• Title/Summary/Keyword: Secure connectivity probability

Search Result 4, Processing Time 0.023 seconds

Secure Connectivity Probability of Multi-hop Clustered Randomize-and-Forward Networks

  • Wang, Xiaowei;Su, Zhou;Wang, Guangyi
    • ETRI Journal
    • /
    • v.39 no.5
    • /
    • pp.729-736
    • /
    • 2017
  • This work investigates secure cluster-aided multi-hop randomize-and-forward networks. We present a hop-by-hop multi-hop transmission scheme with relay selection, which evaluates for each cluster the relays that can securely receive the message. We propose an analytical model to derive the secure connectivity probability (SCP) of the hop-by-hop transmission scheme. For comparison, we also analyze SCPs of traditional end-to-end transmission schemes with two relay-selection policies. We perform simulations, and our analytical results verify that the proposed hop-by-hop scheme is superior to end-to-end schemes, especially with a large number of hops or high eavesdropper channel quality. Numerical results also show that the proposed hop-by-hop scheme achieves near-optimal performance in terms of the SCP.

ST Reliability and Connectivity of VANETs for Different Mobility Environments

  • Saajid, Hussain;DI, WU;Memon, Sheeba;Bux, Naadiya Khuda
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.13 no.5
    • /
    • pp.2338-2356
    • /
    • 2019
  • Vehicular ad-hoc network (VANET) is the name of technology, which uses 'mobile internet' to facilitate communication between vehicles. The aim is to ensure road safety and achieve secure communication. Therefore, the reliability of this type of networks is a serious concern. The reliability of VANET is dependent upon proper communication between vehicles within a given amount of time. Therefore a new formula is introduced, the terms of the new formula correspond 1 by 1 to a class special ST route (SRORT). The new formula terms are much lesser than the Inclusion-Exclusion principle. An algorithm for the Source-to-Terminal reliability was presented, the algorithm produced Source-to-Terminal reliability or computed a Source-to-Terminal reliability expression by calculating a class of special networks of the given network. Since the architecture of this class of networks which need to be computed was comparatively trivial, the performance of the new algorithm was superior to the Inclusion-Exclusion principle. Also, we introduce a mobility metric called universal speed factor (USF) which is the extension of the existing speed factor, that suppose same speed of all vehicles at every time. The USF describes an exact relation between the relative speed of consecutive vehicles and the headway distance. The connectivity of vehicles in different mobile situations is analyzed using USF i.e., slow mobility connectivity, static connectivity, and high mobility connectivity. It is observed that $p_c$ probability of connectivity is directly proportional to the mean speed ${\mu}_{\nu}$ till specified threshold ${\mu}_{\tau}$, and decreases after ${\mu}_{\tau}$. Finally, the congested network is connected strongly as compared to the sparse network as shown in the simulation results.

A Secure Key Predistribution Scheme for WSN Using Elliptic Curve Cryptography

  • Rajendiran, Kishore;Sankararajan, Radha;Palaniappan, Ramasamy
    • ETRI Journal
    • /
    • v.33 no.5
    • /
    • pp.791-801
    • /
    • 2011
  • Security in wireless sensor networks (WSNs) is an upcoming research field which is quite different from traditional network security mechanisms. Many applications are dependent on the secure operation of a WSN, and have serious effects if the network is disrupted. Therefore, it is necessary to protect communication between sensor nodes. Key management plays an essential role in achieving security in WSNs. To achieve security, various key predistribution schemes have been proposed in the literature. A secure key management technique in WSN is a real challenging task. In this paper, a novel approach to the above problem by making use of elliptic curve cryptography (ECC) is presented. In the proposed scheme, a seed key, which is a distinct point in an elliptic curve, is assigned to each sensor node prior to its deployment. The private key ring for each sensor node is generated using the point doubling mathematical operation over the seed key. When two nodes share a common private key, then a link is established between these two nodes. By suitably choosing the value of the prime field and key ring size, the probability of two nodes sharing the same private key could be increased. The performance is evaluated in terms of connectivity and resilience against node capture. The results show that the performance is better for the proposed scheme with ECC compared to the other basic schemes.

A Key Management Technique Based on Topographic Information Considering IoT Information Errors in Cloud Environment (클라우드 환경에서 IoT 정보 오류를 고려한 지형 정보 기반의 키 관리 기법)

  • Jeong, Yoon-Su;Choi, Jeong-hee
    • Journal of Digital Convergence
    • /
    • v.18 no.10
    • /
    • pp.233-238
    • /
    • 2020
  • In the cloud environment, IoT devices using sensors and wearable devices are being applied in various environments, and technologies that accurately determine the information generated by IoT devices are being actively studied. However, due to limitations in the IoT environment such as power and security, information generated by IoT devices is very weak, so financial damage and human casualties are increasing. To accurately collect and analyze IoT information, this paper proposes a topographic information-based key management technique that considers IoT information errors. The proposed technique allows IoT layout errors and groups topographic information into groups of dogs in order to secure connectivity of IoT devices in the event of arbitrary deployment of IoT devices in the cloud environment. In particular, each grouped terrain information is assigned random selected keys from the entire key pool, and the key of the terrain information contained in the IoT information and the probability-high key values are secured with the connectivity of the IoT device. In particular, the proposed technique can reduce information errors about IoT devices because the key of IoT terrain information is extracted by seed using probabilistic deep learning.