Formal modeling and analysis of security schemes of RPL protocol using colored Petri nets.

In the Internet of things (IoT), data packets are accumulated and disseminated across IoT devices without human intervention, therefore the privacy and security of sensitive data during transmission are crucial. For this purpose, multiple routing techniques exist to ensure security and privacy in IoT Systems. One such technique is the routing protocol for low power and lossy networks (RPL) which is an IPv6 protocol commonly used for routing in IoT systems. Formal modeling of an IoT system can validate the reliability, accuracy, and consistency of the system. This paper presents the formal modeling of RPL protocol and the analysis of its security schemes using colored Petri nets that applies formal validation and verification for both the secure and non-secure modes of RPL protocol. The proposed approach can also be useful for formal modeling-based verification of the security of the other communication protocols.

Image Watermarking Using Least Significant Bit and Canny Edge Detection.

With the advancement in information technology, digital data stealing and duplication have become easier. Over a trillion bytes of data are generated and shared on social media through the internet in a single day, and the authenticity of digital data is currently a major problem. Cryptography and image watermarking are domains that provide multiple security services, such as authenticity, integrity, and privacy. In this paper, a digital image watermarking technique is proposed that employs the least significant bit (LSB) and canny edge detection method. The proposed method provides better security services and it is computationally less expensive, which is the demand of today's world. The major contribution of this method is to find suitable places for watermarking embedding and provides additional watermark security by scrambling the watermark image. A digital image is divided into non-overlapping blocks, and the gradient is calculated for each block. Then convolution masks are applied to find the gradient direction and magnitude, and non-maximum suppression is applied. Finally, LSB is used to embed the watermark in the hysteresis step. Furthermore, additional security is provided by scrambling the watermark signal using our chaotic substitution box. The proposed technique is more secure because of LSB's high payload and watermark embedding feature after a canny edge detection filter. The canny edge gradient direction and magnitude find how many bits will be embedded. To test the performance of the proposed technique, several image processing, and geometrical attacks are performed. The proposed method shows high robustness to image processing and geometrical attacks.

Targeting Glioblastoma with the Use of Phytocompounds and Nanoparticles.

Glioblastoma multiforme (GBM) are extremely lethal and still poorly treated primary brain tumors, characterized by the presence of highly tumorigenic cancer stem cell (CSC) subpopulations, considered responsible for tumor relapse. In order to successfully eradicate GBM growth and recurrence, new anti-cancer strategies selectively targeting CSCs should be designed. CSCs might be eradicated by targeting some of their cell surface markers and transporters, inducing their differentiation, impacting their hyper-glycolytic metabolism, inhibiting CSC-related signaling pathways and/or by targeting their microenvironmental niche. In this regard, phytocompounds such as curcumin, isothiocyanates, resveratrol and epigallocatechin-3-gallate have been shown to prevent or reverse cancer-related epigenetic dysfunctions, reducing tumorigenesis, preventing metastasis and/or increasing chemotherapy and radiotherapy efficacy. However, the actual bioavailability and metabolic processing of phytocompounds is generally unknown, and the presence of the blood brain barrier often represents a limitation to glioma treatments. Nowadays, nanoparticles (NPs) can be loaded with therapeutic compounds such as phytochemicals, improving their bioavailability and their targeted delivery within the GBM tumor bulk. Moreover, NPs can be designed to increase their tropism and specificity toward CSCs by conjugating their surface with antibodies specific for CSC antigens, with ligands or with glucose analogues. Here we discuss the use of phytochemicals as anti-glioma agents and the applicability of phytochemical-loaded NPs as drug delivery systems to target GBM. Additionally, we provide some examples on how NPs can be specifically formulated to improve CSC targeting.

The Use of Neuroimaging to Assess Associations Among Diet, Nutrients, Metabolic Syndrome, and Alzheimer's Disease.

In the last decade, specific dietary patterns, mainly characterized by high consumption of vegetables and fruits, have been proven beneficial for the prevention of both metabolic syndrome (MetS)-related dysfunctions and neurodegenerative disorders, such as Alzheimer's disease (AD). Nowadays, neuroimaging readouts can be used to diagnose AD, investigate MetS effects on brain functionality and anatomy, and assess the effects of dietary supplementations and nutritional patterns in relation to neurodegeneration and AD-related features. Here we review scientific literature describing the use of the most recent neuroimaging techniques to detect AD- and MetS-related brain features, and also to investigate associations between consolidated dietary patterns or nutritional interventions and AD, specifically focusing on observational and intervention studies in humans.