Botnet Detection and Mitigation Model for IoT Networks Using Federated Learning.

The Internet of Things (IoT) introduces significant security vulnerabilities, raising concerns about cyber-attacks. Attackers exploit these vulnerabilities to launch distributed denial-of-service (DDoS) attacks, compromising availability and causing financial damage to digital infrastructure. This study focuses on mitigating DDoS attacks in corporate local networks by developing a model that operates closer to the attack source. The model utilizes Host Intrusion Detection Systems (HIDS) to identify anomalous behaviors in IoT devices and employs network-based intrusion detection approaches through a Network Intrusion Detection System (NIDS) for comprehensive attack identification. Additionally, a Host Intrusion Detection and Prevention System (HIDPS) is implemented in a fog computing infrastructure for real-time and precise attack detection. The proposed model integrates NIDS with federated learning, allowing devices to locally analyze their data and contribute to the detection of anomalous traffic. The distributed architecture enhances security by preventing volumetric attack traffic from reaching internet service providers and destination servers. This research contributes to the advancement of cybersecurity in local network environments and strengthens the protection of IoT networks against malicious traffic. This work highlights the efficiency of using a federated training and detection procedure through deep learning to minimize the impact of a single point of failure (SPOF) and reduce the workload of each device, thus achieving accuracy of 89.753% during detection and increasing privacy issues in a decentralized IoT infrastructure with a near-real-time detection and mitigation system.

Biopolymer from Water Kefir as a Potential Clean-Label Ingredient for Health Applications: Evaluation of New Properties.

The present work aimed to characterize the exopolysaccharide obtained from water kefir grains (EPSwk), a symbiotic association of probiotic microorganisms. New findings of the technological, mechanical, and biological properties of the sample were studied. The EPSwk polymer presented an Mw of 6.35 × 105 Da. The biopolymer also showed microcrystalline structure and characteristic thermal stability with maximum thermal degradation at 250 °C. The analysis of the monosaccharides of the EPSwk by gas chromatography demonstrated that the material is composed of glucose units (98 mol%). Additionally, EPSwk exhibited excellent emulsifying properties, film-forming ability, a low photodegradation rate (3.8%), and good mucoadhesive properties (adhesion Fmax of 1.065 N). EPSwk presented cytocompatibility and antibacterial activity against Escherichia coli and Staphylococcus aureus. The results of this study expand the potential application of the exopolysaccharide from water kefir as a potential clean-label raw material for pharmaceutical, biomedical, and cosmetic applications.

Effects of processing on the structure of zein/oleic Acid films investigated by x-ray diffraction.

Zein films plasticized with oleic acid were formed by solution casting, by the stretching of moldable resins, and by blown film extrusion. The effects of the forming process on film structure were investigated by X-ray diffraction. Wide-angle X-ray scattering (WAXS) patterns showed d-spacings at 4.5 and 10 A, which were attributed to the zein alpha-helix backbone and inter-helix packing, respectively. The 4.5 A d-spacing remained stable under processing while the 10 A d-spacing varied with processing treatment. Small-angle X-ray scattering (SAXS) detected a long-range periodicity for the formed films but not for unprocessed zein, which suggests that the forming process-promoted film structure development is possibly aided by oleic acid. The SAXS d-spacing varied among the samples (130-238 A) according to zein origin and film-forming method. X-ray scattering data suggest that the zein molecular structure resists processing but the zein supramolecular arrangements in the formed films are dependent on processing methods. Structural model for a zein molecular aggregate (based on Matsushima et al.10). Rectangular prisms of individual zein molecules are hexagonally aligned parallel to each other.