ELC: Edge Linked Caching for content updating in information-centric Internet of Things

Asmat, Hamid; Din, Ikram Ud; Ullah, Fasee; Talha, Muhammad; Khan, Murad; Guizani, Mohsen

doi:10.1016/j.comcom.2020.03.049

Cited by 23 publications

(13 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…FL provides smart models, low latency, reduced power consumption, and allows the use of training data from a user equipment (UE) without sacrificing the personal data privacy. In [26], it was demonstrated that innetwork caching is an effective technique for reducing content delivery latency and to improve content availability in IoT systems. The work in [16] presented that the ULL communications in 5G and beyond networks will likely rely on the IEEE 802.1 time sensitive networking (TSN) and the emerging IETF deterministic networking (DetNet) standards.…”

Section: A Motivationmentioning

confidence: 99%

“…IP-based networks may not be the best solution for IoT devices because IP-based networks are host-centric and they require the location of content to be identified before the retrieval of the content [26], [35], [104]. To identify the location, every device is assigned an IP-address.…”

Section: A In-network Cachingmentioning

confidence: 99%

“…On the other hand, information-centric network (ICN) has proven to overcome the limitations of IP-based networks. Therefore, ICN is known to become the architecture for the IoT [26].…”

Section: A In-network Cachingmentioning

confidence: 99%

See 2 more Smart Citations

A Classification of the Enabling Techniques for Low Latency and Reliable Communications in 5G and Beyond: AI-Enabled Edge Caching

Mutalemwa

Shin

2020

IEEE Access

View full text Add to dashboard Cite

Section: A Motivationmentioning

confidence: 99%

Section: A In-network Cachingmentioning

confidence: 99%

See 1 more Smart Citation

A Classification of the Enabling Techniques for Low Latency and Reliable Communications in 5G and Beyond: AI-Enabled Edge Caching

Mutalemwa

Shin

2020

IEEE Access

View full text Add to dashboard Cite

“…Cloud-connected IoT edge nodes are fragile on security management as they are geographically distributed from the cloud, which makes it easy for an adversary to launch an attack and remove the logs [12,13]. Moreover, edge nodes are not energy efficient and have potential problems for continuous log collection and preservation [14]. For instance, malicious users, attackers, edge-nodes, and the attacks of the rogue gateway and the rogue data center may be disguised as regular fogs between the data center and the users [15,16].…”

Section: Introductionmentioning

confidence: 99%

Proactive Forensics in IoT: Privacy-Aware Log-Preservation Architecture in Fog-Enabled-Cloud Using Holochain and Containerization Technologies

et al. 2020

Self Cite

View full text Add to dashboard Cite

Collecting and preserving the smart environment logs connected to cloud storage is challenging due to the black-box nature and the multi-tenant cloud models which can pervade log secrecy and privacy. The existing work for log secrecy and confidentiality depends on cloud-assisted models, but these models are prone to multi-stakeholder collusion problems. This study proposes ’PLAF,’ a holistic and automated architecture for proactive forensics in the Internet of Things (IoT) that considers the security and privacy-aware distributed edge node log preservation by tackling the multi-stakeholder issue in a fog enabled cloud. We have developed a test-bed to implement the specification, as mentioned earlier, by incorporating many state-of-the-art technologies in one place. We used Holochain to preserve log integrity, provenance, log verifiability, trust admissibility, and ownership non-repudiation. We introduced the privacy preservation automation of log probing via non-malicious command and control botnets in the container environment. For continuous and robust integration of IoT microservices, we used docker containerization technology. For secure storage and session establishment for logs validation, Paillier Homomorphic Encryption, and SSL with Curve25519 is used respectively. We performed the security and performance analysis of the proposed PLAF architecture and showed that, in stress conditions, the automatic log harvesting running in containers gives a 95% confidence interval. Moreover, we show that log preservation via Holochain can be performed on ARM-Based architectures such as Raspberry Pi in a very less amount of time when compared with RSA and blockchain.

show abstract

“…Internet Things (IoT) [1] provides a diverse opportunity to automate distinct domains, which include wireless sensor networks [2,3], home appliances [4,5], smart cities [6][7][8], healthcare [9][10][11][12][13], security and surveillance [14][15][16], energy consumption [17][18][19], agriculture automation [20], and many more [21][22][23][24][25]. The concept of a smart irrigation system [26] is proposed in the Cloud-based Internet of Agriculture Things (IoAT) [27] in which sensors gather the findings of soil and transmit it towards the base station (BS) to take the required actions [28].…”

Section: Introductionmentioning

confidence: 99%

AgriTrust—A Trust Management Approach for Smart Agriculture in Cloud-based Internet of Agriculture Things

Awan

Din

Almogren

et al. 2020

Sensors

View full text Add to dashboard Cite

Internet of Things (IoT) provides a diverse platform to automate things where smart agriculture is one of the most promising concepts in the field of Internet of Agriculture Things (IoAT). Due to the requirements of more processing power for computations and predictions, the concept of Cloud-based smart agriculture is proposed for autonomic systems. This is where digital innovation and technology helps to improve the quality of life in the area of urbanization expansion. For the integration of cloud in smart agriculture, the system is shown to have security and privacy challenges, and most significantly, the identification of malicious and compromised nodes along with a secure transmission of information between sensors, cloud, and base station (BS). The identification of malicious and compromised node among soil sensors communicating with the BS is a notable challenge in the BS to cloud communications. The trust management mechanism is proposed as one of the solutions providing a lightweight approach to identify these nodes. In this article, we have proposed a novel trust management mechanism to identify malicious and compromised nodes by utilizing trust parameters. The trust mechanism is an event-driven process that computes trust based on the pre-defined time interval and utilizes the previous trust degree to develop an absolute trust degree. The system also maintains the trust degree of a BS and cloud service providers using distinct approaches. We have also performed extensive simulations to evaluate the performance of the proposed mechanism against several potential attacks. In addition, this research helps to create friendlier environments and efficient agricultural productions for the migration of people to the cities.

show abstract

ELC: Edge Linked Caching for content updating in information-centric Internet of Things

Cited by 23 publications

References 19 publications

A Classification of the Enabling Techniques for Low Latency and Reliable Communications in 5G and Beyond: AI-Enabled Edge Caching

A Classification of the Enabling Techniques for Low Latency and Reliable Communications in 5G and Beyond: AI-Enabled Edge Caching

Proactive Forensics in IoT: Privacy-Aware Log-Preservation Architecture in Fog-Enabled-Cloud Using Holochain and Containerization Technologies

AgriTrust—A Trust Management Approach for Smart Agriculture in Cloud-based Internet of Agriculture Things

Contact Info

Product

Resources

About