Integrity Of Transmitted Data Research Articles

Implementing optimization and fine-tuning emergency response strategies in cryptographically enhanced IoT-infused medical infrastructure for rapid response

In today’s healthcare landscape, connecting medical facilities to the Internet of Things (IoT) has led to transformative changes. This study focuses on optimizing and refining emergency response strategies within IoT-enabled medical systems through cryptographic improvements. The proposed framework aims to strengthen rapid response mechanisms to better handle critical scenarios more efficiently. Using cryptographic techniques ensures the security and integrity of data transmission, protecting sensitive medical information. Our approach involves developing a sophisticated optimization algorithm tailored for emergency situations’ unique demands. This algorithm refines response strategies based on real-time data collected from IoT sensors, allowing dynamic adjustment to evolving conditions. Additionally, cryptographic protocols reinforce the communication channels, reducing the risk of unauthorized access or data manipulation. Through simulation and actual validation, the effectiveness of our proposed framework is demonstrated in enhancing medical infrastructure’s responsiveness during emergencies. By combining IoT capabilities with cryptographic measures, this research contributes to more resilient and secure emergency response systems’ evolution, ultimately advancing healthcare delivery’s effectiveness in critical situations.

Quantum Key Distribution-based Techniques in IoT

Quantum key distribution (QKD) is a cryptographic technique that creates a secure channel of communication between two parties by applying the ideas of quantum physics. QKD ensures the confidentiality and integrity of data transmission by providing a unique key that the intended recipient can only access. Secure communication has become paramount with the proliferation of IoT (Internet of Things) devices. IoT devices have confined computational power and storage, making them vulnerable to attacks. QKD provides a safe and efficient solution for securing communication between IoT devices. This paper examines how QKD can be utilized in IoT, discussing its benefits and limitations, followed by the discussion on various QKD protocols suitable for IoT devices. In addition, the paper demonstrates that QKD is a promising solution for securing IoT communication, and its adoption significantly enhances the security and reliability of IoT networks.

Challenges of IoT Identification and Multi-Level Protection in Integrated Data Transmission Networks Based on 5G/6G Technologies

This paper illustrates the main problematic issues of minimizing technological risks in the construction of an integrated architecture for the protection of a “smart habitat” (SH). We analyze the use of the IoT to identify both object hazards and the categorization of switching detection in information collection and processing centers. The article proposes wired and wireless data-transmission systems for the required level of efficiency as well as SH protection. Particular attention is paid to the organization of multi-level protection of promising 5G/6G cellular networks based on the analysis of the security threat landscape.

Link-State Aware Hybrid Routing in the Terrestrial–Satellite Integrated Network

In this paper, we study data transmission in the Terrestrial-Satellite Integrated Network (TSIN), where terrestrial networks and satellites are combined together to provide seamless global network services for ground users. However, efficiency of the data transmission is limited by the time-varying inter-satellite link connection and intermittent terrestrial-satellite link connection. Therefore, we propose a link-state aware hybrid routing algorithm, which selects the integrated data transmission path adaptively in this paper. First of all, a space-time topology model is constructed to represent the dynamic link connections in TSIN. Thus, the transmission delay can be analyzed accordingly, and the data transmission problem can then be formulated. To balance the effectiveness and accuracy of searching a hybrid path, we carefully discuss the optimization of space-time topology updating, and propose an inter-satellite link selection algorithm. For the terrestrial-satellite link in hybrid routing, the data transmission problem is transformed into a weighted bipartite graph matching problem and solved with a Kuhn-Munkres-based link selection algorithm. To verify the effectiveness of our proposed routing algorithm, extensive simulations are conducted based on a realistic Hongyun constellation project. Results show that the network performance is improved with respect to data transmission delay, packet loss rate, and throughput.

Локальное местоопределение приемника связи и проблема многолучевости в сложных условиях

In conditions when the signals of satellite navigation systems are unavailable or distorted, the receiver positioning task could be solved by local positioning system with an integrated data transmission channel. However, when such a system operates in various environments, a lot of multipath signals might appear, which strongly distort delay and phase measurements, on the basis of which the receiver coordinates are calculated. The accuracy of measurements can be significantly increased by introducing measurement redundancy by using the signal reflection properties and increasing the tracking channels on the receiver. In this article, a technique is proposed for creating and using the redundancy of phase measurements, as well as the phase derivatives differences of the local positioning system signals. This technique is based on the effects of signal reflection. An algorithm is proposed for estimating the intensity of the relative acceleration of a moving object, which makes it possible, using the threshold method, to switch between receiver channels at the moments when abnormal spikes appears because of the influence of a multipath signal propagation channel. An algorithm for smoothing transitions between antennas is also proposed using cubic spline interpolation. The obtained methods and algorithms, using two receiving antennas with a single phase center, make it possible to exclude about 80% of spikes caused by multipath effects from estimates of the relative velocity of a moving object, and also provide a basis for developing more advanced methods for using redundancy and further research in this area.

A PUF-based and cloud-assisted lightweight authentication for multi-hop body area network

Wireless sensor technology plays an important role in the military, medical, and commercial fields nowadays. Wireless Body Area Network (WBAN) is a special application of the wireless sensor network in human health monitoring, through which patients can know their physical condition in real time and respond to emergencies on time. Data reliability, guaranteed by the trust of nodes in WBAN, is a prerequisite for the effective treatment of patients. Therefore, authenticating the sensor nodes and the sink nodes in WBAN is necessary. This paper proposes a lightweight Physical Unclonable Function (PUF)-based and cloud-assisted authentication mechanism for multi-hop body area networks, which compared with the star single-hop network, can enhance the adaptability to human motion and the integrity of data transmission. Such authentication mechanism can significantly reduce the storage overhead and resource loss in the data transmission process.

An efficient privacy-preserving data query and dissemination scheme in vehicular cloud

Vehicular Cloud (VC) improves the utilization of idle resources in vehicles by providing data services for other vehicles or entities such as data computing and storage. However, the vehicles in the VC still face privacy and security issues, especially when querying data from the road side unit. To this end, in this paper, we propose an efficient privacy-preserving data query and dissemination scheme, named EPDQD, for VC. More precisely, by using the lightweight homomorphic encryption technique and the Chinese Remainder Theorem, the road side unit can aggregate and recover multiple data query requests without knowing the linkability of the data query request and its origin vehicle. EPDQD also adopts the message authentication code and non-interactive secure session keys to achieve the authentication of data query requests and the integrity of data transmission. Detailed security analysis indicates that EPDQD can resist various security threats. In addition, the performance evaluations demonstrate that EPDQD can significantly reduce computation complexity and communication overhead.

Research on power regulation service data transmission path optimisation method

Owing to the large amount of transmission data and transmission paths between equipment and applications in the power grid control centre, it is easy to cause problems such as packet loss and incomplete data transmission. An improved Apriori algorithm is proposed to mine multi-dimensional data association rules when multiple service devices are running in parallel, then optimise the discontinuous data path transmission based on the ant colony algorithm. The ant colony migration probability is used to calculate the pheromone concentration value of the ant on the discontinuous data path in a fixed period, plan the ant travel path, use the direction factor to adjust the discontinuous data transmission path appropriately, determine the optimal path, and realise the mining optimisation. Simulation results show that the proposed method can effectively improve the convergence speed of discontinuous data transmission, reduce the delay time of the data transmission network, and ensure the integrity of data transmission.

Fuzzy Based Data Gathering Model for Improving Network Lifetime in ADHOC Networking

In Adhoc Wireless Sensor Networks (AWSN), nodes are moving with less or high mobility. It is very difficult to Quality of Service (QoS) to achieve network performance. Paths can be identified based on network model and stable route formation. In a cluster region, data gathering ratio can be easily achieved but difficult to reach maximum level. In existing schemes, balancing between data gathering and security was not attained. In this paper, Fuzzy based Secure Data Gathering Approach (FSDGA) is proposed based on TDMA based scheduling and Asymmetric key crypto model. This approach consists of three phases. In first phase, cluster formation and cluster head election is done based on calculation of remaining energy and stability of nodes. In second phase, secure routes are identified with constant key metrics. In third phase, Fuzzy integrated Data transmission phase is installed to protect the data from attackers and improve the data collection rate. The performance of FSDGA is analysed using simulation tool in terms of energy conservation rate, propagation delay, data confidential rate, control overhead and data gathering ratio.

Vehicle Text Data Compression and Transmission Method Based on Maximum Entropy Neural Network and Optimized Huffman Encoding Algorithms

Because of the continuous progress of vehicle hardware, the condition where the vehicle cannot load a complex algorithm no longer exists. At the same time, with the progress of vehicle hardware, the number of texts shows exponential growth in actual operation. In order to optimize the efficiency of mass data transmission in actual operation, this paper presented the text information (including position information) of the maximum entropy principle of a neural network probability prediction model combined with the optimized Huffman encoding algorithm, optimization from the exchange of data to data compression, transmission, and decompression of the whole process. The test results show that the text type vehicle information based on compressed algorithm to optimize the algorithm of data compression and transmission can effectively realize data compression. It can also achieve a higher compression rate and data transmission integrity, and after decompression it can basically guarantee no distortion. The method proposed in this paper is of great significance for improving the transmission efficiency of vehicle text information, improving the interpretability and integrity of text information, realizing vehicle monitoring, and grasping real-time traffic conditions.

Vehicle Information Influence Degree Screening Method Based on GEP Optimized RBF Neural Network

Due to the continuous progress in the field of vehicle hardware, the condition that a vehicle cannot load a complex algorithm no longer exists. At the same time, with the progress in the field of vehicle hardware, a number of studies have reported exponential growth in the actual operation. To solve the problem for a large number of data transmissions in an actual operation, wireless transmission is proposed for text information (including position information) on the basis of the principles of the maximum entropy probability and the neural network prediction model combined with the optimization of the Huffman encoding algorithm, from the exchange of data to the entire data extraction process. The test results showed that the text-type vehicle information based on a compressed algorithm to optimize the algorithm of data compression and transmission could effectively realize the data compression, achieve a higher compression rate and data transmission integrity, and after decompression guarantee no distortion. Therefore, it is important to improve the efficiency of vehicle information transmission, to ensure the integrity of information, to realize the vehicle monitoring and control, and to grasp the traffic situation in real time.

High-speed and Long-reach Hybrid AMI–WDM–PI Inter-satellite Communication System

AbstractIn the current context of high-altitude platform communication system, inter-satellite communication is remarkable and highly effective. The present work aims to develop an integrated data transmission system incorporating alternate mark inversion, wavelength-division multiplexing, and polarization interleaving scheme for transmitting data of eight channels, each carrying 20 Gbps data over inter-satellite link of 5,000 km. The performance of the integrated data transmission of 160 Gbps data up to 5,000 km will be evaluated by means of signal-to-noise ratio, total received power, and eye diagram.

Design and implementation of real-time continuous glucose monitoring instrument

Real-time continuous glucose monitoring can help diabetics to control blood sugar levels within the normal range. However, in the process of practical monitoring, the output of real-time continuous glucose monitoring system is susceptible to glucose sensor and environment noise, which will influence the measurement accuracy of the system. Aiming at this problem, a dual-calibration algorithm for the moving-window double-layer filtering algorithm combined with real-time self-compensation calibration algorithm is proposed in this paper, which can realize the signal drift compensation for current data. And a real-time continuous glucose monitoring instrument based on this study was designed. This real-time continuous glucose monitoring instrument consisted of an adjustable excitation voltage module, a current-voltage converter module, a microprocessor and a wireless transceiver module. For portability, the size of the device was only 40 mm × 30 mm × 5 mm and its weight was only 30 g. In addition, a communication command code algorithm was designed to ensure the security and integrity of data transmission in this study. Results of experiments in vitro showed that current detection of the device worked effectively. A 5-hour monitoring of blood glucose level in vivo showed that the device could continuously monitor blood glucose in real time. The relative error of monitoring results of the designed device ranged from 2.22% to 7.17% when comparing to a portable blood meter.

Influence of Transmitting Pointing Errors on High Speed WDM-AMI-Is-OWC Transmission System

AbstractInter-satellite communication is one of the revolutionary techniques that can be used to transmit the high speed date between satellites. However, space turbulences such as transmitting pointing errors play a significant role while designing inter-satellite communication systems. Those turbulences cause shutdown of inter-satellite link due to increase of attenuation during data transmission through link. The present work aims to develop an integrated data transmission system incorporating alternate mark inversion (AMI), wavelength division multiplexing (WDM), and polarization interleaving (PI) scheme for transmitting data 160 Gbps over inter-satellite link of 1,000 km under the influence of space turbulences. The performance of the integrated data transmission of 160 Gbps data up to 1,000 km will be evaluated under the influence of space turbulences by means of signal to noise ratio (SNR), total received power, bit error rate and eye diagram.

Mobility Prediction Based Joint Stable Routing and Channel Assignment for Mobile Ad Hoc Cognitive Networks

Link instability and channel interference cause significant performance degradation to mobile ad hoc cognitive networks (MACNets). Existing work designs routing and assigns channels separately or does not consider mobility prediction and channel vacation to primary nodes. In this paper, we investigate how to jointly optimize route setup and channel assignment. Firstly, we propose an integrated data transmission cost (IDTC) to quantitatively measure the communication quality of links. This novel routing metric IDTC integratively considers 1) node mobility, 2) co-channel interference among primary and cognitive nodes, 3) relay workload on a specified channel, and 4) distance between the relay and the destination node. We, then, design channel assignment algorithms that completely avoid the interference with primary nodes and minimize the conflict to cognitive nodes. Finally, we propose a joint stable routing and channel assignment (J-SRCA) protocol based on mobility prediction for the network throughput maximization. In our J-SRCA, each link selected hop by hop is simultaneously assigned an interference-avoiding channel during a route setup. NS2-based simulation results demonstrate that our J-SRCA significantly improves various network performance, and the higher interference degree cognitive networks experience, the more improvement our J-SRCA will bring to the networks.

Secured Web Service Communication using Attribute based Encryption and Outsource Decryption with Trusted Certificate Authorities (ABE-TCA)

Web services are one of the most aspired technologies in IT industry and more companies are adopting concepts and strategies used in web services for their businesses. User‘s set of attributes paves way for encryption and decryption of data by employing impregnable Attribute Based Encryption (ABE) for defended web service communication, which intensifies its privacy and security. In the existing ABE scheme, decryption involves an expensive process and increase the complexity of the access policy. To overcome the decryption overhead, outsourced decryption is used to authenticate the untrusted servers. The transformation key is responsible for reducing the decryption overhead by translating the complex ciphertext into simple ciphertext based on the user‘s attributes, and the overhead for the conversion of ciphertext to plaintext is acceptably minimal. Kerberos is incorporated to generate a ticket granting service that is used to verify authentication database and after verification of both parties, replies to the requested user for authentication. Furthermore to secure outsourcing agents, Certificate Authority is used to segregate unauthorized users. During data transmission integrity of the data can be verified by hashing algorithms.

A novel dynamic multi-service multi-grade encryption scheme used in EPON

Ethernet Passive optical network (EPON) considered as an efficient solution for high-speed bandwidth data transmission, is a promising candidate for next generation access network with safety problems such as eavesdropping, forgery and tampering because of its point-to-multipoint (P2MP) shared topology structure and broadcasted data pattern in the downstream direction. Besides, under multi-service circumstances, both encrypting efficiency and effective transmission of high-speed data can be difficult to be guaranteed when traditional single static encryption (TSSE) mechanism focusing on only one encryption method based on DES, AES or TAES for all business flows is adopted. To solve these problems, a multi-service multi-grade encryption (MSMGE) mechanism is presented. In MSMGE, service flows from providers are first divided into four queues according to differentiated service (DiffServ) model, then encrypted by calling relative encryption method on the basis of different security needs of different services and the simulation results indicate the validity of the proposed MSMGE mechanism in packet loss rate and integrity of data transmission.

Botnet detection techniques: review, future trends, and issues

In recent years, the Internet has enabled access to widespread remote services in the distributed computing environment; however, integrity of data transmission in the distributed computing platform is hindered by a number of security issues. For instance, the botnet phenomenon is a prominent threat to Internet security, including the threat of malicious codes. The botnet phenomenon supports a wide range of criminal activities, including distributed denial of service (DDoS) attacks, click fraud, phishing, malware distribution, spam emails, and building machines for illegitimate exchange of information/materials. Therefore, it is imperative to design and develop a robust mechanism for improving the botnet detection, analysis, and removal process. Currently, botnet detection techniques have been reviewed in different ways; however, such studies are limited in scope and lack discussions on the latest botnet detection techniques. This paper presents a comprehensive review of the latest state-of-the-art techniques for botnet detection and figures out the trends of previous and current research. It provides a thematic taxonomy for the classification of botnet detection techniques and highlights the implications and critical aspects by qualitatively analyzing such techniques. Related to our comprehensive review, we highlight future directions for improving the schemes that broadly span the entire botnet detection research field and identify the persistent and prominent research challenges that remain open.

Data hiding of high compression ratio in VQ indices with neighboring correlations

As the progressive development of information and communication technology, the security and integrity of data transmission through public network have become important issues. Thus information hiding for images is one of the main research issues to maintain the data security and integrity. This paper proposed a data hiding method on the indices of VQ compression. For an index table of VQ compression, neighboring indices have similar index values in a great chance. Exploiting neighboring correlation among VQ indices, the proposed data hiding can enhance the embedding capacity and bit rate of encoding. In addition, our method can use the output bit stream to reconstruct the cover image. Experimental results show the proposed scheme performs better in average comparing with Lee et al.'s method [9] in 2013.

Forecasting of Information Security Related Incidents: Amount of Spam Messages as a Case Study

With the increasing demand for services provided by communication networks, quality and reliability of such services as well as confidentiality of data transfer are becoming ones of the highest concerns. At the same time, because of growing hacker's activities, quality of provided content and reliability of its continuous delivery strongly depend on integrity of data transmission and availability of communication infrastructure, thus on information security of a given IT landscape. But, the amount of resources allocated to provide information security (like security staff, technical countermeasures and etc.) must be reasonable from the economic point of view. This fact, in turn, leads to the need to employ a forecasting technique in order to make planning of IT budget and short-term planning of potential bottlenecks. In this paper we present an approach to make such a forecasting for a wide class of information security related incidents (ISRI) — unambiguously detectable ISRI. This approach is based on different auto regression models which are widely used in financial time series analysis but can not be directly applied to ISRI time series due to specifics related to information security. We investigate and address this specifics by proposing rules (special conditions) of collection and storage of ISRI time series, adherence to which improves forecasting in this subject field. We present an application of our approach to one type of unambiguously detectable ISRI — amount of spam messages which, if not mitigated properly, could create additional load on communication infrastructure and consume significant amounts of network capacity. Finally we evaluate our approach by simulation and actual measurement.