The Rise of Passive RFID RTLS Solutions in Industry 5.0.

In today's competitive landscape, manufacturing companies must embrace digital transformation. This study asserts that integrating Internet of Things (IoT) technologies for the deployment of real-time location systems (RTLS) is crucial for better monitoring of critical assets. Despite the challenge of selecting the right technology for specific needs from a wide range of indoor RTLS options, this study provides a solution to assist manufacturing companies in exploring and implementing IoT technologies for their RTLS needs.

Designing secure PUF-based authentication protocols for constrained environments.

Physical Unclonable Functions (PUFs) are widely used in cryptographic authentication and key-agreement protocols due to their unique physical properties. This article presents a comprehensive cryptanalysis of two recently developed authentication protocols, namely PLAKE and EV-PUF, both relying on PUFs. Our analysis reveals significant vulnerabilities in these protocols, including susceptibility to impersonation and key leakage attacks, which pose serious threats to the security of the underlying systems.

Deeper neural network models better reflect how humans cope with contrast variation in object recognition.

Visual inputs are far from ideal in everyday situations such as in the fog where the contrasts of input stimuli are low. However, human perception remains relatively robust to contrast variations. To provide insights about the underlying mechanisms of contrast invariance, we addressed two questions.

ECG Identification Based on the Gramian Angular Field and Tested with Individuals in Resting and Activity States.

In the last decade, biosignals have attracted the attention of many researchers when designing novel biometrics systems. Many of these works use cardiac signals and their representation as electrocardiograms (ECGs). Nowadays, these solutions are even more realistic since we can acquire reliable ECG records by using wearable devices.

A Recurrent Temporal Model for Semantic Levels Categorization Based on Human Visual System.

Humans can categorize an object in different semantic levels. For example, a dog can be categorized as an animal (superordinate), a terrestrial animal (basic), or a dog (subordinate). Recent studies have shown that the duration of stimulus presentation can affect the mechanism of categorization in the brain.

IoT in medical & pharmaceutical: Designing lightweight RFID security protocols for ensuring supply chain integrity.

Nowadays the sharing of trade in counterfeit and pirated goods is constantly growing and fake products are found in a large number of industries - particularly pharmaceuticals, food, and medical equipment - that can pose serious health and safety risks. With the intention of avoiding any loss of client confidence and any disclosure of sensitive information, Internet of Things (IoT) solutions are increasingly used to fulfill this need for a reliable and secure infrastructure in medical & pharmaceutical industry. When looking at the technologies used to identify products and packaging, balancing security and hardware limitations is often a difficult task and using cost-effective techniques such as bit-oriented lightweight functions is a challenge.

IoT Device Security: Challenging "A Lightweight RFID Mutual Authentication Protocol Based on Physical Unclonable Function".

With the exponential increase of Internet of things (IoT) connected devices, important security risks are raised as any device could be used as an attack channel. This preoccupation is particularly important with devices featuring limited processing power and memory capabilities for security purposes. In line with this idea, Xu et al.

Invariant object recognition is a personalized selection of invariant features in humans, not simply explained by hierarchical feed-forward vision models.

One key ability of human brain is invariant object recognition, which refers to rapid and accurate recognition of objects in the presence of variations such as size, rotation and position. Despite decades of research into the topic, it remains unknown how the brain constructs invariant representations of objects. Providing brain-plausible object representations and reaching human-level accuracy in recognition, hierarchical models of human vision have suggested that, human brain implements similar feed-forward operations to obtain invariant representations.

Hard-wired feed-forward visual mechanisms of the brain compensate for affine variations in object recognition.

Humans perform object recognition effortlessly and accurately. However, it is unknown how the visual system copes with variations in objects' appearance and the environmental conditions. Previous studies have suggested that affine variations such as size and position are compensated for in the feed-forward sweep of visual information processing while feedback signals are needed for precise recognition when encountering non-affine variations such as pose and lighting.

Average activity, but not variability, is the dominant factor in the representation of object categories in the brain.

To categorize the perceived objects, brain utilizes a broad set of its resources and encoding strategies. Yet, it remains elusive how the category information is encoded in the brain. While many classical studies have sought the category information in the across-trial-averaged activity of neurons/neural populations, several recent studies have observed category information also in the within-trial correlated variability of activities between neural populations (i.

Two RFID standard-based security protocols for healthcare environments.

Radio Frequency Identification (RFID) systems are widely used in access control, transportation, real-time inventory and asset management, automated payment systems, etc. Nevertheless, the use of this technology is almost unexplored in healthcare environments, where potential applications include patient monitoring, asset traceability and drug administration systems, to mention just a few. RFID technology can offer more intelligent systems and applications, but privacy and security issues have to be addressed before its adoption.

A note on the security of IS-RFID, an inpatient medication safety.

Objective: In this paper we investigate the security level of a comprehensive RFID solution to enhance inpatient medication safety, named IS-RFID, which has been recently proposed by Peris-Lopez et al.

Method: We analyses the security of the protocol against the known attacks in the context. The main target of this paper is to determine whether the new protocol provides the confidentiality property, which is expected to be provided by such a protocol.

On the designing of a tamper resistant prescription RFID access control system.

Recently, Chen et al. have proposed a novel tamper resistant prescription RFID access control system, published in the Journal of Medical Systems. In this paper we consider the security of the proposed protocol and identify some existing weaknesses.