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Artykuły w czasopismach na temat „Resource consumption attack”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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1

Gao, Minyan, Liton Kumar Biswas, Navid Asadi, and Domenic Forte. "Detour-RS: Reroute Attack Vulnerability Assessment with Awareness of the Layout and Resource." Cryptography 8, no. 2 (2024): 13. http://dx.doi.org/10.3390/cryptography8020013.

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Recent decades have witnessed a remarkable pace of innovation and performance improvements in integrated circuits (ICs), which have become indispensable in an array of critical applications ranging from military infrastructure to personal healthcare. Meanwhile, recent developments have brought physical security to the forefront of concern, particularly considering the valuable assets handled and stored within ICs. Among the various invasive attack vectors, micro-probing attacks have risen as a particularly menacing threat. These attacks leverage advanced focused ion beam (FIB) systems to enabl

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Moataz, H. Khalil, Azab Mohamed, Elsayed Ashraf, Sheta Walaa, Gabr Mahmoud, and S. Elmaghraby Adel. "MAINTAINING CLOUD PERFORMANCE UNDER DDOS ATTACKS." International Journal of Computer Networks & Communications (IJCNC) 11, no. 6 (2019): 1–22. https://doi.org/10.5281/zenodo.3564217.

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The popularity of cloud computing has been growing where the cloud became an attractive alternative rather than classic information processing system. The distributed denial of service (DDoS) attack is one of the famous attacks to cloud computing. This paper proposes a Multiple Layer Defense (MLD) scheme to detect and mitigate DDoS attacks which due to resource depletion. The MLD consists of two layers. The first layer has an alarm system send alarms to cloud management when DDoS attacks start. The second layer includes an anomaly detection system detects VM is infected by DDoS attacks. Also,M

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Padmaja, K., and K. Padmaja. "Radial Basis Kernel Regressive Feature Extraction and Robert Ensembled Brown Boost Classifier for Attack Detection in Cloud Environment." Webology 18, no. 2 (2021): 41–59. http://dx.doi.org/10.14704/web/v18i2/web18306.

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Cloud computing shares the resource in information technology field. The existing technique is failed to provide better results for identifying unknown attacks with higher accuracy and lesser time consumption. In order to address these problems, Radial Basis Kernel Regressive Feature Extracted Brown Boost Classification (RBKRFEBBC) method is introduced for performing the attack detection in cloud computing. The main objective of RBKRFEBBC method is to improve the attack detection performance with higher accuracy and minimal time consumption. Dichotomous radial basis kernelized regressive funct

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Kim, Sungbeen, and Dohoon Kim. "Securing the Cyber Resilience of a Blockchain-Based Railroad Non-Stop Customs Clearance System." Sensors 23, no. 6 (2023): 2914. http://dx.doi.org/10.3390/s23062914.

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Current railroad customs clearance systems are problematic in that the movement of trains is occasionally restricted for extended periods during inspections to verify cargo integrity at customs clearance. Consequently, significant human and material resources are consumed to obtain customs clearance to the destination, considering different processes exist for cross-border trade. Therefore, we developed a cross-border blockchain-based non-stop customs clearance (NSCC) system to address these delays and reduce resource consumption for cross-border trains. The integrity, stability, and traceabil

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Zhang, Yanshuo, Liqiu Li, Hengyu Bao, Xiaohong Qin, Zhiyuan Zhang, and Xiaoyi Duan. "IAESR: IoT-oriented authenticated encryption based on iShadow round function." PeerJ Computer Science 11 (June 11, 2025): e2947. https://doi.org/10.7717/peerj-cs.2947.

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With the growing popularity of the Internet of Things (IoT) devices and the widespread application of embedded systems, the demand for security and resource efficiency in these devices is also increasing. Traditional authenticated encryption (AE) algorithms are often unsuitable for lightweight devices due to their complexity and resource consumption, creating a need for lightweight AE algorithms. Lightweight devices typically have limited processing power, storage capacity, and energy resources, which necessitates the design of simple and efficient encryption algorithms that can function withi

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6

Shruthi, R., and Z. Khan Prof.Rasheeda. "Preventing X-DoS attack on Cloud using Reputation-Based Technology." International Journal of Advances In Scientific Research and Engineering (IJASRE) 3, no. 4 (2017): 68–75. https://doi.org/10.5281/zenodo.581759.

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<em>Cloud computing is a vast system which provides service based on usage to any number of users from any place using any device. But due to third party interference for maintenance and storage there are numerous denial of service attacks and other security attacks which affects not only the quality but also the cost due to resource consumption. And moreover the cost keeps increasing as long as the DoS attack is not detected at the earliest possible stage. Even though there are many security solutions to keep the attacks away still the DoS attacks take place stealthily due to some point of we

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Garcia Ribera, Eric, Brian Martinez Alvarez, Charisma Samuel, Philokypros P. Ioulianou, and Vassilios G. Vassilakis. "An Intrusion Detection System for RPL-Based IoT Networks." Electronics 11, no. 23 (2022): 4041. http://dx.doi.org/10.3390/electronics11234041.

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The Internet of Things (IoT) has become very popular during the last decade by providing new solutions to modern industry and to entire societies. At the same time, the rise of the industrial Internet of Things (IIoT) has provided various benefits by linking infrastructure around the world via sensors, machine learning, and data analytics. However, the security of IoT devices has been proven to be a major concern. Almost a decade ago, the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) was designed to handle routing in IoT and IIoT. Since then, numerous types of attacks on RPL hav

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Wu, Hongyu, Xiaoning Feng, and Jiale Zhang. "Quantum Implementation of the SAND Algorithm and Its Quantum Resource Estimation for Brute-Force Attack." Entropy 26, no. 3 (2024): 216. http://dx.doi.org/10.3390/e26030216.

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The SAND algorithm is a family of lightweight AND-RX block ciphers released by DCC in 2022. Our research focuses on assessing the security of SAND with a quantum computation model. This paper presents the first quantum implementation of SAND (including two versions of SAND, SAND-64 and SAND-128). Considering the depth-times-width metric, the quantum circuit implementation of the SAND algorithm demonstrates a relatively lower consumption of quantum resources than that of the quantum implementations of existing lightweight algorithms. A generalized Grover-based brute-force attack framework was i

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Kannan, Charulatha, Rajendiran Muthusamy, Vimala Srinivasan, Vivek Chidambaram, and Kiruthika Karunakaran. "Machine learning based detection of DDoS attacks in software defined network." Indonesian Journal of Electrical Engineering and Computer Science 32, no. 3 (2023): 1503. http://dx.doi.org/10.11591/ijeecs.v32.i3.pp1503-1511.

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<span>Nowadays, software defined networking (SDN) offers benefits in the area so fautomation, elasticity, and resource consumption. However, evidenceis there that SDN controller may undergo certain defeat for the network structure, particularly as the yare targeted by attacks like denial of service (DoS). Due to this network traffic has increased tremendously and attacked the server severely. To handle this issue, weused the Ryu controller and Mininet tool to identify and all eviate the DoS attack by the machine learning (ML) algorithm. Since ML is deemed as themain method for detecting

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Shi, Haibin, Guang Cheng, Ying Hu, Fuzhou Wang, and Haoxuan Ding. "RT-SAD: Real-Time Sketch-Based Adaptive DDoS Detection for ISP Network." Security and Communication Networks 2021 (July 27, 2021): 1–10. http://dx.doi.org/10.1155/2021/9409473.

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With the great changes in network scale and network topology, the difficulty of DDoS attack detection increases significantly. Most of the methods proposed in the past rarely considered the real-time, adaptive ability, and other practical issues in the real-world network attack detection environment. In this paper, we proposed a real-time adaptive DDoS attack detection method RT-SAD, based on the response to the external network when attacked. We designed a feature extraction method based on sketch and an adaptive updating algorithm, which makes the method suitable for the high-speed network e

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Hwang, Min-Shiang, Jung-Wen Lo, and Chia-Hsin Liu. "Enhanced of Key Agreement Protocols Resistant to a Denial-of-Service Attack." Fundamenta Informaticae 61, no. 3-4 (2004): 389–98. https://doi.org/10.3233/fun-2004-613-412.

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The denial-of-service attack, a malicious client executes a key agreement protocol simultaneously many times to exhaust the server's memory or computing resource and to interfere the honest client connecting with the server. It is a serious problem in the key agreement protocol. A key agreement protocol which resists to the storage-exhaustion and the CPU-exhaustion attack was firstly proposed by Hiros-Matsuura. However, their protocol is not efficient enough during the weak key validation. Our proposed protocol modifies the weak key validation and avoids the unnecessary heavy computation to en

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12

Le, Duc, Minh Dao, and Quyen Nguyen. "Comparison of machine learning algorithms for DDoS attack detection in SDN." Information and Control Systems, no. 3 (June 15, 2020): 59–70. http://dx.doi.org/10.31799/1684-8853-2020-3-59-70.

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Introduction: Distributed denial-of-service (DDoS) has become a common attack type in cyber security. Apart from the conventional DDoS attacks, software-defined networks also face some other typical DDoS attacks, such as flow-table attack or controller attack. One of the most recent solutions to detect a DDoS attack is using machine learning algorithms to classify the traffic. Purpose: Analysis of applying machine learning algorithms in order to prevent DDoS attacks in software-defined network. Results: A comparison of six algorithms (random forest, decision tree, naive Bayes, support vector m

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13

Kumar Singh Yadav, Ajit, and Rajesh K. Yadav. "A Reliable and Secure AODV Protocol for MANETs." International Journal of Engineering & Technology 7, no. 4.38 (2018): 893. http://dx.doi.org/10.14419/ijet.v7i4.38.27603.

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In recent years, Mobile ad hoc networks ((MANETs) have generated great interest among researchers in their implementation under several computing environments. However, MANETs are highly susceptible to various security attacks due to their inherent characteristics. The ad hoc on demand distance vector (AODV) is most suitable routing protocol for mobile adhoc networks in which resource consumption attacks are frequent if it is not detected timely. In this paper, we have proposed a scheme to detect as well as overcome black hole attacks using an Intrusion Detection System (IDS). The proposed sch

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Alani, Mohammed M., and Ernesto Damiani. "XRecon: An Explainbale IoT Reconnaissance Attack Detection System Based on Ensemble Learning." Sensors 23, no. 11 (2023): 5298. http://dx.doi.org/10.3390/s23115298.

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IoT devices have grown in popularity in recent years. Statistics show that the number of online IoT devices exceeded 35 billion in 2022. This rapid growth in adoption made these devices an obvious target for malicious actors. Attacks such as botnets and malware injection usually start with a phase of reconnaissance to gather information about the target IoT device before exploitation. In this paper, we introduce a machine-learning-based detection system for reconnaissance attacks based on an explainable ensemble model. Our proposed system aims to detect scanning and reconnaissance activity of

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15

Abdelhaq, Maha. "A Study on the Vulnerability of AODV Routing Protocol to Resource Consumption Attack." Indian Journal of Science and Technology 5, no. 11 (2012): 1–5. http://dx.doi.org/10.17485/ijst/2012/v5i11.4.

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Yaokumah, Winfred, Richard Nunoo Clottey, and Justice Kwame Appati. "Network Intrusion Detection in Internet of Things (IoT)." International Journal of Smart Security Technologies 8, no. 1 (2021): 49–65. http://dx.doi.org/10.4018/ijsst.2021010104.

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The open nature of the internet of things network makes it vulnerable to cyber-attacks. Intrusion detection systems aid in detecting and preventing such attacks. This paper offered a systematic review of studies on intrusion detection in IoT, focusing on metrics, methods, datasets, and attack types. This review used 33 network intrusion detection papers in 31 journals and 2 conference proceedings. The results revealed that the majority of the studies used generated or private datasets. Machine learning (ML)-based methods (85%) were used in the studies, while the rest used statistical methods.

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Cao, Laicheng, and Min Zhu. "Fuzzy-Based Privacy-Preserving Scheme of Low Consumption and High Effectiveness for IoTs: A Repeated Game Model." Sensors 22, no. 15 (2022): 5674. http://dx.doi.org/10.3390/s22155674.

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In the Internet of things (IoTs), data transmission via network coding is highly vulnerable to intra-generation and inter-generation pollution attacks. To mitigate such attacks, some resource-intensive privacy-preserving schemes have been adopted in the previous literature. In order to balance resource consumption and data-privacy-preserving issues, a novel fuzzy-based privacy-preserving scheme is proposed. Our scheme is constructed on a T-S fuzzy trust theory, and network coding data streams are routed in optimal clusters formulated by a designed repeated game model to defend against pollutio

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18

Hajar, Dahhak, Nadia Afifi, and Imane Hilal. "Dynamic Sharding and Monte Carlo for Post-Quantum Blockchain Resilience." Cryptography 9, no. 2 (2025): 22. https://doi.org/10.3390/cryptography9020022.

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Scalability and security restrictions are posing new challenges for blockchain networks, especially in the face of Distributed Denial-of-Service (DDoS) attacks and upcoming quantum threats. Previous research also found that post-quantum blockchains, despite their improved cryptographic algorithms, are still vulnerable to DDoS attacks, emphasizing the need for more resilient architectural solutions. This research studies the use of dynamic sharding, an innovative approach for post-quantum blockchains that allows for adaptive division of the network into shards based on workload and network cond

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Abdulkareem, Omar A., Raja Kumar Kontham, and Farhad E. Mahmood. "Collaborative Intrusion Detection System to Identify Joint Attacks in Routing Protocol for Low-Power and Lossy Networks Routing Protocol on the Internet of Everything." Mesopotamian Journal of CyberSecurity 4, no. 3 (2024): 251–77. https://doi.org/10.58496/mjcs/2024/026.

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The Routing Protocol for Low-Power and Lossy Networks (RPL) routing protocol is utilized in the Internet of Everything (IoE) is highly vulnerable to various collaborative routing attacks. This attack can highly degrade network performance through increased delay, energy consumption, and unreliable data exchange. This critical vulnerability necessitates a robust intrusion detection system. This study aims to enhance a Collaborative Intrusion Detection System (CIDS) for detecting and mitigating joint attacks in the RPL protocol, focusing on improving detection accuracy while minimizing network d

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Neve, Rahul P., and Rajesh Bansode. "Attack Analysis on Hybrid-SIMON-SPECKey Lightweight Cryptographic Algorithm for IoT Applications." Indian Journal Of Science And Technology 17, no. 10 (2024): 932–40. http://dx.doi.org/10.17485/ijst/v17i10.2811.

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Objective: To perform attack analysis on new developed hybrid-SIMON-SPECKey lightweight cryptographic algorithms and compare its strength with existing SIMON and SPECK Lightweight cryptographic algorithm. Methods: A hybrid-SIMON-SPECKey algorithm is the combination of round function of SIMON and key scheduling of SPECK algorithm. Both SIOMN & SPECK algorithm are used for securing resource constrained devices. In this research work, avalanche effect method is used to analyze attack resistance property of algorithm. Findings: Newly developed Hybrid algorithm shows better results in terms of

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Oladipupo, Esau Taiwo, and Oluwakemi Christiana Abikoye. "Improved authenticated elliptic curve cryptography scheme for resource starve applications." Computer Science and Information Technologies 3, no. 3 (2022): 169–85. http://dx.doi.org/10.11591/csit.v3i3.p169-185.

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Elliptic curve cryptography (ECC) remains the best approach to asymmetric cryptography when it comes to securing communication among communication partners in low-computing devices such as wireless sensor networks (WSN) and the Internet of Things (IoT) due to its effectiveness in generating small keys with a strong encryption mechanism. The ECC cuts down on power use and improves device performance, so it can be used in a wide range of devices that don't have a lot of resources. However, most of the existing ECC implementations suffer from implementation flaws that make them vulnerable to cryp

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Esau Taiwo Oladipupo and Oluwakemi Christiana Abikoye. "Improved authenticated elliptic curve cryptography scheme for resource starve applications." Computer Science and Information Technologies 3, no. 3 (2022): 169–85. http://dx.doi.org/10.11591/csit.v3i3.pp169-185.

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Elliptic curve cryptography (ECC) remains the best approach to asymmetric cryptography when it comes to securing communication among communication partners in low-computing devices such as wireless sensor networks (WSN) and the Internet of Things (IoT) due to its effectiveness in generating small keys with a strong encryption mechanism. The ECC cuts down on power use and improves device performance, so it can be used in a wide range of devices that don't have a lot of resources. However, most of the existing ECC implementations suffer from implementation flaws that make them vulnerable to cryp

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Esau, Taiwo Oladipupo, and Christiana Abikoye Oluwakemi. "Improved authenticated elliptic curve cryptography scheme for resource starve applications." Computer Science and Information Technologies 3, no. 3 (2022): 169–85. https://doi.org/10.11591/csit.v3i3.pp169-185.

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Elliptic curve cryptography (ECC) remains the best approach to asymmetric cryptography when it comes to securing communication among communication partners in low-computing devices such as wireless sensor networks (WSN) and the Internet of Things (IoT) due to its effectiveness in generating small keys with a strong encryption mechanism. The ECC cuts down on power use and improves device performance, so it can be used in a wide range of devices that don't have a lot of resources. However, most of the existing ECC implementations suffer from implementation flaws that make them vulnerable to

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Han, Seungjae, Keonyong Lee, Seongje Cho, and Moonju Park. "Anomaly Detection Based on Temporal Behavior Monitoring in Programmable Logic Controllers." Electronics 10, no. 10 (2021): 1218. http://dx.doi.org/10.3390/electronics10101218.

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As Programmable Logic Controllers (PLCs) are increasingly connected and integrated into the industrial Internet of things, cybersecurity threats to PLCs are also increasing. Adversaries can perform a denial of service (DoS) attack based on the transmission of a large number of network packets, and a control-logic injection attack through sophisticated packet transmission. We propose an approach to detecting and defending against attacks that exploit security vulnerabilities in a PLC system. In order to protect against indiscriminate packet transmission attacks that exploit uncontrolled resourc

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Alcala’ Garrido, Hassel Aurora, Mario E. Rivero-Angeles, and Eleazar Aguirre Anaya. "Primary User Emulation in Cognitive Radio-Enabled WSNs for Structural Health Monitoring: Modeling and Attack Detection." Journal of Sensors 2019 (April 28, 2019): 1–14. http://dx.doi.org/10.1155/2019/6950534.

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Nowadays, the use of sensor nodes for the IoT is widespread. At the same time, cyberattacks on these systems have become a relevant design consideration in the practical deployment of wireless sensor networks (WSNs). However, there are some types of attacks that have to be prevented or detected as fast as possible, like, for example, attacks that put lives in danger. In this regard, a primary user emulation (PUE) attack in a structural health monitoring (SHM) system falls inside this category since nodes failing to report structural damages may cause a collapse of the building with no warning

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Priya M R, Usha J. "A Study on DDoS Attack Detection Technique Prior to Machine Learning in Wireless Sensor Networks." Tuijin Jishu/Journal of Propulsion Technology 44, no. 5 (2023): 3698–721. http://dx.doi.org/10.52783/tjjpt.v44.i5.3458.

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Wireless Sensor Networks (WSNs) are integral to a wide range of critical applications, including environmental monitoring, healthcare, and industrial control systems. Then delves into DDoS attacks, elucidating the various attack types, motives, and their detrimental effects on WSNs. The core of the study investigates DDoS detection techniques, encompassing signature-based, anomaly-based, and hybrid approaches. Optimization mechanisms for DDoS detection in WSNs are explored in-depth, including resource-efficient algorithms and scalability solutions. Consideration is given to striking a balance

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Trikalinou, Anna, and Nikolaos Bourbakis. "An Enhanced Dynamic Information Flow Tracking Method with Reverse Stack Execution." International Journal of Monitoring and Surveillance Technologies Research 3, no. 1 (2015): 40–58. http://dx.doi.org/10.4018/ijmstr.2015010103.

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Memory errors have long been a critical security issue primarily for C/C++ programming languages and are still considered one of the top three most dangerous software errors according to the MITRE ranking. In this paper the authors focus on their exploitation via control-flow hijacking and data-only attacks (stack, and partially heap (G. Novarck & E. Berger, 2010)) by proposing a synergistic security methodology, which can accurately detect and thwart them. Their methodology is based on the Dynamic Information Flow Tracking (DIFT) technique and improves its data-only attack detection by ut

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Jain, Shaveta, and Kushagra Agrawal. "The Impact of Resource Consumption Attack on Signal-Stability based Adaptive Routing Protocol in Manet." Indian Journal of Science and Technology 10, no. 30 (2017): 1–5. http://dx.doi.org/10.17485/ijst/2017/v10i19/115535.

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Jain, Shaveta, and Kushagra Agrawal. "The Impact of Resource Consumption Attack on Signal-Stability based Adaptive Routing Protocol in Manet." Indian Journal of Science and Technology 10, no. 30 (2017): 1–5. http://dx.doi.org/10.17485/ijst/2017/v10i30/115535.

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Cho, Won, and Joonho Kong. "Memory and Cache Contention Denial-of-Service Attack in Mobile Edge Devices." Applied Sciences 11, no. 5 (2021): 2385. http://dx.doi.org/10.3390/app11052385.

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In this paper, we introduce a memory and cache contention denial-of-service attack and its hardware-based countermeasure. Our attack can significantly degrade the performance of the benign programs by hindering the shared resource accesses of the benign programs. It can be achieved by a simple C-based malicious code while degrading the performance of the benign programs by 47.6% on average. As another side-effect, our attack also leads to greater energy consumption of the system by 2.1× on average, which may cause shorter battery life in the mobile edge devices. We also propose detection and m

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Yan, Fei, Xiaoping Zhu, Zhou Zhou, and Yang Tang. "Heterogeneous multi-unmanned aerial vehicle task planning: Simultaneous attacks on targets using the Pythagorean hodograph curve." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 233, no. 13 (2019): 4735–49. http://dx.doi.org/10.1177/0954410019829368.

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The coupled task allocation and path planning problem for heterogeneous multiple unmanned aerial vehicles performing a search and attack mission involving obstacles and no-fly zones are addressed. The importance of the target is measured using a time-dependent value. A task allocation algorithm is proposed to obtain the maximum system utility. In the system utility function, the reward of the target, path lengths of unmanned aerial vehicles, and number of unmanned aerial vehicles to perform a simultaneous attack are considered. The path length of the unmanned aerial vehicles based on the Pytha

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Nhu, Chien-Nguyen, and Minho Park. "Two-Phase Deep Learning-Based EDoS Detection System." Applied Sciences 11, no. 21 (2021): 10249. http://dx.doi.org/10.3390/app112110249.

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Cloud computing is currently considered the most cost-effective platform for offering business and consumer IT services over the Internet. However, it is prone to new vulnerabilities. A new type of attack called an economic denial of sustainability (EDoS) attack exploits the pay-per-use model to scale up the resource usage over time to the extent that the cloud user has to pay for the unexpected usage charge. To prevent EDoS attacks, a few solutions have been proposed, including hard-threshold and machine learning-based solutions. Among them, long short-term memory (LSTM)-based solutions achie

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Wu, Jianping, Jiahe Jin, and Chunming Wu. "Challenges and Countermeasures of Federated Learning Data Poisoning Attack Situation Prediction." Mathematics 12, no. 6 (2024): 901. http://dx.doi.org/10.3390/math12060901.

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Federated learning is a distributed learning method used to solve data silos and privacy protection in machine learning, aiming to train global models together via multiple clients without sharing data. However, federated learning itself introduces certain security threats, which pose significant challenges in its practical applications. This article focuses on the common security risks of data poisoning during the training phase of federated learning clients. First, the definition of federated learning, attack types, data poisoning methods, privacy protection technology and data security situ

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Indrayati, Liestiana. "INVENTARISASI NEMATODA PARASIT PADA TANAMAN, HEWAN DAN MANUSIA." EnviroScienteae 13, no. 3 (2017): 195. http://dx.doi.org/10.20527/es.v13i3.4306.

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Pathogenic nematodas are widespread in nature, it can attack plants, animals, and humans and cause disruption to their hosts, then effect to lower quantity of plantation, yields, and livestock production and also affect to degradation of human resource quality. This paper is a systematic review that uses literature method about the inventory of nematoda parasite that attacks plants, animals and human, some method of examination and the effects that occurred by the host. The major parasite nematodas that infect the plants are Meloidogyne sp, Pratylenchut sp, and Radopholus sp., nematode in anim

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Howard, Brett R., Daniel Barrios-O’Neill, Mhairi E. Alexander, et al. "Functional responses of a cosmopolitan invader demonstrate intraspecific variability in consumer-resource dynamics." PeerJ 6 (September 28, 2018): e5634. http://dx.doi.org/10.7717/peerj.5634.

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Background Variability in the ecological impacts of invasive species across their geographical ranges may decrease the accuracy of risk assessments. Comparative functional response analysis can be used to estimate invasive consumer-resource dynamics, explain impact variability, and thus potentially inform impact predictions. The European green crab (Carcinus maenas) has been introduced on multiple continents beyond its native range, although its ecological impacts appear to vary among populations and regions. Our aim was to test whether consumer-resource dynamics under standardized conditions

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Riaz, SK, and V. Srirammanoj. "Sufficient Authentication for Energy Consumption in Wireless Sensor Networks." TELKOMNIKA Indonesian Journal of Electrical Engineering 16, no. 2 (2015): 316. http://dx.doi.org/10.11591/tijee.v16i2.1619.

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Given the understanding of the prospective WSN programs and because of source restrictions, key management emerges as a complicated problem for WSNs. One of the main issues when developing a key management scheme is the system scalability. Indeed, the method should assistance a huge number of nodes to allow a large range implementation of the system. In this paper we implemented a performance trade-off research of power intake vs. We urbanized a novel probability style to evaluate the best redundancy stage in terms of direction redundancy (mp) and resource redundancy (ms), as well as the best

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37

Dass, Ruby, Manikandan Narayanan, Gayathri Ananthakrishnan, et al. "A Cluster-Based Energy-Efficient Secure Optimal Path-Routing Protocol for Wireless Body-Area Sensor Networks." Sensors 23, no. 14 (2023): 6274. http://dx.doi.org/10.3390/s23146274.

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Recently, research into Wireless Body-Area Sensor Networks (WBASN) or Wireless Body-Area Networks (WBAN) has gained much importance in medical applications, and now plays a significant role in patient monitoring. Among the various operations, routing is still recognized as a resource-intensive activity. As a result, designing an energy-efficient routing system for WBAN is critical. The existing routing algorithms focus more on energy efficiency than security. However, security attacks will lead to more energy consumption, which will reduce overall network performance. To handle the issues of r

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Alshdadi, Abdulrahman A., Abdulwahab Ali Almazroi, Nasir Ayub, Miltiadis D. Lytras, Eesa Alsolami, and Faisal S. Alsubaei. "Big Data-Driven Deep Learning Ensembler for DDoS Attack Detection." Future Internet 16, no. 12 (2024): 458. https://doi.org/10.3390/fi16120458.

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The increasing threat of Distributed DDoS attacks necessitates robust, big data-driven methods to detect and mitigate complex Network and Transport Layer (NTL) attacks. This paper proposes EffiGRU-GhostNet, a deep-learning ensemble model for high-accuracy DDoS detection with minimal resource consumption. EffiGRU-GhostNet integrates Gated Recurrent Units (GRU) with the GhostNet architecture, optimized through Principal Component Analysis with Locality Preserving Projections (PCA-LLP) to handle large-scale data effectively. Our ensemble was tested on IoT-23, APA-DDoS, and additional datasets cre

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Alshammari, Majid, and Khaled Elleithy. "Efficient and Secure Key Distribution Protocol for Wireless Sensor Networks." Sensors 18, no. 10 (2018): 3569. http://dx.doi.org/10.3390/s18103569.

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Modern wireless sensor networks have adopted the IEEE 802.15.4 standard. This standard defines the first two layers, the physical and medium access control layers; determines the radio wave used for communication; and defines the 128-bit advanced encryption standard (AES-128) for encrypting and validating the transmitted data. However, the standard does not specify how to manage, store, or distribute the encryption keys. Many solutions have been proposed to address this problem, but the majority are impractical in resource-constrained devices such as wireless sensor nodes or cause degradation

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Sukavasi, Hema Gopinath, Lokesh Kanagala, and Riaz Shaik. "Sufficient Authentication for Energy Consumption in Wireless Sensor Networks." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 2 (2016): 735. http://dx.doi.org/10.11591/ijece.v6i2.9038.

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Given the understanding of the prospective WSN programs and because of source restrictions, key management emerges as a complicated problem for WSNs. One of the main issues when developing a key management scheme is the system scalability. Indeed, the method should assistance a huge number of nodes to allow a large range implementation of the system. In this paper we implemented a performance trade-off research of power intake vs. Quality of Solutions obtain in stability, suitability, and security for redundancy control of clustered heterogeneous wireless indicator systems using multipath rout

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Sukavasi, Hema Gopinath, Lokesh Kanagala, and Riaz Shaik. "Sufficient Authentication for Energy Consumption in Wireless Sensor Networks." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 2 (2016): 735. http://dx.doi.org/10.11591/ijece.v6i2.pp735-742.

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Given the understanding of the prospective WSN programs and because of source restrictions, key management emerges as a complicated problem for WSNs. One of the main issues when developing a key management scheme is the system scalability. Indeed, the method should assistance a huge number of nodes to allow a large range implementation of the system. In this paper we implemented a performance trade-off research of power intake vs. Quality of Solutions obtain in stability, suitability, and security for redundancy control of clustered heterogeneous wireless indicator systems using multipath rout

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42

Dhananjay, Krithika, and Emre Salman. "Charge Based Power Side-Channel Attack Methodology for an Adiabatic Cipher." Electronics 10, no. 12 (2021): 1438. http://dx.doi.org/10.3390/electronics10121438.

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SIMON is a block cipher developed to provide flexible security options for lightweight hardware applications such as the Internet-of-things (IoT). Safeguarding such resource-constrained hardware from side-channel attacks poses a significant challenge. Adiabatic circuit operation has recently received attention for such applications due to ultra-low power consumption. In this work, a charge-based methodology is developed to mount a correlation power analysis (CPA) based side-channel attack to an adiabatic SIMON core. The charge-based method significantly reduces the attack complexity by reducin

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Zakiya Manzoor Khan, Et al. "Trust Based Mechanism for Isolation of Malicious Nodes in Internet of Things." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 10 (2023): 1689–95. http://dx.doi.org/10.17762/ijritcc.v11i10.8740.

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The Internet of Things systems are prone to the attacks as they have ad-hoc and limited resource structure. IoT-based systems are utilized for managing a large volume of information and assist in services related to industrial and medical applications. Due to this, the IoT attains becomes a target for a multitude of attackers and adversaries namely occasional hackers, cybercriminals, hacktivists, government, etc. The major goal of potential attackers is to steal the sensitive information such as credit card numbers, location data, credential of financial account and information related to heal

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Zakiya Manzoor Khan, Et al. "Trust based Mechanism for Isolation of Malicious Nodes in Internet of Things." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 9 (2023): 709–14. http://dx.doi.org/10.17762/ijritcc.v11i9.8863.

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The Internet of Things systems are prone to the attacks as they have ad-hoc and limited resource structure. IoT-based systems are utilized for managing a large volume of information and assist in services related to industrial and medical applications. Due to this, the IoT attains becomes a target for a multitude of attackers and adversaries namely occasional hackers, cybercriminals, hacktivists, government, etc. The major goal of potential attackers is to steal the sensitive information such as credit card numbers, location data, credential of financial account and information related to heal

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Rahul, P. Neve, and Bansode Rajesh. "Attack Analysis on Hybrid-SIMON-SPECKey Lightweight Cryptographic Algorithm for IoT Applications." Indian Journal of Science and Technology 17, no. 10 (2024): 932–40. https://doi.org/10.17485/IJST/v17i10.2811.

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Abstract <strong>Objective:</strong> To perform attack analysis on new developed hybrid-SIMON-SPECKey lightweight cryptographic algorithms and compare its strength with existing SIMON and SPECK Lightweight cryptographic algorithm. <strong>Methods:</strong> A hybrid-SIMON-SPECKey algorithm is the combination of round function of SIMON and key scheduling of SPECK algorithm. Both SIOMN & SPECK algorithm are used for securing resource constrained devices. In this research work, avalanche effect method is used to analyze attack resistance property of algorithm. <strong>Findi

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Jia, Hefei, Xu Liu, Xiaoqiang Di, et al. "A Secure Virtual Machine Allocation Strategy Against Co-Resident Attacks." Journal of Advanced Computational Intelligence and Intelligent Informatics 23, no. 5 (2019): 898–908. http://dx.doi.org/10.20965/jaciii.2019.p0898.

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In the area of network development, especially cloud computing, security has been a long-standing issue. In order to better utilize physical resources, cloud service providers usually allocate different tenants on the same physical machine, i.e., physical resources such as CPU, memory, and network devices are shared among multiple tenants on the same host. Virtual machine (VM) co-resident attack, a serious threat in this sharing methodology, includes malicious tenants who tend to steal private data. Currently, most solutions focus on how to eliminate known specific side channels, but they have

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Ilokanuno, Ogochukwu A. "Smart Meter Tampering Detection Using IoT Based Unsupervised Machine Learning." International Journal for Research in Applied Science and Engineering Technology 12, no. 4 (2024): 5434–45. http://dx.doi.org/10.22214/ijraset.2024.61153.

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Abstract: This work presents a novel smart grid tampering detection system re-engineered for end user monitoring and pipeline automation. The research focused on distributed energy resources. In context, the end user load profile, and generation capacity were processed in the cloud environment for tampering management. Computational pipelined methodology was adopted using baseline data from an independent electricity consumption data from 2018-2021 Abuja. First, a smart grid (SG) survey was carried using existing home estate at Abuja to ascertain tampering procedures in distributed energy reso

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Howard, BR, DTS Wong, V. Aguiar, et al. "Effects of perceived competition and water temperature on the functional responses of invasive and native crabs." Marine Ecology Progress Series 684 (February 17, 2022): 69–78. http://dx.doi.org/10.3354/meps13974.

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As the frequency of species introductions increases globally, the need for predicting the ecological impacts of invaders becomes ever more urgent. Functional responses, i.e. how resource uptake by consumers changes as a function of resource density, describe the species-specific ability to deplete resources under standardized conditions, and their shape has been used as a tool to predict the impact of non-native species. However, functional responses are usually derived from individuals foraging alone, which overlooks the important roles of intra- and interspecific interactions in shaping per

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Zhang, Yuanyuan, Ning Wu, Fang Zhou, Jinbao Zhang, and Muhammad Yahya. "A Countermeasure against DPA on SIMON with an Area-Efficient Structure." Electronics 8, no. 2 (2019): 240. http://dx.doi.org/10.3390/electronics8020240.

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Differential power analysis (DPA) is an effective side channel attack method, which poses a critical threat to cryptographic algorithms, especially lightweight ciphers such as SIMON. In this paper, we propose an area-efficient countermeasure against DPA on SIMON based on the power randomization. Firstly, we review and analyze the architecture of SIMON algorithm. Secondly, we prove the threat of DPA attack to SIMON by launching actual DPA attack on SIMON 32/64 circuit. Thirdly, a low-cost power randomization scheme is proposed by combining fault injection with double rate technology, and the co

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Gankotiya, Anil Kumar, Vishal Kumar, and Kunwar Singh Vaisla. "Cross-layer DDoS attack detection in wireless mesh networks using deep learning algorithm." Journal of Electrical Engineering 76, no. 1 (2025): 34–47. https://doi.org/10.2478/jee-2025-0004.

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Abstract Wireless mesh networks (WMNs), owing to its decentralized design and resource limitations, are susceptible to several security vulnerabilities, including distributed denial of service (DDoS) attacks. Traditional DDoS detection techniques are usually unable to effectively mitigate such attacks in WMNs due to their dynamic and complex nature. In this work, we show the capability of a Deep Convolutional Neural Network (DCNN) algorithm at the cross-layer of the network protocol stack to accurately and robustly detect Distributed Denial-of-Service (DDoS) attacks in WMNs. DDoS attack assess

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