Questa è la nostra ultima selezione di pubblicazioni e brevetti in inglese sulla Cybersecurity, tra numerose riviste scientifiche online, classificate e focalizzate su cybersecurity, malware, phishing, firewall, crittografia, zero-day exploit, denial of service, data breach e threat intelligence.
Blockchain-Based, Dynamic Attribute-Based Access Control for Smart Home Energy Systems
Published on 2025-04-11 by Urooj Waheed, Sadiq Ali Khan, Muhammad Masud, Huma Jamshed, Touqeer Ahmed Jumani, Najeeb Ur Rehman Malik @MDPI
Abstract: The adoption of the Internet of Things (IoT) in smart household energy systems offers new opportunities for efficiency and automation, while also posing substantial security challenges. These systems utilize diverse standards and protocols to autonomously access, collect, and share energy-related data over distributed networks. However, this interconnectivity increases their vulnerability to cyber threats, making the system vulnerable to cyber threats. The literature reveals numerous cases of cy[...]
Our summary: The paper proposes a dynamic attribute-based access control model using blockchain to enhance security in smart household energy systems, addressing cyber threats and ensuring efficient access control.
Blockchain-Based, Dynamic Attribute-Based Access Control, Smart Home Energy Systems, IoT
Publication
Zero-Trust Mechanisms for Securing Distributed Edge and Fog Computing in 6G Networks
Published on 2025-04-09 by Abdulrahman K. Alnaim, Ahmed M. Alwakeel @MDPI
Abstract: The rapid advancement in 6G networks, driven by the proliferation of distributed edge and fog computing, has introduced unprecedented challenges in securing these decentralized architectures. Traditional security paradigms are inadequate for protecting the dynamic and heterogeneous environments of 6G-enabled systems. In this context, we propose ZTF-6G (Zero-Trust Framework for 6G Networks), a novel model that integrates Zero-Trust principles to secure distributed edge and fog computing environme[...]
Our summary: Zero-Trust Framework for 6G Networks integrates Zero-Trust principles to secure distributed edge and fog computing environments, ensuring robust security through adaptive authentication, continuous verification, and fine-grained access control. The framework utilizes multi-layering, AI-driven anomaly detection, and blockchain-based identity management to reduce latency, improve throughput, resource utilization, trust score accuracy, energy efficiency, threat detection accuracy, and insider threat mitigation in 6G networks.
Zero-Trust, Edge Computing, Fog Computing, 6G Networks
Publication
Takagi–Sugeno–Kang Fuzzy Neural Network for Nonlinear Chaotic Systems and Its Utilization in Secure Medical Image Encryption
Published on 2025-03-11 by Duc Hung Pham, Mai The Vu @MDPI
Abstract: This study introduces a novel control framework based on the Takagi–Sugeno–Kang wavelet fuzzy neural network, integrating brain imitated network and cerebellar network. The proposed controller demonstrates high robustness, making it an excellent candidate for handling intricate nonlinear dynamics, effectively mapping input–output relationships and efficiently learning from data. To enhance its performance, the controller’s parameters are fi[...]
Our summary: Novel control framework based on Takagi-Sugeno-Kang wavelet fuzzy neural network, high robustness, parameters fine-tuned using Lyapunov stability theory, superior learning capabilities and outstanding performance metrics, synchronization technique applied to secure transmission of medical images, experimental results confirm effectiveness and reliability.
Takagi-Sugeno-Kang, Fuzzy Neural Network, Secure Medical Image Encryption, Nonlinear Chaotic Systems
Publication
A Reliable and Privacy-Preserving Framework for Federated Learning-Based IoT Malware Detection
Published on 2025-03-10 by Mohammed Asiri, Maher A. Khemakhem, Reemah M. Alhebshi, Bassma S. Alsulami, Fathy E. Eassa @MDPI
Abstract: The proliferation of Internet of Things (IoT) devices and their vulnerability to malware infections pose critical security challenges in IoT networks and multi-access edge computing (MEC). Traditional federated learning-based IoT malware detection (FL-IMD) methods face limitations in privacy, reliability, and client authentication, necessitating innovative solutions. This study proposes a reliable and privacy-preserving federated learning framework (RPFL) that integrates elliptic curve digital s[...]
Our summary: A study proposes a reliable and privacy-preserving federated learning framework integrating ECDSA, homomorphic encryption, and blockchain technology. Experimental results show RPFL achieves high accuracy in IoT malware detection while enhancing reliability and privacy. RPFL outperforms BCFL in reducing communication costs and latency.
federated learning, IoT malware detection, privacy-preserving framework, reliability
Publication
A High-Entropy True Random Number Generator with Keccak Conditioning for FPGA
Published on 2025-03-08 by Valeria Piscopo, Alessandra Dolmeta, Mattia Mirigaldi, Maurizio Martina, Guido Masera @MDPI
Abstract: Any cryptographic system strongly relies on randomness to ensure robust encryption and masking methods. True Random Number Generators play a fundamental role in this context. The National Institute of Standards and Technology (NIST) and the Bundesamt für Sicherheit in der Informationstechnik (BSI) provide guidelines for designing reliable entropy sources to fuel cryptographic Random Bit Generators. This work presents a highly parameterized, open-source implementation of a TRNG based[...]
Our summary: Implementation of a highly parameterized TRNG with optimized Keccak conditioning unit, meeting NIST and BSI guidelines, achieving high min-entropy per bit.
True Random Number Generator, High-Entropy, Keccak Conditioning, FPGA
Publication
Enhancing the Effectiveness and Efficiency of Knowledge Transfer in Malware Classification
Published on 2025-03-08 by Hyeon-Jin Jeong, Han-Jin Lee, Gwang-Nam Kim, Seok-Hwan Choi @MDPI
Abstract: As malware continues to evolve, AI-based malware classification methods have shown significant promise in improving the malware classification performance. However, these methods lead to a substantial increase in computational complexity and the number of parameters, increasing the computational cost during the training process. Moreover, the maintenance cost of these methods also increases, as frequent retraining and transfer learning are required to keep pace with evolving malware variants. In[...]
Our summary: Enhancing malware classification efficiency and effectiveness through Self-MCKD, a technique that transfers output logits separated into target and non-target classes, utilizing small and shallow AI-based models. Outperforms traditional knowledge distillation methods in malware classification.
Knowledge Transfer, Malware Classification, AI-based Methods, Computational Complexity
Publication
Network-independent dynamic encryption
Patent published on the 2025-03-06 in WO under Ref WO2025049427 by CONC3AL INC [US] (Ilic Igor [us], Quinn Cary [us], Chase Charles [us], Nastasi Franklin [us])
Abstract: A computer-implemented method to improve the safety of digital documents and assets, including for example digital tickets, may include the steps of: generating a salt/public key by obtaining a longitude and latitude of an event attendee smart device GPS chip and obtaining a time stamp from the smart device operating system; creating a static and unique ID; creating a data carrier/glyph/code, such creating a new quick response code, in intervals using data to be rehashed comprising the unique ID[...]
Our summary: A method for enhancing digital document safety by generating unique IDs and using GPS data to create dynamic encryption codes for validation.
dynamic encryption, digital documents, GPS chip, quick response code
Patent
Method and apparatus for confirming boarding of passenger in uam environment
Patent published on the 2025-03-06 in WO under Ref WO2025048366 by KIA CORP [KR] (Jung Chang Hun [kr], Park Seung Wook [kr])
Abstract: A method and an apparatus for confirming boarding of a passenger in a UAM environment are disclosed. According to one aspect of the present disclosure, the provided method, which is performed by a fuselage system supporting a function of checking whether a user has boarded a fuselage and taken a reserved seat, comprises the steps of: receiving, from a user terminal, a first encryption token including reservation information of the user and identification proof information; receiving, from a flig[...]
Our summary: Method and apparatus for confirming boarding of passenger in UAM environment by using encryption tokens and symmetric key to verify user reservation and seat allocation.
boarding, passenger, UAM, fuselage
Patent
IT 
EN 
FR 
DE 
ES