Without physical boundaries, a wireless network faces many more security threats than a wired network does. Therefore, in the IEEE 802.16 standard a security sublayer is specified in the MAC layer to address the privacy issues across the fixed Broadband Wireless Access (BWA). Several articles have been published to address the flaws in IEEE 802.16 security after the IEEE standard 802.16-2001 was released. However, the IEEE standard 802.16-2004 revision does not settle all the discovered problems and additional flaws remain. This paper gives an overview of the IEEE 802.16 standard, focusing on the MAC layer and especially the security sublayer. We analyze the security flaws in the standard as well as in related works, and illustrate possible attacks to the authentication and key management protocols. Possible solutions are also proposed to prevent these attacks. Finally, we propose a security handover protocol that should be supported in the future 802.16e for mobility.
Without physical boundaries, a wireless network faces many more vulnerabilities than a wired network does. IEEE802.16 provides a security sublayer in the MAC layer to address the privacy issues across the fixed BWA (Broadband Wireless Access). Several articles have been published to address the flaws in IEEE802.16 security after IEEE802.16-2001 was released. However, even the enhanced version IEEE802.16-2004 does not settle all the problems and additional flaws emerge. In addition, we found that PKM (Privacy and Key Management) protocols version 2 (PKMv2), proposed by recently released IEEE802.16e, is also vulnerable to new attacks. In this paper, we first overview the IEEE802.16 standard, especially the security sublayer, and then investigate possible attacks on the basic PKM protocol in IEEE802.16 as well as in its other versions from related works and the newest PKMv2. We also give possible solutions to counter those attacks and verify our analysis using formal (BAN) logic.
Multicast enables efficient large-scale content distribution and has become more and more popular in network service. Security is a critical issue for multicast because many applications require access control and privacy. This issue is more sensitive to wireless network, which is lack of physical boundaries. IEEE 802.16 is the standard for next generation wireless network, which aims to provide the last mile access for Wireless Metropolitan Area Network (WirelessMAN). Multicast is also supported in IEEE 802.16, and a Multicast and Broadcast Rekeying Algorithm (MBRA) was proposed in the standard as an optional function for secure multicast. However, this algorithm does not provide backward and forward secrecy. It is not scalable to a large group either. This paper reviews the above two deficiencies of MBRA and proposes revision to address these problems for Intra-BS multicast. We also propose algorithms for secure multicast in different scenarios of WirelessMAN besides its basic schema, including Inter-BS multicast, multicast for mesh network, and multicast during handover.
Multicast delivery of data is a powerful mechanism that has strong potential in next generation networks. The increased efficiency over unicast is a definite advantage, but the use of multicast poses many security risks. Effectively adding security measures to a multicast service is an intriguing problem, especially when the service is deployed in a wireless setting. Next generation IEEE 802.16 standard WirelessMAN networks are a perfect example of this problem, and the latest draft specification of the standard includes a secure protocol solution called Multicast and Broadcast Rekeying Algorithm (MBRA). In this paper, we expose the security problems of MBRA, including non-scalability and omission of backward and forward secrecy, and propose a new approach, ELAPSE, to address these problems. We analyze the security property of ELAPSE and use Qualnet simulations to show its efficiency. Index Terms-802.16 WirelessMAN, Privacy and Key Management (PKM) Protocol, Multicast and Broadcast Rekeying Algorithm (MBRA) 1-4244-0523-8/07/$20.00 ©2007 IEEE
Deep convolutional networks have better smoke recognition performance. However, a lightweight network model and high recognition accuracy cannot be balanced when deployed on hardware with limited computing resources such as edge computing. Based on this background, we propose a novel smoke recognition network that combines convolutional networks (CNN) and self-attention. The core ideas of this framework are as follows: (1) Combine the depthwise convolution and asymmetric convolution of large convolution kernels to construct a lightweight CNN model, and realize multiscale extraction of feature information with slight model complexity. (2) Combined with the self-attention in transformer, a skip-connection branch is designed, which improves the feature extraction capability of the backbone network through parallel processing and fusion of feature map information. (3) Fusion multicomponent discrete cosine transform (DCT) is used to compress channel information and expand the ability of global average pooling (GAP) to aggregate feature maps. The proposed DCT-GAP improves the accuracy of the network without adding additional computational costs. Experimental results show that the proposed CSANet achieves an average accuracy of over 98.3% with 238 M FLOPs and 5.8 M parameters on the homemade smoke dataset, outperforming state-of-the-art competitors.
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