Intermediate Attacks Research Articles

Mechanism of Electrocatalytic H2 Evolution, Carbonyl Hydrogenation, and Carbon-Carbon Coupling on Cu.

Aqueous-phase electrocatalytic hydrogenation of benzaldehyde on Cu leads not only to benzyl alcohol (the carbonyl hydrogenation product), but Cu also catalyzes carbon-carbon coupling to hydrobenzoin. In the absence of an organic substrate, H2 evolution proceeds via the Volmer-Tafel mechanism on Cu/C, with the Tafel step being rate-determining. In the presence of benzaldehyde, the catalyst surface is primarily covered with the organic substrate, while H* coverage is low. Mechanistically, the first H addition to the carbonyl O of an adsorbed benzaldehyde molecule leads to a surface-bound hydroxy intermediate. The hydroxy intermediate then undergoes a second and rate-determining H addition to its α-C to form benzyl alcohol. The H additions occur predominantly via the proton-coupled electron transfer mechanism. In a parallel reaction, the radical α-C of the hydroxy intermediate attacks the electrophilic carbonyl C of a physisorbed benzaldehyde molecule to form the C-C bond, which is rate-determining. The C-C coupling is accompanied by the protonation of the formed alkoxy radical intermediate, coupled with electron transfer from the surface of Cu, to form hydrobenzoin.

Secure Healthcare Model Using Multi-Step Deep Q Learning Network in Internet of Things

Internet of Things (IoT) is an emerging networking technology that connects both living and non-living objects globally. In an era where IoT is increasingly integrated into various industries, including healthcare, it plays a pivotal role in simplifying the process of monitoring and identifying diseases for patients and healthcare professionals. In IoT-based systems, safeguarding healthcare data is of the utmost importance, to prevent unauthorized access and intermediary assaults. The motivation for this research lies in addressing the growing security concerns within healthcare IoT. In this proposed paper, we combine the Multi-Step Deep Q Learning Network (MSDQN) with the Deep Learning Network (DLN) to enhance the privacy and security of healthcare data. The DLN is employed in the authentication process to identify authenticated IoT devices and prevent intermediate attacks between them. The MSDQN, on the other hand, is harnessed to detect and counteract malware attacks and Distributed Denial of Service (DDoS) attacks during data transmission between various locations. Our proposed method’s performance is assessed based on such parameters as energy consumption, throughput, lifetime, accuracy, and Mean Square Error (MSE). Further, we have compared the effectiveness of our approach with an existing method, specifically, Learning-based Deep Q Network (LDQN).

Efficient ECC-Based Authentication Scheme for Fog-Based IoT Environment

The rapid growth of cloud computing and Internet of Things (IoT) applications faces several threats, such as latency, security, network failure, and performance. These issues are solved with the development of fog computing, which brings storage and computation closer to IoT-devices. However, there are several challenges faced by security designers, engineers, and researchers to secure this environment. To ensure the confidentiality of data that passes between the connected devices, digital signature protocols have been applied to the authentication of identities and messages. However, in the traditional method, a user's private key is directly stored on IoTs, so the private key may be disclosed under various malicious attacks. Furthermore, these methods require a lot of energy, which drains the resources of IoT-devices. A signature scheme based on the elliptic curve digital signature algorithm (ECDSA) is proposed in this paper to improve the security of the private key and the time taken for key-pair generation. ECDSA security is based on the intractability of the Elliptic Curve Discrete Logarithm Problem (ECDLP), which allows one to use much smaller groups. Smaller group sizes directly translate into shorter signatures, which is a crucial feature in settings where communication bandwidth is limited, or data transfer consumes a large amount of energy. In this paper, we have chosen the safe curve types of elliptic-curve cryptography (ECC) such as M221, SECP256r1, curve 25519, Brainpool P256t1, and M-551. These types of curves are the most secure curves of other curves of ECC as their security is based on the complexity of the ECDLP of the curve. And these types of curves exceed the complexity of the ECDLP. A valid signature can be generated without reestablishing the whole private key. ECDSA ensures data security and successfully reduces intermediate attacks. The efficiency and effectiveness of ECDSA in the IoT environment are validated by experimental evaluation and comparison analysis. The results indicate that, in comparison to the two-party ECDSA and RSA, the proposed ECDSA decreases computation time by 65% and 87%, respectively. Additionally, as compared to two-party ECDSA and RSA, respectively, it reduces energy consumption by 77% and 82%.

Spoofing Traction Strategy Based on the Generation of Traction Code

Traction spoofing is an important component of Global Navigation Satellite System (GNSS) intermediate attacks, and the traction scheme directly determines the concealment of spoofing. However, spoofing via conventional traction strategies can be easily detected using Time of Arrival (TOA) and power detection. Based on a BPSK-modulated signal, a novel traction strategy using traction code is proposed to suppress part of the authentication signal and form an ideal correlation peak. This strategy was modeled and simulated to verify its theoretical feasibility. Effective spoofing data were generated based on the signal generation software to verify the spoofing effect with the reception of the software receiver. It can be inferred that no significant distortion occurred throughout the traction process, and the value range of the traction speed was expanded. The received results in different scenarios demonstrated that the observations’ Root-Mean-Square Error (RMSE) percentage change in the proposed strategy is significantly better than those of conventional strategies. A Ratio Test was also performed, verifying that the strategy can bypass Signal Quality Monitoring (SQM) detection. Meanwhile, the proposed strategy remained effective when the C/N0 increased to 60 dBHz. In summary, the proposed strategy exhibits destructiveness, concealment, and adaptability on the battlefield.

RETRACTED: Internet of Things security framework based on near field communication with Otway Rees protocol

AbstractInternet of Things (IoT) devices are crucial in different industries because they provide high‐functioning services to the IoT network connectivity. The IoT devices collect sensitive data, which comes under potential risk while transmitting data from one location to another. The data transmission is performed using various communication protocols that give security to the data. The intermediate attacks such as jamming, collision, flooding, worm‐hole, black‐hole and so forth create several security‐related issues. These intermediate attacks affect data privacy, trust, user identity, which completely affects the IoT device performance. So, this article introduces the near field communication (NFC) protocol with the Otway Rees protocol for making the secure communication process. In IoT applications based on short‐range communication, intermediate attacker issues have been reduced by combining NFC protocol features with Otway Rees protocol features. The NFC protocol provides baseline security trustworthiness while making the communication in the IoT environment cost‐effective. IoT communication is protected while cost‐effective using the security model, ensuring data integrity and confidentiality. In addition to this, the user and servers are authenticated for every session, which provides data security. Moreover, the discussed system is implemented using the NS2 simulation tool, ensuring security and trust with minimum complexity. Even in abnormal traffic conditions, our proposed method resulted in data transmission speeds (up to 289 Kb/s), and this feature can improve processing times.

Enhanced IoT Wi-Fi protocol standard’s security using secure remote password

In the Internet of Things (IoT) environment, a network of devices is connected to exchange information to perform a specific task. Wi-Fi technology plays a significant role in IoT based applications. Most of the Wi-Fi-based IoT devices are manufactured without proper security protocols. Consequently, the low-security model makes the IoT devices vulnerable to intermediate attacks. The attacker can quickly target a vulnerable IoT device and breaches that vulnerable device's connected network devices. So, this research suggests a password protection based security solution to enhance Wi-Fi-based IoT network security. This password protection approach utilizes the secure remote password protocol (SRPP) in Wi-Fi network protocols to avoid brute force attack and dictionary attack in Wi-Fi-based IoT applications. The performance of the IoT security solution is implemented and evaluated in the GNS3 simulator. The simulation analysis report shows that the suggested password protection approach supports scalability, integrity and data protection against intermediate attacks.

IoT network security using autoencoder deep neural network and channel access algorithm

Abstract Internet-of-Things (IoT) creates a significant impact in spectrum sensing, information retrieval, medical analysis, traffic management, etc. These applications require continuous information to perform a specific task. At the time, various intermediate attacks such as jamming, priority violation attacks, and spectrum poisoning attacks affect communication because of the open nature of wireless communication. These attacks create security and privacy issues while making data communication. Therefore, a new method autoencoder deep neural network (AENN) is developed by considering exploratory, evasion, causative, and priority violation attack. The created method classifies the transmission outcomes used to predict the transmission state, whether it is jam data transmission or sensing data. After that, the sensing data is applied for network training that predicts the intermediate attacks. In addition to this, the channel access algorithm is used to validate the channel for every access that minimizes unauthorized access. After validating the channel according to the neural network, data have been transmitted over the network. The defined process is implemented, and the system minimizes different attacks on various levels of energy consumption. The effectiveness of the system is implemented using TensorFlow, and the system ensures the 99.02% of detection rate when compared with other techniques.

Code-based encryption techniques with distributed cluster head and energy consumption routing protocol

Fog computing and the Internet of Things (IoT) played a crucial role in storing data in the third-party server. Fog computing provides various resources to collect data by managing data security. However, intermediate attacks and data sharing create enormous security challenges like data privacy, confidentiality, authentication, and integrity issues. Various researchers introduce several cryptographic techniques; security is still significant while sharing data in the distributed environment. Therefore, in this paper, Code-Based Encryption with the Energy Consumption Routing Protocol (CBE-ECR) has been proposed for managing data security and data transmission protocols using keyed-hash message authentication. Initially, the data have been analyzed, and the distributed cluster head is selected, and the stochastically distributed energy clustering protocol is utilized for making the data transmission. Code-driven cryptography relies on the severity of code theory issues such as disorder demodulation and vibration required to learn equivalence. These crypto-systems are based on error codes to build a single-way function. The encryption technique minimizes intermediate attacks, and the data have protected all means of transmission. In addition to data security management, the introduced CBE-ECR reduces unauthorized access and manages the network lifetime successfully, leading to the effective data management of 96.17% and less energy consumption of 21.11% than other popular methods.The effectiveness of the system is compared to the traditional clustering techniques.

Inside Back Cover: Boosting Photocatalytic Water Oxidation Over Bifunctional Rh0‐Rh3+ Sites (Angew. Chem. Int. Ed. 42/2021)

Bifunctional Rh0–Rh3+ sites anchored on Mo-doped BiVO4 show a high visible-light photocatalytic oxygen production activity, as reported by Peng Fei Liu, Zheng Jiang, Hua Gui Yang, and co-workers in their Research Article on page 22761. Operando XAFS results and DFT calculations illustrate the bifunctional OER mechanism on the Rh0–Rh3+ sites: the oxygen intermediate attacks the Rh3+ sites, facilitating a hydrogen atom transfer to the adjacent Rh0 sites, which synergistically optimizes the OER energetics.

Boosting Photocatalytic Water Oxidation Over Bifunctional Rh0 -Rh3+ Sites.

Photocatalytic water splitting provides an economically feasible way for converting solar energy into hydrogen. Great efforts have been devoted to developing efficient photocatalysts; however, the surface catalytic reactions, especially for the sluggish oxygen evolution reaction (OER), still remain a challenge, which limits the overall photocatalytic energy efficiency. Herein, we design a Rhn cluster cocatalyst, with Rh0 -Rh3+ sites anchoring the Mo-doped BiVO4 model photocatalytic system. The resultant photocatalyst enables a high visible-light photocatalytic oxygen production activity of 7.11 mmol g-1 h-1 and an apparent quantum efficiency of 29.37 % at 420 nm. The turnover frequency (TOF) achieves 416.73 h-1 , which is 378 times higher than that of the photocatalyst only with Rh3+ species. Operando X-ray absorption characterization shows the OER process on the Rh0 -Rh3+ sites. The DFT calculations further illustrate a bifunctional OER mechanism over the Rh0 -Rh3+ sites, in which the oxygen intermediate attacks the Rh3+ sites with assistance of a hydrogen atom transfer to the Rh0 sites, thus breaking the scaling relationship of various oxygen intermediates.

Boosting Photocatalytic Water Oxidation Over Bifunctional Rh0‐Rh3+ Sites

AbstractPhotocatalytic water splitting provides an economically feasible way for converting solar energy into hydrogen. Great efforts have been devoted to developing efficient photocatalysts; however, the surface catalytic reactions, especially for the sluggish oxygen evolution reaction (OER), still remain a challenge, which limits the overall photocatalytic energy efficiency. Herein, we design a Rhn cluster cocatalyst, with Rh0‐Rh3+ sites anchoring the Mo‐doped BiVO4 model photocatalytic system. The resultant photocatalyst enables a high visible‐light photocatalytic oxygen production activity of 7.11 mmol g−1 h−1 and an apparent quantum efficiency of 29.37 % at 420 nm. The turnover frequency (TOF) achieves 416.73 h−1, which is 378 times higher than that of the photocatalyst only with Rh3+ species. Operando X‐ray absorption characterization shows the OER process on the Rh0‐Rh3+ sites. The DFT calculations further illustrate a bifunctional OER mechanism over the Rh0‐Rh3+ sites, in which the oxygen intermediate attacks the Rh3+ sites with assistance of a hydrogen atom transfer to the Rh0 sites, thus breaking the scaling relationship of various oxygen intermediates.

RETRACTED ARTICLE: Creating Security Modelling Framework Analysing in Internet of Things Using EC-GSM-IoT

Internet of Things (IoT) placed a vital role in making effective communication because it consists of several interconnected smart devices. In IoT, device communication started via different communication protocols like Wi-Fi, ZigBee. During the communication process, smart devices are affected by intermediate attacks, which causes several communication vulnerabilities. Therefore, successful communication protocols have to be developed to reduce intermediate attacks like insider attacks, DDoS. To achieve this goal in this work, Extended Coverage-GSM-IoT protocol has been integrated with the wide-mouth frog protocol for making the secure communication process. This protocol improves the overall IoT device integrity protocol and enables mutual authentication while making the communication process. The WMFP protocol validates the user identity that leads to reduce the replay and eavesdropping attacks. Thus, the process ensures a feasible and secure IoT communication environment with minimum complexity.

Short TML occurred during percutaneous dilatational tracheostomy for long term invasive ventilation. The tube’s tip went into the mediastinum. The lesion was detected two days after tracheostomy and intermediate attacks of increased air way resistance. Intraluminal repair was performed with a 2/0 Vicryl thread with UCLX needle (Ethicon, Germany) using a 14 mm tracheoscope and the optical needle holder (KARL

Short TML occurred during percutaneous dilatational tracheostomy for long term invasive ventilation. The tube’s tip went into the mediastinum. The lesion was detected two days after tracheostomy and intermediate attacks of increased air way resistance. Intraluminal repair was performed with a 2/0 Vicryl thread with UCLX needle (Ethicon, Germany) using a 14 mm tracheoscope and the optical needle holder (KARL

Secure communication process in IoT using media gate network transmit protocol with reliable data transport protocol

Internet of things (IoT) is the important concept for making the effective and secure communication between networks. During the communication process the security and intermediate attack is one of the main issues because the communication may be used in various applications such as energy management, infrastructure analysis and environmental monitoring process, and so on. This issue has been overcome by applying the effective transmission protocol along with the secure encryption method. Initially, communication process is enhanced and making reliable with the help of the media gate network transmit protocol along with the reliable data transport protocol. In addition, the intermediate attacks present in the network communication process have been resolved by using the fuzzy soft multi-set blowfish encryption method. The application layer transmission protocol with the encryption method ensures the secured communication when compared to the other protocol based communication. Then the efficiency of the system is evaluated with the help of the experimental results in terms of the energy consumption and throughput metrics.

Spoofing Detection Algorithm Based on Pseudorange Differences.

Intentional spoofing interference can cause damage to the navigation terminal and threaten the security of a global navigation satellite system (GNSS). For spoofing interference, an anti-spoofing algorithm based on pseudorange differences for a single receiver is proposed, which can be used to detect simplistic and intermediate spoofing attacks, as well as meaconing attacks. Double-difference models using the pseudorange of two adjacent epochs are established followed by the application of Taylor expansion to the position relationship between the satellite and the receiver (or the spoofer). The authenticity of the signal can be verified by comparing the results of the proposed spoofing detection algorithm with the traditional least squares method. The results will differ when spoofing is present. The parameter setting of the proposed algorithm is introduced. The algorithm has the advantage of both simplicity and efficiency and needs only a single receiver and pseudorange data. A NovAtel receiver is adopted for the actual experiments. The Texas spoofing test battery (TEXBAT), as well as two other simulation experiments are used to verify the performance of the algorithm. The simulation results validate the feasibility and effectiveness of the algorithm.

Collaboration of Trusted Node and QoS Based Energy Multi Path Routing Protocol for Vehicular Ad Hoc Networks

In the recent past information transmission through the vehicular ad hoc network (VANET) playing a vital role due to increase in accident statistics. There are numerous networking and VANET protocols helpful to control the trust while transmitting the data from source to destination nodes in traffic environment. In spite of many existing protocols for analyzing the trust in the network, the challenge of routing overhead, high energy consumption and malicious attacks issues still continue in the communication. This research introduces the trust collaboration nodes and Quality of Service (QoS) with energy multipath routing protocol for transmitting the information through VANET. Initially, the trusted nodes have been collected for analyzing the neighbouring nodes and the information are transmitted using the proposed QoS based energy efficient multipath routing protocol. During this transmission, the multi path protocol eliminates the intermediate attacks effectively when compared with the other existing protocols. The Proposed protocol maintains the QoS while routing the information from source to destination and further the efficiency has been analyzed through simulation experiments and Montgomery multiplier based Elliptic Curve Cryptography (ECC) will be used in future for better security and privacy.

Maintaining Security and Privacy in Health Care System Using Learning Based Deep-Q-Networks.

In the recent past, Internet of Things (IoT) plays a significant role in different applications such as health care, industrial sector, defense and research etc.… It provides effective framework in maintaining the security, privacy and reliability of the information in internet environment. Among various applications as mentioned health care place a major role, because security, privacy and reliability of the medical information is maintained in an effective way. Even though, IoT provides the effective protocols for maintaining the information, several intermediate attacks and intruders trying to access the health information which in turn reduce the privacy, security and reliability of the entire health care system in internet environment. As a result and to solve the issues, in this research Learning based Deep-Q-Networks has beenintroduced for reducing the malware attacks while managing the health information. This method examines the medical information in different layers according to the Q-learning concept which helps to minimize the intermediate attacks with less complexity. The efficiency of the system has beenevaluated with the help of experimental results and discussions.

Particle bee optimized convolution neural network for managing security using cross-layer design in cognitive radio network

Cognitive radio (CR) is one of the promising technologies for better utilization of radio spectrum. The parameters like operating frequency, transmission power, type of modulation etc., extend a major contribution in CR. These parameters helps to transmit the information in communication environment. The CR monitors their own performance and subsequently reads the radio outputs in radio frequency environment in an effective manner. During the process of this cognitive communication, security is one of the major issues owing to the factors such as anomalous spectrum usage, hindrance in the identification of primary and secondary spectrum users. This paper introduces Cross-Layer Design Based Particle Bee optimized Convolution Neural Network (CLPBCNN) for managing the security issues present in the cognitive radio networks. Initially, user’s spectrum has been sensed based on the energy level with cyclostationary process which helps to analyze the primary user related radio features. Along with the extracted user features, authentication is handled by symmetric triple data encryption algorithm and the features are trained by proposed network which examines the intermediate attacks and malicious activities. Furthermore, an efficient multi-path energy routing protocol is proposed to monitor the neighboring nodes and spectrum usage for detecting the attacks in CR. This process is repeated continuously for creating the effective attack free cognitive radio based wireless communication system. Then the excellence of the system is evaluated and validated with the help of NS2 simulation tool and the efficiency is analyzed in terms of miss detection probability, route dis-connectivity ratio, and detection delay. The effective utilization of this cyclostationary and routing process leads to overall improved performance.

Enhancing Rumor Riding protocol in P2P network with Cryptographic puzzle through challenge question method

This research seeks is to investigate the Peer to Peer network topology and its custom behavior. The habitual effect of Peer to Peer network includes considering all the connected nodes as peers and these peers head-on with other peers to effectuate the tasks assigned to each one of them. The entire embrace of this network topology clings on to the heterogeneous sphere. Due to its comprehensive network topology and penchant features, the network is vulnerable to many castigating attacks. Furthermore, the possession attributed to the security traits of the network is comparatively tiny. Thus, this network topology is subjected to copious attacks. Rumor Riding (RR) is an anonymous and non-path based protocol. In this protocol, three nodes (including the Initiator, Intermediate, and Responder) are involved in sharing the information or searching the file. In some cases, the named three nodes may act as attackers leading to initiator attacks, intermediate attacks and responder attacks. The reason behind the argument is that RR protocol is based on an anonymous method that tends to hide the information from source to destination without authentication. Hence, the network performance gradually becomes ineffective. The main intent of this paper is to explore the ways and means to prevent all the stated onslaughts. To achieve this, we have developed an attack prevention protocol. The protocol involves the Reliable Rumor Riding Protocol in P2P Network through the Cryptographic Puzzle attributed to the Challenge Question Method. Furthermore, we have augmented the performance and measured. Hence, in this quintessential way, the network operation is proved to be secured and authenticated.

Enhancing trust in mobile ad-hoc network using trust and dynamic with energy efficient multipath routing protocol

Mobile ad-hoc network is one of the most effective self-configuring and infrastructure less based communication networks. During the communication process, trust between the networks is placed an important issue due to the intermediate attacks. Several types of research introduce the trust-based communication protocol for overcoming privacy issues but still, the efficiency of the trust is one of the major problems. So, this paper introduces the optimised trust and energy efficient multipath routing protocol based on the maintained energy of the node to overcome the issues. The intermediate attack in the network has been eliminated with the help of the trust and dynamic with energy efficient multipath routing protocol. The established trust has been used for a multipath routing protocol. Then, the efficiency of the system is analysed using the packet delivery ratio and security. The method ensures the trust in the network by applying the computation, aggregation, and propagation and prediction process.