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A two-way trust framework for AI agents and blockchain

The study establishes a bidirectional trust framework for AI and blockchain interactions, addressing key issues like identity, permission, and intent-based execution. The framework identifies unfinished standards and security questions, highlighting the need for further research to ensure secure and autonomous systems.

SourceELSP·JournalBlockchain·TypeSystematic review·DateSep 23, 2026

Training Australia’s next line of cyber defence

A new partnership will provide access to a constantly evolving training environment, enabling the development of practical cyber skills and strengthening connections between education, research, industry, and defence. The partnership aims to build Australia's sovereign cyber capability and ensure resilience in the face of evolving cybe...

‘Gamified’ DDoS attacks wage psychological warfare against NATO states, finds study

A study by Aalto University reveals pro-Russian hackers are using 'gamified' DDoS attacks to undermine public trust in governments and institutions, with cryptocurrency-based rewards for successful attacks. The researchers urge companies and governments to counteract the effects of propaganda and psychological intimidation.

SourceAalto University·JournalJournal of Information Technology Teaching Cases·DateAug 31, 2026

Seoul National University of Science and Technology develops AI framework to test and improve vision-system robustness

A new AI framework, AdvWT, uses realistic fading, cracks, and corrosion to test vulnerabilities in AI vision systems. It achieves near-perfect attack success rates on lightweight CNNs and transformer-based models, and can also be used to restore naturally damaged traffic signs.

SourceSeoul National University of Science & Technology·JournalIEEE Transactions on Dependable and Secure Computing·TypeExperimental study·DateAug 31, 2026

Online reviews risk cyberattacks

A new study found that online review platforms can be vulnerable to cyberattacks, which can be triggered by analyzing users' review lengths and social connections. The researchers suggest adding noise to the data to reduce the risk of identity theft and phishing attacks.

SourceUniversity of Texas at Austin·JournalInformation Systems Research·DateAug 26, 2026

Thwarting hidden resume hacks targeting AI hiring tools

A recent study from Duke University and industry collaborators found that at least 1% of resumes submitted to a popular hiring platform contained hidden instructions designed to trick the AI system. The trend is accelerating quickly, with the rate increasing sevenfold between July 2024 and November 2025.

SourceDuke University·TypeData/statistical analysis·DateJul 22, 2026

AI gets a cerebellum

A new brain-like electronic device consumes very little energy and detects novelties almost instantly, with over 98% accuracy. The device requires roughly 10,000 times fewer computer operations than conventional AI approaches, paving the way for more energy-efficient AI systems.

SourceNorthwestern University·JournalNature Communications·DateJul 10, 2026

To defend your software, first teach AI to break it

A team of researchers, led by Ying Zhang, has developed artificial intelligence-driven tools to identify and attack software vulnerabilities. By teaching AI to generate proof-of-concept exploits, developers can see exactly how attackers could exploit known flaws, motivating them to fix issues before malicious actors do.

New federated learning algorithm enables private, robust, and fast AI development

Researchers have developed a federated learning algorithm that solves the long-standing conflict between robustness and efficiency in AI development. The new approach anonymizes data and reduces single-point failure risks while maintaining speed. By remembering past client interactions, servers can protect against malicious input.

A tokenized blockchain framework for faster and safer medical record sharing

Researchers developed SST-MedChain, a patient-centric framework for secure electronic medical record sharing on permissioned blockchains. The system uses non-interactive delegation, one-time access tokens, and policy-bounded re-delegation to reduce costly on-chain authorization while preserving traceability and revocation.

SourceELSP·JournalBlockchain·TypeExperimental study·DateJul 6, 2026

UT System investments of over $470 million accelerate UT San Antonio’s rise as a world-class research university

The University of Texas System has invested over $470 million in capital projects supporting UT San Antonio's growth as a top public research university. These investments span research, innovation, infrastructure, technology, and patient care, with a focus on expanding the university's research capabilities and technology infrastructure.

AI fails to make inroads with cybercriminals, study finds

A study analyzing 100 million posts from underground cybercrime communities found that most cybercriminals lack the skills to use AI effectively, and its adoption has limited benefits for their work. However, AI coding assistants are mostly useful for already skilled actors, and poorly secured agentic AI systems pose a significant risk.

SourceUniversity of Edinburgh·TypeObservational study·DateMay 4, 2026

Companies disclose more on cybersecurity – but markets remain indifferent

A study by the University of Vaasa and Aalto University finds that mandatory cybersecurity disclosure in the US has increased internal documentation and made cyber risks more visible to senior management, but not affected investor behavior. Companies produced new content describing their cybersecurity governance structures, suggesting ...

SourceUniversity of Vaasa·JournalInternational Journal of Accounting Information Systems·DateApr 29, 2026