scholarly journals A Proficient Algorithm For Mining Frequent Item Sets

Frequent Item set Mining (FIM) discover recurrent item sets that are extremely associated in a transactional database. It can be used in big data applications like gene extraction, social network analysis, IOT devices sensor data analysis, etc. As the data size keeps on growing, an efficient procedure is necessary to process the enormous volume of data. Apriori is one of the topmost algorithm and its entry enhanced the research in mining. The algorithm requires multiple scans of the database and produce more candidate items, which increase the computation time and storage along with the transactions size. An efficient technique is required to boost the performance of the algorithm in terms of storage and computational complexity. To reduce the complexity we proposed a reduction factor to Apriori and it can be adopted before candidate generation. Experimental results revealed that our proposed technique greatly reduce the total execution time as well as storage requirements.

2021 ◽  
Vol 11 (3) ◽  
pp. 1260
Author(s):  
Abhijeet Thakare ◽  
Young-Gab Kim

Optimization of resource consumption and decreasing the response time of authentication requests is an immense urgent requirement for supporting the scalability of resources in IoT environments. The existing research attempts to design lightweight authentication protocols to address these issues. However, the schemes proposed in the literature are lacking in the creation of a lightweight (i.e., low computing, communication, and storage cost) and secure architecture. IoT devices in existing approaches consume high electricity and computing power, despite the fact that IoT devices have limited power and computing capabilities. Furthermore, the existing approaches lead to an increase in the burden on storage memory and also create heavy traffic on a communication channel, increasing the response time of device authentication requests. To overcome these limitations, we propose a novel lightweight and secure architecture that uses crypto-modules, which optimize the usage of one-way hash functions, elliptic-curve cryptography, and an exclusive-or operation. We demonstrate the proposed scheme’s security strength using informal security analysis and verified it by considering the widely used automated validation of internet security protocol application (AVISPA) and the ProVerif tool. The result shows that the proposed scheme is effective against active and passive security attacks and satisfies secure design. Moreover, we calculate the proposed scheme’s working cost by implementing it using a widely accepted standard pairing-based cryptography (PBC) library on embedded devices. The implementation proves that the proposed scheme is lightweight and reduces computation time by 0.933 ms, communication cost by 1408 bits, and storage cost by 384 bits, and removes the existing gaps.


Author(s):  
P.Hemalatha , Et. al.

Blockchain and Internet of Things (IoT) technologies are used in many domains, predominantly for electronic-healthcare. Here, IoT devices has the ability to provide real-time sensor data from patients to get processed and analyzed. As a single point of failure, mistrust, data manipulation and tampering, and privacy avoidance may all occur as a result of such a method. Through offering shared computing and storage for IoT data, blockchain can help solve such issues.Maintaining and sharing Medical data is necessary here.If there occurs loss of confidence means it threatens the medical data and loss of integrity creates impact on the life of patient. So, the first objective is to protect the medical records. Also, a central server to the records will pretend the hackers to attack and continuous fetching is difficult.Therefore, combining Blockchain and IoT will be a threat breaker for computerized medical records.


Author(s):  
Jaber Almutairi ◽  
Mohammad Aldossary

AbstractRecently, the number of Internet of Things (IoT) devices connected to the Internet has increased dramatically as well as the data produced by these devices. This would require offloading IoT tasks to release heavy computation and storage to the resource-rich nodes such as Edge Computing and Cloud Computing. Although Edge Computing is a promising enabler for latency-sensitive related issues, its deployment produces new challenges. Besides, different service architectures and offloading strategies have a different impact on the service time performance of IoT applications. Therefore, this paper presents a novel approach for task offloading in an Edge-Cloud system in order to minimize the overall service time for latency-sensitive applications. This approach adopts fuzzy logic algorithms, considering application characteristics (e.g., CPU demand, network demand and delay sensitivity) as well as resource utilization and resource heterogeneity. A number of simulation experiments are conducted to evaluate the proposed approach with other related approaches, where it was found to improve the overall service time for latency-sensitive applications and utilize the edge-cloud resources effectively. Also, the results show that different offloading decisions within the Edge-Cloud system can lead to various service time due to the computational resources and communications types.


Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4034
Author(s):  
Arie Haenel ◽  
Yoram Haddad ◽  
Maryline Laurent ◽  
Zonghua Zhang

The Internet of Things world is in need of practical solutions for its security. Existing security mechanisms for IoT are mostly not implemented due to complexity, budget, and energy-saving issues. This is especially true for IoT devices that are battery powered, and they should be cost effective to be deployed extensively in the field. In this work, we propose a new cross-layer approach combining existing authentication protocols and existing Physical Layer Radio Frequency Fingerprinting technologies to provide hybrid authentication mechanisms that are practically proved efficient in the field. Even though several Radio Frequency Fingerprinting methods have been proposed so far, as a support for multi-factor authentication or even on their own, practical solutions are still a challenge. The accuracy results achieved with even the best systems using expensive equipment are still not sufficient on real-life systems. Our approach proposes a hybrid protocol that can save energy and computation time on the IoT devices side, proportionally to the accuracy of the Radio Frequency Fingerprinting used, which has a measurable benefit while keeping an acceptable security level. We implemented a full system operating in real time and achieved an accuracy of 99.8% for the additional cost of energy, leading to a decrease of only ~20% in battery life.


2001 ◽  
Vol 61 (3) ◽  
pp. 350-371 ◽  
Author(s):  
Ramesh C. Agarwal ◽  
Charu C. Aggarwal ◽  
V.V.V. Prasad

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1339 ◽  
Author(s):  
Hasan Islam ◽  
Dmitrij Lagutin ◽  
Antti Ylä-Jääski ◽  
Nikos Fotiou ◽  
Andrei Gurtov

The Constrained Application Protocol (CoAP) is a specialized web transfer protocol which is intended to be used for constrained networks and devices. CoAP and its extensions (e.g., CoAP observe and group communication) provide the potential for developing novel applications in the Internet-of-Things (IoT). However, a full-fledged CoAP-based application may require significant computing capability, power, and storage capacity in IoT devices. To address these challenges, we present the design, implementation, and experimentation with the CoAP handler which provides transparent CoAP services through the ICN core network. In addition, we demonstrate how the CoAP traffic over an ICN network can unleash the full potential of the CoAP, shifting both overhead and complexity from the (constrained) endpoints to the ICN network. The experiments prove that the CoAP Handler helps to decrease the required computation complexity, communication overhead, and state management of the CoAP server.


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