Deep Learning Anomaly Detection for Cellular IoT With Applications in Smart Logistics

Savić, Miloš; Lukić, Milan; Danilovic, Dragan; Bodroski, Zarko; Bajović, Dragana; Mezei, Ivan; Vukobratović, Dejan; Škrbić, Srdjan; Jakovetić, Dušan

doi:10.1109/access.2021.3072916

Cited by 44 publications

(15 citation statements)

References 40 publications

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“…With this information, the metrics success ratio, failure ratio, authentication time, verification time, and complexity are analyzed. In the comparative analysis section, the existing HTLA [19], DL-AD [20], and B-SSS [25] are considered.…”

Section: Discussionmentioning

confidence: 99%

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Security System of Logistics Service Transaction Record Based on Wireless Network

2022

Mobile Information Systems

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Wireless Networks (WNs) and their associated technology paradigms are employed for smart and secure logistics services. The wireless logistics transactions are secured through end-to-end authentication, verification, and third-party watchdog systems. This manuscript introduces a Preemptive Security Scheme for Transaction Verification (PSS-TV) in wireless network-aided logistics services. Different logistics services are secured based on the sender and receiver’s signature in mutual consent. Signature generation and implications are varied using the key size and validity based on the previous transaction recommendation. The conventional random forest classifier learning is used for detecting transaction breaches and validity requirements. This is feasible based on the transaction interruptions and failed mutual verifications. These classifications are performed using the learning paradigm for improving the key size in generating stealthy signatures. In the signature generation, the conventional elliptic curve cryptography is relied upon. The proposed scheme’s performance is analyzed using success ratio, failure rate, verification and authentication time, and complexity.

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Section: Discussionmentioning

confidence: 99%

“…Savic et al [20] proposed an anomaly detection (AD) method using the deep learning (DL) technique for cellular Internet of ings-(IoT-) based logistics devices. IoT is mostly used in logistics devices to provide many services for users.…”

Section: Related Workmentioning

confidence: 99%

Security System of Logistics Service Transaction Record Based on Wireless Network

2022

Mobile Information Systems

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“…This last section will explain communication in a Short-Range Network, Cellular IoT, which utilizes AI to enhance IoT performance. The following are related research studies: Savic et al [160] explain that IoT devices in infrastructure have increased. This factor becomes a challenge for the management and security of IoT devices.…”

Section: H Cellular Iotmentioning

confidence: 99%

A Systematic Review of LPWAN and Short-Range Network using AI to Enhance Internet of Things

Widianto

Sinaga

Ginting

2022

Journal of Robotics and Control

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Artificial intelligence (AI) has recently been used frequently, especially concerning the Internet of Things (IoT). However, IoT devices cannot work alone, assisted by Low Power Wide Area Network (LPWAN) for long-distance communication and Short-Range Network for a short distance. However, few reviews about AI can help LPWAN and Short-Range Network. Therefore, the author took the opportunity to do this review. This study aims to review LPWAN and Short-Range Networks AI papers in systematically enhancing IoT performance. Reviews are also used to systematically maximize LPWAN systems and Short-Range networks to enhance IoT quality and discuss results that can be applied to a specific scope. The author utilizes selected reporting items for systematic review and meta-analysis (PRISMA). The authors conducted a systematic review of all study results in support of the authors' objectives. Also, the authors identify development and related study opportunities. The author found 79 suitable papers in this systematic review, so a discussion of the presented papers was carried out. Several technologies are widely used, such as LPWAN in general, with several papers originating from China. Many reports from conferences last year and papers related to this matter were from 2020-2021. The study is expected to inspire experimental studies in finding relevant scientific papers and become another review.

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“…Zeke et al [11] proposed a phase measurement unit (PMU) by using two anomaly detection techniques single spectrum analysis and K-nearest neighboring (KNN) in edge fog hierarchy clustering architecture to detect anomalies more accurately. Tested consequences of the proposed model show that together approaches are appropriate at the cloud sheet with dissimilar benefits and restraints.…”

Section: Milos Et Al [6] Proposed An Anomaly Detection Technique Base...mentioning

confidence: 99%

Anomaly Detection for IOT/Cloud-Based Model in Fog Computing Using Machine Learning

Nayak¹,

Khan²

2022

IJOSCIENCE

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We know that the key technologies that are involved in the Internet of Things are wireless sensor networks and cloud computing, big data, embedded systems, and the internet. It is a giant network with connected devices. These devices gather and share data. But many IoT devices have poor security and cybercriminals are taking benefit of this. The two techniques cloud and fog computing both combined can be used to transfer secure data in IoT devices as cloud computing provides storage of data on cloud servers and fog computing offers us various services to access data and provides support for cloud servers. This research work presents various techniques to detect an intruder and anomaly detection in IoT-based cloud systems. Also, a comparison of all the techniques used to detect intruders and anomalies are compared on various parameters like accuracy, performance, efficiency, precision, recall, the detection rate.

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Deep Learning Anomaly Detection for Cellular IoT With Applications in Smart Logistics

Cited by 44 publications

References 40 publications

Security System of Logistics Service Transaction Record Based on Wireless Network

Security System of Logistics Service Transaction Record Based on Wireless Network

A Systematic Review of LPWAN and Short-Range Network using AI to Enhance Internet of Things

Anomaly Detection for IOT/Cloud-Based Model in Fog Computing Using Machine Learning

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