Prediction of Re-Occurrences of Spoofed ACK Packets Sent to Deflate a Target Wireless Sensor Network Node by DDOS

Al-Naeem, Mohammed

doi:10.1109/access.2021.3089683

Cited by 12 publications

(4 citation statements)

References 24 publications

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“…Al-Naeem [23] conducted a study to predict DDoS attacks with transmission behavior variability to obtain high accuracy. This study's pattern of security attacks is in the form of fake ACKs, which deceive the target node, where the delivery is considered successful but failed.…”

Section: Wsn Security Systemsmentioning

confidence: 99%

Wireless Sensor Network Based Monitoring System: Implementation, Constraints, and Solution

Miptahudin

Suryani²,

Wirawan³

2022

JOIV : Int. J. Inform. Visualization

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Wireless Sensor Network (WSN) is a collection of sensors communicating at close range by forming a wireless-based network (wireless). Since 2015 research related to the use of WSN in various health, agriculture, security industry, and other fields has continued to grow. One interesting research case is the use of WSN for the monitoring process by collecting data using sensors placed and distributed in locations based on a wireless system. Sensors with low power, multifunction, supported by a combination of wireless network, microcontroller, memory, operating system, radio communication, and energy source in the form of an integrated battery enable a monitoring process of the monitoring area to run properly. The implementation of the wireless sensor network includes five main parts, namely sender, receiver, wireless transmission media, data/information, network architecture/configuration, and network management. Network management itself includes network configuration management, network performance management, network failure management, network security management, and network financing management. The main obstacles in implementing a wireless sensor network include three things: an effective and efficient data sending/receiving process, limited and easily depleted sensor energy/power, network security, and data security that is vulnerable to eavesdropping and destruction. This paper presents a taxonomy related to the constraints in implementing Wireless Sensor Networks. This paper also presents solutions from existing studies related to the constraints of implementing the WSN. Furthermore, from the results of the taxonomy mapping of these constraints, new gaps were identified related to developing existing research to produce better solutions.

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Section: Wsn Security Systemsmentioning

confidence: 99%

Wireless Sensor Network Based Monitoring System: Implementation, Constraints, and Solution

Miptahudin

Suryani²,

Wirawan³

2022

JOIV : Int. J. Inform. Visualization

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“…11 There are several attacks are occurred in IWSN such as denial of service (DoS), black hole, Sybil attack, node capture (NC) attack, and wormhole attack. [12][13][14] Among these attacks, the DoS and NC attacks are considered as most hazardous attacks in which an intruder can accomplish numerous redundant operations in the network. These redundant operations can easily collapse the entire process of IWSN.…”

Section: Introductionmentioning

confidence: 99%

An artificial intelligence approach for energy‐aware intrusion detection and secure routing in internet of things‐enabled wireless sensor networks

Aruchamy,

Gnanaselvi,

Sowndarya

et al. 2023

Concurrency and Computation

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SummaryIn today's world, the Internet of things (IoT) and wireless sensor networks (WSNs) have been integrated into various applications to support reliable communication systems. The IoT nodes collect the sensed data with the aid of WSN and transfer them to the cloud environment. Nevertheless, these nodes become vulnerable when Denial of Service attacks occurred in the IoT‐enabled WSN (IWSN). The insecure route also affects the energy efficiency of IWSN. Therefore, robust intrusion detection along with secure routing is necessitated to protect the IWSN from various security threats. In this paper, a novel Artificial Intelligence‐based Energy‐aware Intrusion Detection and Secure Routing model has been proposed to develop a secured IWSN. Initially, the proposed model executes the intrusion detection system to identify the various attacks. Afterward, a game strategy‐based decision mechanism is integrated with the proposed intrusion detection model to decide whether protection is needed or not. In the last phase, an energy‐aware ad‐hoc on‐demand distance vector algorithm has been established to offer secured routing among multiple nodes. The performance results show that the proposed model achieves superior detection accuracy of 95% and reduced energy utilization of 38% as compared with the existing intrusion detection models.

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“…This method performs encryption twice over the IoT environment using quadratic form residues. Al-Naeem [22] attempted to predict the reoccurrences of spoofed acknowledgement packets sent to deflate a target network node by a distributed denial-of-service (DDoS) attack. The prediction of DDoS attacks is done based on the variability analysis of the transmission pattern.…”

mentioning

confidence: 99%

“…The proposed solution is designed to operate within the unique constraints of WSN environments, focusing primarily on the CH and base station (BS) levels to optimize resource usage. By leveraging enhanced fuzzy logic for CH selection and introducing a lightweight, hybrid encryption model combining modified advanced encryption standard (AES) and Rivest-Shamir-Adleman (RSA), the proposed methodology is custom-made to address the identified gaps [21], [22]. This method ensures resourceconscious security and efficiency improvements, responding directly to the challenges outlined by Ahmed et al [11], and the optimization needs identified in studies by Haseeb et al [13] and Niu et al [15].…”

mentioning

confidence: 99%

Enhancing wireless sensor network security with optimized cluster head selection and hybrid public-key encryption

Puttaswamy,

Kanakapura Shivaprasad

2024

IJECE

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This paper introduces an integrated methodology that enhances both the efficiency and security of wireless sensor networks (WSNs) against various active attacks. A two-fold strategy is proposed that incorporates an advanced cluster head (CH) selection and a customized, lightweight encryption protocol. The CH selection process is optimized through a multi-phase approach using fuzzy logic, local and global network qualifiers, and a trust index to ensure the election of CHs that are not only energy-efficient but also reliable. To complement the robust CH selection, the study introduces a hybrid yet lightweight encryption scheme customized Rivest-Shamir-Adleman (c-RSA) and customized advanced encryption standard (c-AES) algorithms. This scheme is customized for WSNs with limited computational resources, maintaining strong encryption standards while significantly reducing energy consumption and computational overhead. Experimental results demonstrate that the proposed system substantially enhances network performance, exhibiting a 34.15% improvement in energy efficiency and a 30.95% increase in reliability over existing methods such as LEACH and its modified versions. This comprehensive approach underscores the potential for a synergistic design in WSNs that does not compromise on security while optimizing operational efficiency.

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Prediction of Re-Occurrences of Spoofed ACK Packets Sent to Deflate a Target Wireless Sensor Network Node by DDOS

Cited by 12 publications

References 24 publications

Wireless Sensor Network Based Monitoring System: Implementation, Constraints, and Solution

Wireless Sensor Network Based Monitoring System: Implementation, Constraints, and Solution

An artificial intelligence approach for energy‐aware intrusion detection and secure routing in internet of things‐enabled wireless sensor networks

Enhancing wireless sensor network security with optimized cluster head selection and hybrid public-key encryption

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