryptocurrencies. As we move further into 2024, its impact on cryptocurrency development is more profound than ever. From enhancing security and scalability to enabling new forms of digital assets, let's delve into how blockchain technology will advance cryptocurrency development in 2024.

Enhanced Security: Blockchain's immutable and decentralized nature makes it a robust platform for ensuring the security of cryptocurrency transactions. In 2024, advancements in cryptography and consensus mechanisms are making blockchain networks even more secure. Technologies like multi-signature wallets, zero-knowledge proofs, and homomorphic encryption are becoming more prevalent, providing users with greater confidence in the safety of their digital assets.

Scalability Solutions: One of the longstanding challenges of blockchain technology has been scalability. In 2024, we're seeing the emergence of Layer 2 solutions, such as the Lightning Network for Bitcoin and the Raiden Network for Ethereum, which are designed to increase transaction throughput and reduce latency. These solutions enable cryptocurrencies to handle a larger volume of transactions, making them more suitable for mass adoption.

Interoperability: Blockchain technology is enabling interoperability between different cryptocurrencies and blockchain networks. Projects like Polkadot, Cosmos, and Wanchain are creating bridges that allow assets and data to move seamlessly between disparate blockchains. This interoperability not only improves the efficiency of cryptocurrency transactions but also opens up new possibilities for cross-chain applications and decentralized finance (DeFi) protocols.

Tokenization of Assets: Blockchain technology is revolutionizing the way assets are represented and traded. In 2024, we're witnessing the tokenization of traditional assets such as real estate, art, and commodities. These digital tokens are programmable, divisible, and can be traded instantly, making them more liquid and accessible to a global audience. This trend is blurring the lines between traditional finance and the cryptocurrency world, paving the way for a new era of digital asset ownership.

Decentralized Finance (DeFi): DeFi has been one of the most significant trends in cryptocurrency development in recent years, and its growth is expected to continue in 2024. DeFi platforms leverage blockchain technology to offer a wide range of financial services, including lending, borrowing, trading, and insurance, without the need for traditional financial intermediaries. This decentralized approach to finance is democratizing access to financial services and creating new opportunities for innovation in the cryptocurrency space.

Smart Contracts: Smart contracts are self-executing contracts with the terms of the agreement directly written into code. They enable trustless and automated transactions, removing the need for intermediaries. In 2024, smart contracts are being used in a variety of cryptocurrency applications, including decentralized exchanges (DEXs), decentralized autonomous organizations (DAOs), and non-fungible tokens (NFTs). The programmability of smart contracts is enabling new use cases and business models that were previously impossible.

Regulatory Compliance: Blockchain technology is also driving advancements in regulatory compliance for cryptocurrencies. In 2024, we're seeing the development of solutions that enable cryptocurrency transactions to comply with anti-money laundering (AML) and know-your-customer (KYC) regulations. These solutions are essential for the continued adoption of cryptocurrencies by mainstream financial institutions and regulators.

Conclusion

Blockchain technology is playing a pivotal role in advancing cryptocurrency development in 2024. From enhancing security and scalability to enabling new forms of digital assets and decentralized finance, blockchain technology is driving innovation and reshaping the future of finance. As we continue to see these advancements unfold, the cryptocurrency landscape is poised for further growth and evolution in the years to come.