Research on identity authentication methods for IoT devices in smart tourism

The internet of things (IoT) is a key trend in smart tourism, involving multiple stakeholders like government management, public cloud platforms, device manufacturers, scenic areas, and tourists. IoT devices, often deployed in public spaces, are vulnerable to physical attacks, making identity authentication critical for security. A certificate-free identity authentication method based on administrative applications was proposed, using MQTT protocol message queues to maintain device security status, addressing issues with low-power devices in sleep mode. Based on national cryptographic algorithms, secure and controllable IoT information was ensured. Performance evaluations show that it effectively helps prevent security threats, achieving an average authentication accuracy of 99.7%, with embedded RAM and FLASH usage not exceeding 35 KB and 30 KB, suitable for smart tourism applications

Research on side-channel attacks and defense methods for IoT devices

Internet of things (IoT) devices are typically implemented using microcontrollers with limited computational capabilities, which necessitate the use of lightweight symmetric encryption algorithms to ensure data security. Due to their inherent characteristics, these devices can only be deployed in open environments, making them highly vulnerable to side-channel attacks. To address this issue, experiments were conducted on a self-designed side-channel attack validation platform, where a secure key management scheme and an improved S-box design were proposed as countermeasures against side-channel attacks. The validation platform consisted of a two-stage differential amplifier and an anti-interference finite impulse response (FIR) filter, which were capable of capturing subtle power consumption fluctuations. A two-round correlated energy attack targeting lightweight encryption algorithms was also designed. By evaluating the confidence of the correct key correlation coefficient, after 10 000 attacks on 3 000 power consumption traces of the PRESENT algorithm, a success rate of over 96% is achieved, with the mean correlation of the correct key exceeding 0.6. At a 95% confidence level, a narrow confidence interval is obtained. In contrast, when the improved algorithm is used in the same experiment, the attack success rate is only 9.12%

Stylization of a Seismic Image Profile Based on a Convolutional Neural Network

Seismic data are widely used in oil, gas, and other kinds of mineral exploration and development. However, due to low artificial interpretation accuracy and small sample sizes, seismic data may not meet the needs of convolutional neural network training. There are major differences between optical image and seismic data, making it difficult for a model to learn seismic data characteristics. Therefore, a style transfer network is necessary to make the styles of optical image and seismic data more similar. Since the stylization effect of a seismic section is similar to that of most art styles, based on an in-depth study of image style transfer, this paper compared the effects of various style transfer models, and selected a Laplacian pyramid network to carry out a study of seismic section stylization. It transmits low-resolution global style patterns through a drafting network, revises high-resolution local details through correction networks, and aggregates all pyramid layers to output final stylized images of seismic profiles. Experiments show that this method can effectively convey the whole style pattern without losing the original image content. This style transfer method, based on the Laplacian pyramid network, provides theoretical guidance for the fast and objective application of the model to seismic data features

Side Effects of Opioids Are Ameliorated by Regulating TRPV1 Receptors

Humans have used opioids to suppress moderate to severe pain for thousands of years. However, the long-term use of opioids has several adverse effects, such as opioid tolerance, opioid-induced hyperalgesia, and addiction. In addition, the low efficiency of opioids in controlling neuropathic pain limits their clinical applications. Combining nonopioid analgesics with opioids to target multiple sites along the nociceptive pathway may alleviate the side effects of opioids. This study reviews the feasibility of reducing opioid side effects by regulating the transient receptor potential vanilloid 1 (TRPV1) receptors and summarizes the possible underlying mechanisms. Blocking and activating TRPV1 receptors can improve the therapeutic profile of opioids in different manners. TRPV1 and μ-opioid receptors are bidirectionally regulated by β-arrestin2. Thus, drug combinations or developing dual-acting drugs simultaneously targeting μ-opioid and TRPV1 receptors may mitigate opioid tolerance and opioid-induced hyperalgesia. In addition, TRPV1 receptors, especially expressed in the dorsal striatum and nucleus accumbens, participate in mediating opioid reward, and its regulation can reduce the risk of opioid-induced addiction. Finally, co-administration of TRPV1 antagonists and opioids in the primary action sites of the periphery can significantly relieve neuropathic pain. In general, the regulation of TRPV1 may potentially ameliorate the side effects of opioids and enhance their analgesic efficacy in neuropathic pain.</jats:p

Side Effects of Opioids Are Ameliorated by Regulating TRPV1 Receptors

Humans have used opioids to suppress moderate to severe pain for thousands of years. However, the long-term use of opioids has several adverse effects, such as opioid tolerance, opioid-induced hyperalgesia, and addiction. In addition, the low efficiency of opioids in controlling neuropathic pain limits their clinical applications. Combining nonopioid analgesics with opioids to target multiple sites along the nociceptive pathway may alleviate the side effects of opioids. This study reviews the feasibility of reducing opioid side effects by regulating the transient receptor potential vanilloid 1 (TRPV1) receptors and summarizes the possible underlying mechanisms. Blocking and activating TRPV1 receptors can improve the therapeutic profile of opioids in different manners. TRPV1 and mu-opioid receptors are bidirectionally regulated by beta-arrestin2. Thus, drug combinations or developing dual-acting drugs simultaneously targeting mu-opioid and TRPV1 receptors may mitigate opioid tolerance and opioid-induced hyperalgesia. In addition, TRPV1 receptors, especially expressed in the dorsal striatum and nucleus accumbens, participate in mediating opioid reward, and its regulation can reduce the risk of opioid-induced addiction. Finally, co-administration of TRPV1 antagonists and opioids in the primary action sites of the periphery can significantly relieve neuropathic pain. In general, the regulation of TRPV1 may potentially ameliorate the side effects of opioids and enhance their analgesic efficacy in neuropathic pain.</p