G protein activation by different μ-selective opioid agonists was examined in rat thalamus, SK-N-SH cells, and μ-opioid receptor-transfected mMOR-CHO cells using agonist-stimulated guanosine-5′-<i>O</i>-(γ-thio)-triphosphate ([³⁵S]GTPγS) binding to membranes the presence of excess GDP. [d-Ala²,<i>N</i>-MePhe⁴,Gly⁵-ol]Enkephalin (DAMGO) most efficacious agonist thalamus followed (in rank order) fentanyl = morphine ≫ buprenorphine. In expressing a...

Encrypted traffic classification is receiving widespread attention from researchers and industrial companies. However, the existing methods only extract flow-level features, failing to handle short flows because of unreliable statistical properties, or treat header payload equally, mine potential correlation between bytes. Therefore, in this paper, we propose a byte-level graph construction approach based on point-wise mutual information (PMI), model named Temporal Fusion Encoder using Graph...

Botnets are one of predominant threats to Internet security. To date, machine learning technology has wide application in botnet detection because that it is able summarize the features existing attacks and generalize never-before-seen families. However, recent works adversarial have shown attackers bypass model by constructing specific samples, which due many algorithms vulnerable almost imperceptible perturbations their inputs. According degree adversaries' knowledge about model, can be...

Abstract As a progressive security strategy, the zero trust model has attracted notable attention and importance within realm of network security, especially in context Internet Things (IoT). This paper aims to evaluate current research regarding highlight its practical applications IoT sphere through extensive bibliometric analysis. We also delve into vulnerabilities explore potential role mitigating these risks via thorough review relevant schemes. Nevertheless, challenges associated with...

Transactions in the cryptocurrency market has been extremely hot recent years, with price of climbing all way. Hackers have turned their attentions to cryptocurrencies, and used various means acquire cryptocurrencies illegally, which caused huge losses victims. Some browsers block malicious mining activities from network protocol level, but they do not ability detect samples themselves, it is difficult make effective detection homogenous layer. To solve these problems, based on attack...

Abstract: Endomorphin‐1 is a peptide whose binding selectivity suggests role as an endogenous ligand at μ‐opioid receptors. In the present study, effect of endomorphin‐1 on μ receptor‐coupled G proteins was compared with that agonist DAMGO by using agonist‐stimulated [ 35 S]GTPγS in rat brain. autoradiography revealed similar localization and DAMGO‐stimulated areas including thalamus, caudate‐putamen, amygdala, periaqueductal gray, parabrachial nucleus, nucleus tractus solitarius. Naloxone...

Sodium ions inhibit spontaneous G i /G o ‐coupled receptor activity and promote agonist‐induced responses in vitro . The effects of sodium on the relative efficacy opioid agonists for G‐protein activation was measured by guanosine‐5′‐ O ‐(γ‐ 35 S)‐triphosphate ([ S]‐GTPγS) binding membranes from two μ‐opioid receptor‐containing systems: CHO cells stably transfected with mouse μ receptors (mMOR‐CHO cells) rat thalamus. NaCl inhibited basal [ S]‐GTPγS both systems, this effect partially...

Obtaining a comprehensive model of large and complex ground typically is crucial for autonomous driving both in urban countryside environments. This paper presents an improved segmentation method 3D LIDAR point clouds. Our approach builds on polar grid map, which divided into some sectors, then 1D Gaussian process (GP) regression Incremental Sample Consensus (INSAC) algorithm used to extract every sector. Experiments are carried out at the vehicle different outdoor scenes, results compared...

How to discover router vulnerabilities effectively and automatically is a critical problem ensure network information security.Previous research on security mostly about the technology of exploiting known flaws routers.Fuzzing famous automated vulnerability finding technology; however, traditional Fuzzing tools are designed for testing applications or other software.These not partly suitable routers.This paper designs framework discovering protocol vulnerabilities, proposes mathematical...

Java is one of the preferred options modern developers and has become increasingly more prominent with prevalence open-source culture. Thanks to serialization deserialization features, programs have flexibility transmit object data between multiple components or systems, which significantly facilitates development. However, features may also allow attackers construct gadget chains lead vulnerabilities. Due highly flexible customizable nature deserialization, finding an exploitable chain...

Fuzz testing has been widely used in practice to detect software vulnerabilities. Traditional fuzzing tools typically use blocks model program input. Despite the demonstrated success of this approach, its effectiveness is inherently limited when applied test programs that process grammatical inputs, where input data are mainly human-readable text with complex structures specified by a formal grammar. In paper we present BlendFuzz, fuzz framework grammar-aware. It works breaking set existing...

As web attackers hide themselves by using multi-step springboard (e.g., VPN, encrypted proxy) or anonymous network (i.e. Tor network), it raises a big obstacle for traceability and forensics. Furthermore, traditional forensics methods based on traffic log analysis are just useful analyzing attack events but useless fingerprinting an attacker. Because of this, the browser technique which makes use slight differences among different browsers was come up with. However, although this is...

As the cyber security has attracted great attention in recent years, and with all kinds of tools' (such as Network Agent, VPN so on) help, traditional methods tracking users like log analysis cookie have been not that effective. Especially for some privacy sensitive who changed their browser configuration frequently to hide themselves. The Browser Fingerprinting technology proposed by Electronic Frontier Foundation (EFF) gives a new approach users, then our team designed an enhanced...

Machine learning(ML)-based botnet detection methods have become mainstream in corporate practice. However, researchers found that ML models are vulnerable to adversarial attacks, which can mislead the by adding subtle perturbations sample. Due complexity of traffic samples and special constraints keep malicious functions, no substantial research has been conducted field, where evasion attacks caused carefully crafted examples may directly make ML-based detectors unavailable cause significant...

Abstract Software-defined networking (SDN), a novel network paradigm, separates the control plane and data into different equipment to realize flexible of traffic. Its excellent programmability global view present many new opportunities. DDoS detection under SDN context is an important challenging research field. Some previous works attempted collect analyze statistics related flows, usually recorded in switches, address threats. In contrast, other applied machine learning-based solutions...