Ethereum, currently the most widely utilized smart contracts platform, anchors the security of myriad smartcontracts upon its own robustness. Its foundational peer-to-peer network facilitates a dependable node connect...Ethereum, currently the most widely utilized smart contracts platform, anchors the security of myriad smartcontracts upon its own robustness. Its foundational peer-to-peer network facilitates a dependable node connectionmechanism, whereas an efficient data-sharing protocol constitutes as the bedrock of Blockchain network security.In this paper, we propose NodeHunter, an Ethereum network detector implemented through the application ofsimulation technology, which is capable of aggregating all node records within the network and the interconnectednessbetween them. Utilizing this connection information, NodeHunter can procure more comprehensive insightsfor network status analysis compared to preceding detection methodologies. Throughout a three-month period ofunbroken surveillance of the Ethereum network, we obtained an excess of two million node records along with overone hundred million node acquaintances. Analysis of the gathered data revealed that an alarming 49% or more ofthese node records were maliciously forged.展开更多
The administrators of data center networks have to continually monitor path latency to detect network anomaly quickly and ensure the efficient operation of the networks. In this work, we propose Link Layer Measurement...The administrators of data center networks have to continually monitor path latency to detect network anomaly quickly and ensure the efficient operation of the networks. In this work, we propose Link Layer Measurement Protocol （LLMP）, a prototype latency measuring framework based on the Link Layer Discovery Protocol （LLDP）. LLDP is utilized by the controller to discover network topology dynamically. We insert timestamps into the optional LLDPTLV field in LLDP, so that the controller can estimate latency on any single link. The framework utilizes a reactive measurement approach without injecting any probe packets to the network. Our experiments show that the latency of a link can be measured accurately by LLMP. In relatively complex network conditions, LLMP can still maintain a high accuracy. We store the LLMP measurement results into a latency matrix, which can be used to infer the path latency.展开更多
基金the National Key Research and Development Program of China(No.2020YFB1005805)Peng Cheng Laboratory Project(Grant No.PCL2021A02)+2 种基金Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies(2022B1212010005)Shenzhen Basic Research(General Project)(No.JCYJ20190806142601687)Shenzhen Stable Supporting Program(General Project)(No.GXWD20201230155427003-20200821160539001).
文摘Ethereum, currently the most widely utilized smart contracts platform, anchors the security of myriad smartcontracts upon its own robustness. Its foundational peer-to-peer network facilitates a dependable node connectionmechanism, whereas an efficient data-sharing protocol constitutes as the bedrock of Blockchain network security.In this paper, we propose NodeHunter, an Ethereum network detector implemented through the application ofsimulation technology, which is capable of aggregating all node records within the network and the interconnectednessbetween them. Utilizing this connection information, NodeHunter can procure more comprehensive insightsfor network status analysis compared to preceding detection methodologies. Throughout a three-month period ofunbroken surveillance of the Ethereum network, we obtained an excess of two million node records along with overone hundred million node acquaintances. Analysis of the gathered data revealed that an alarming 49% or more ofthese node records were maliciously forged.
基金This work was supported by the National Natural Science Foundation of China under Grant Nos. 61379145, 61501482, 61762033.
文摘The administrators of data center networks have to continually monitor path latency to detect network anomaly quickly and ensure the efficient operation of the networks. In this work, we propose Link Layer Measurement Protocol （LLMP）, a prototype latency measuring framework based on the Link Layer Discovery Protocol （LLDP）. LLDP is utilized by the controller to discover network topology dynamically. We insert timestamps into the optional LLDPTLV field in LLDP, so that the controller can estimate latency on any single link. The framework utilizes a reactive measurement approach without injecting any probe packets to the network. Our experiments show that the latency of a link can be measured accurately by LLMP. In relatively complex network conditions, LLMP can still maintain a high accuracy. We store the LLMP measurement results into a latency matrix, which can be used to infer the path latency.
