Lin He

Selected Publications

1. SIGCOMM

   P4runpro: Enabling Runtime Programmability for RMT Programmable Switches

   Yifan Yang, Lin He^#, Jiasheng Zhou, Xiaoyi Shi, Jiamin Cao, and Ying Liu

   In Proceedings of the 2024 Annual Conference of the ACM Special Interest Group on Data Communication (SIGCOMM)
   Sydney, Australia, August 4-8, 2024

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   Programmable switches have revolutionized network operations by enabling the flexible customization of packet processing logic using language like P4. However, changing the programs running on the switch requires disturbing traffic and suspending other unrelated programs. In this paper, we present P4runpro, enabling runtime data plane updates with dynamic resource allocation. The P4runpro data plane abstracts hardware resources and defines dynamically reconfigurable atomic operations that form packet processing logic. P4runpro provides runtime programming interfaces called P4runpro primitives for the operator to write high-level programs. We have designed the P4runpro compiler to automatically and consistently link the P4runpro programs to the running data plane. We implement our prototype on a Tofino switch. We implement 15 example runtime programs using P4runpro to demonstrate its generality and expressiveness. Our evaluation results show that compared to the state-of-the-art, P4runpro can respond within hundreds of milliseconds, achieve an average of 60% to 80% dynamic resource utilization, concurrently run ≈0.6K to ≈2.8K programs, and introduce lower overhead. Our case studies illustrate the benefit of runtime programming and prove the same functionality between P4runpro and conventional P4 programs.

   @inproceedings{yang2024p4runpro,
     title = {P4runpro: Enabling Runtime Programmability for RMT Programmable Switches},
     author = {Yang, Yifan and He, Lin and Zhou, Jiasheng and Shi, Xiaoyi and Cao, Jiamin and Liu, Ying},
     booktitle = {Proceedings of the 2024 Annual Conference of the ACM Special Interest Group on Data Communication (SIGCOMM)},
     year = {2024},
     pages = {921-937},
     doi = {10.1145/3651890.3672230},
     address = {Sydney, Australia},
     date = {August 4-8},
   }

2. INFOCOM

   AggDeliv: Aggregating Multiple Wireless Links for Efficient Mobile Live Video Delivery

   Jinlong E, Lin He, Zongyi Zhao, Yachen Wang, Gonglong Chen, and Wei Chen

   In Proceedings of the 43rd IEEE Conference on Computer Communications (INFOCOM)
   Vancouver, Canada, May 20–23, 2024

   Abs Bib HTML

   Mobile live-streaming applications with stringent latency and bandwidth requirements have gained tremendous attention in recent years. Encountered with bandwidth insufficiency and congestion instability of the wireless uplinks, multi-access networking provides opportunities to achieve fast and robust connectivity. However, the state-of-the-art multi-path transmission solutions are lack of adaptivity to the heterogeneous and dynamic nature of wireless networks. Meanwhile, the indispensable video coding and transformation bring about extra latency and make the video delivery vulnerable to network throughput fluctuation. This paper presents AggDeliv, a framework that provides efficient and robust multi-path transmission for mobile live video delivery. The key idea is to relate multi-path packet scheduling to congestion control optimization over diverse wireless links and adapt it to the mobile video characteristics. This is achieved by probabilistic packet allocation based on links’ congestion windows, wireless-oriented delay and loss aware congestion control, as well as lightweight video frame coding and network adaptive frame-packet transformation. Real-world evaluations demonstrate that our framework significantly outperforms the state-of-the-art solutions on aggregate goodput and streaming video bitrate.

   @inproceedings{e2024aggdeliv,
     title = {AggDeliv: Aggregating Multiple Wireless Links for Efficient Mobile Live Video Delivery},
     author = {E, Jinlong and He, Lin and Zhao, Zongyi and Wang, Yachen and Chen, Gonglong and Chen, Wei},
     booktitle = {Proceedings of the 43rd IEEE Conference on Computer Communications (INFOCOM)},
     year = {2024},
     pages = {1171-1180},
     doi = {10.1109/INFOCOM52122.2024.10621184},
     address = {Vancouver, Canada},
     date = {May 20–23},
   }

3. NDSS

   Your Router is My Prober: Measuring IPv6 Networks via ICMP Rate Limiting Side Channels

   Long Pan, Jiahai Yang, Lin He^#, Zhiliang Wang, Leyao Nie, Guanglei Song, and Yaozhong Liu

   In Proceedings of the 30th Annual Network and Distributed System Security Symposium (NDSS)
   San Diego, California, USA, February 27 – March 3, 2023

   🏆 Distinguished Paper Award

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   Active Internet measurements face challenges when some measurements require many remote vantage points. In this paper, we propose a novel technique for measuring remote IPv6 networks via side channels in ICMP rate limiting, a required function for IPv6 nodes to limit the rate at which ICMP error messages are generated. This technique, iVantage, can to some extent use 1.1M remote routers distributed in 9.5k autonomous systems and 182 countries as our “vantage points”.We apply iVantage to two different, but both challenging measurement tasks: 1) measuring the deployment of inbound source address validation (ISAV) and 2) measuring reachability between arbitrary Internet nodes. We accomplish these two tasks from only one local vantage point without controlling the targets or relying on other services within the target networks. Our large-scale ISAV measurements cover  50% of all IPv6 autonomous systems and find  79% of them are vulnerable to spoofing, which is the most large-scale measurement study of IPv6 ISAV to date. Our method for reachability measurements achieves over 80% precision and recall in our evaluation. Finally, we perform an Internet-wide measurement of the ICMP rate limiting implementations, present a detailed discussion on ICMP rate limiting, particularly the potential security and privacy risks in the mechanism of ICMP rate limiting, and provide possible mitigation measures. We make our code available to the community.

   @inproceedings{pan2023your,
     title = {Your Router is My Prober: Measuring IPv6 Networks via ICMP Rate Limiting Side Channels},
     author = {Pan, Long and Yang, Jiahai and He, Lin and Wang, Zhiliang and Nie, Leyao and Song, Guanglei and Liu, Yaozhong},
     booktitle = {Proceedings of the 30th Annual Network and Distributed System Security Symposium (NDSS)},
     year = {2023},
     publisher = {The Internet Society},
     address = {San Diego, California, USA},
     date = {February 27 – March 3},
   }

4. INFOCOM

   WiseCam: Wisely Tuning Wireless Pan-Tilt Cameras for Cost-Effective Moving Object Tracking

   Jinlong E, Lin He, Zhenhua Li, and Yunhao Liu

   In Proceedings of the 42nd IEEE Conference on Computer Communications (INFOCOM)
   New York area, USA, May 17–20, 2023

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   With desired functionality of moving object tracking, wireless pan-tilt cameras are able to play critical roles in a growing diversity of surveillance environments. However, today’s pan-tilt cameras oftentimes underperform when tracking frequently moving objects like humans – they are prone to lose sight of objects and bring about excessive mechanical rotations that are especially detrimental to those energy-constrained outdoor scenarios. The ineffectiveness and high cost of state-of-the-art tracking approaches are rooted in their adherence to the industry’s simplicity principle, which leads to their stateless nature, performing gimbal rotations based only on the latest object detection. To address the issues, we design and implement WiseCam that wisely tunes the pan-tilt cameras to minimize mechanical rotation costs while maintaining long-term object tracking. We examine the performance of WiseCam by experiments on two types of pan-tilt cameras with different motors. Results show that WiseCam significantly outperforms the state-of-the-art tracking approaches on both tracking duration and power consumption.

   @inproceedings{e2023wisecam,
     title = {WiseCam: Wisely Tuning Wireless Pan-Tilt Cameras for Cost-Effective Moving Object Tracking},
     author = {E, Jinlong and He, Lin and Li, Zhenhua and Liu, Yunhao},
     booktitle = {Proceedings of the 42nd IEEE Conference on Computer Communications (INFOCOM)},
     year = {2023},
     pages = {1-10},
     doi = {10.1109/INFOCOM53939.2023.10228926},
     address = {New York area, USA},
     date = {May 17–20},
   }

5. USENIX ATC

   AddrMiner: A Comprehensive Global Active IPv6 Address Discovery System

   Guanglei Song, Jiahai Yang^#, Lin He^#, Zhiliang Wang, Guo Li, Chenxin Duan, Yaozhong Liu, and Zhongxiang Sun

   In Proceedings of the 2022 USENIX Annual Technical Conference (USENIX ATC)
   Carlsbad, CA, USA, July 11–13, 2022

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   Fast Internet-wide scanning is essential for network situational awareness and asset evaluation. However, the vast IPv6 address space makes brute-force scanning infeasible. Although state-of-the-art techniques have made effective attempts, these methods do not work in seedless regions, while the detection efficiency is low in regions with seeds. Moreover, the constructed hitlists with low coverage cannot truly represent the active IPv6 address landscape of the Internet. This paper introduces AddrMiner, a global active IPv6 address probing system, making IPv6 active address probing systematic, comprehensive, and economical. We divide the IPv6 address space regions into three kinds according to the number of seed addresses and propose a probing algorithm for each of them. For the regions with no seeds, we propose AddrMiner-N, leveraging an organization association strategy to mine active addresses. It finds active addresses covering 86.4K BGP prefixes, accounting for 81.6% of the probed BGP prefixes. For the regions with few seeds, we propose AddrMiner-F, utilizing a similarity matching strategy to probe active addresses further. The hit rate of active address probing is improved by 70%-150% compared to existing algorithms. For the regions with sufficient seeds, we propose AddrMiner-S to generate target addresses based on reinforcement learning dynamically. It nearly doubles the hit rate compared to the state-of-the-art algorithms. Finally, we deploy AddrMiner and discover 2.1 billion active IPv6 addresses, including 1.7 billion de-aliased active addresses and 0.4 billion aliased addresses, through continuous probing for 13 months. We would like to further open the door of IPv6 measurement studies by publicly releasing AddrMiner and sharing our data.

   @inproceedings{song2022addeminer,
     title = {AddrMiner: A Comprehensive Global Active IPv6 Address Discovery System},
     author = {Song, Guanglei and Yang, Jiahai and He, Lin and Wang, Zhiliang and Li, Guo and Duan, Chenxin and Liu, Yaozhong and Sun, Zhongxiang},
     booktitle = {Proceedings of the 2022 USENIX Annual Technical Conference (USENIX ATC)},
     year = {2022},
     isbn = {978-1-939133-29-19},
     address = {Carlsbad, CA, USA},
     date = {July 11–13},
     pages = {309--326},
     url = {https://www.usenix.org/conference/atc22/presentation/song},
     publisher = {USENIX Association},
   }

6. USENIX ATC

   Firebolt: Finding Bugs in Programmable Data Plane Generators

   Jiamin Cao, Yu Zhou, Chen Sun, Lin He, Zhaowei Xi, and Ying Liu

   In Proceedings of the 2022 USENIX Annual Technical Conference (USENIX ATC)
   Carlsbad, CA, USA, July 11–13, 2022

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   Programmable data planes (DP) enable flexible customization of packet processing logic with domain-specific languages such as P4. To relieve developers from lengthy codes and tedious hardware details, many researches propose DP program generators that take high-level intents as input and automatically convert intents into DP programs. Generators must be correct, otherwise they may produce buggy programs or DP logic that is inconsistent with intents. Nevertheless, existing verification tools are designed to verify individual DP programs, not generators. They either cannot achieve high bug coverage or cannot debug generators with high scalability. This paper presents Firebolt, a blackbox testing tool designed to dig out faults in DP program generators, including security vulnerabilities, intent violations, and generator crash. Firebolt achieves high bug coverage by using syntax-guided intent generation to construct a comprehensive, syntactically correct, and semantically valid intent set. To avoid intent explosion, Firebolt designs an intent space pruning approach that eliminates redundant intents while preserving representative ones. For high scalability, Firebolt automatically formalizes DP programs and intents for verification. We apply Firebolt to three popular open-source DP generators. Evaluation results demonstrate that Firebolt can detect 2x bugs with 0.1% to 0.01% human efforts compared to existing tools.

   @inproceedings{cao2022firebolt,
     title = {Firebolt: Finding Bugs in Programmable Data Plane Generators},
     author = {Cao, Jiamin and Zhou, Yu and Sun, Chen and He, Lin and Xi, Zhaowei and Liu, Ying},
     booktitle = {Proceedings of the 2022 USENIX Annual Technical Conference (USENIX ATC)},
     year = {2022},
     isbn = {978-1-939133-29-32},
     address = {Carlsbad, CA, USA},
     date = {July 11–13},
     pages = {819--834},
     url = {https://www.usenix.org/conference/atc22/presentation/cao},
     publisher = {USENIX Association},
   }

7. INFOCOM

   Bootstrapping Accountability and Privacy to IPv6 Internet without Starting from Scratch

   Lin He, Gang Ren, and Ying Liu

   In Proceedings of the 38th IEEE Conference on Computer Communications (INFOCOM)
   Paris, France, April 29 - May 2, 2019

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   Accountability and privacy are considered valuable but conflicting properties in the Internet, which at present does not provide native support for either. Past efforts to balance accountability and privacy in the Internet have unsatisfactory deployability due to the introduction of new communication identifiers, and because of large-scale modifications to fully deployed infrastructures and protocols. The IPv6 is being deployed around the world and this trend will accelerate. In this paper, we propose a private and accountable proposal based on IPv6 called PAVI that seeks to bootstrap accountability and privacy to the IPv6 Internet without introducing new communication identifiers and large-scale modifications to the deployed base. A dedicated quantitative analysis shows that the proposed PAVI achieves satisfactory levels of accountability and privacy. The results of evaluation of a PAVI prototype show that it incurs little performance overhead, and is widely deployable.

   @inproceedings{he2019bootstrapping,
     title = {Bootstrapping Accountability and Privacy to IPv6 Internet without Starting from Scratch},
     author = {He, Lin and Ren, Gang and Liu, Ying},
     booktitle = {Proceedings of the 38th IEEE Conference on Computer Communications (INFOCOM)},
     year = {2019},
     pages = {1486-1494},
     doi = {10.1109/INFOCOM.2019.8737453},
     address = {Paris, France},
     date = {April 29 - May 2},
   }

1. TMC

   WiseCam: A Systematic Approach to Intelligent Pan-Tilt Cameras for Moving Object Tracking

   Jinlong E, Fangshuo Han, Lin He, Wei Xu, Zhenhua Li, Yunpeng Chai, and Yunhao Liu

   IEEE Transactions on Mobile Computing, 2024

   Abs Bib HTML

   With the desired functionality of moving object tracking, wireless pan-tilt cameras are able to play critical roles in a growing diversity of surveillance environments. However, today’s pan-tilt cameras oftentimes underperform when tracking frequently moving objects like humans – they are prone to lose sight of objects and bring about excessive mechanical rotations that are especially detrimental to those energy-constrained outdoor scenarios. The ineffectiveness and high cost of all state-of-the-art tracking approaches are rooted in their adherence to the industry’s simplicity principle, which leads to their stateless nature, performing gimbal rotations based only on the latest object detection. To address the issues, we design and implement WiseCam that wisely tunes the pan-tilt cameras to minimize mechanical rotation costs while maintaining long-term object tracking. This systematic tracking approach also tackles issues of motion-rotation speed gap and scattered moving objects, which is universally applicable to complex tracking scenarios. We examine the performance of WiseCam by experiments on two types of pan-tilt cameras with different motors. Results show that it significantly outperforms the state-of-the-art tracking approaches on both tracking duration and power consumption.

   @article{e2024wisecam,
     title = {WiseCam: A Systematic Approach to Intelligent Pan-Tilt Cameras for Moving Object Tracking},
     author = {E, Jinlong and Han, Fangshuo and He, Lin and Xu, Wei and Li, Zhenhua and Chai, Yunpeng and Liu, Yunhao},
     journal = {IEEE Transactions on Mobile Computing},
     year = {2024},
     volume = {},
     number = {},
     pages = {},
     publisher = {IEEE},
     doi = {10.1109/TMC.2024.3410645},
   }

2. TON

   AddrMiner: A Fast, Efficient, and Comprehensive Global Active IPv6 Address Detection System

   Guanglei Song, Lin He^#, Feiyu Zhu, Jinlei Lin, Lina Fan, Chenglong Li, Zhiliang Wang, and Jiahai Yang^#

   IEEE/ACM Transactions on Networking, 2024

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   Fast Internet-wide scanning is essential for network situational awareness and asset evaluation. However, the vast IPv6 address space makes brute-force scanning infeasible. Despite advancements in state-of-the-art methods, they do not work in seedless regions and suffer low detection efficiency and speed in regions with seed addresses. Moreover, the collected active address list (i.e., IPv6 hitlist) with low coverage cannot truly represent the active IPv6 address landscape of the Internet. This paper introduces AddrMiner, a fast, efficient, and comprehensive global active IPv6 address detection system. We design a systematic active IPv6 address detection strategy that divides the IPv6 space into two detection scenarios based on the presence or absence of seed addresses to discover active IPv6 addresses from scratch and from few to many. In the seedless regions, we present AddrMiner-N, leveraging a multi-level association policy to probe active addresses. It fills the gap of address detection in seedless regions and successfully discovers active addresses in 39,899 BGP prefixes without seed addresses, with a 1.03X higher hit rate, 30∼911X higher speed, and 2.7X broader coverage, compared to existing solutions. In the regions with seed addresses, our method AddrMiner-S dynamically generates target addresses using reinforcement learning. Compared to state-of-the-art methods, AddrMiner-S achieves an impressive 56.3% hit rate and a discovery speed of 839.0/s, which is 1.9∼2153X and 1.5∼755X of existing works, respectively. Finally, we deploy AddrMiner and discover 2.1B active IPv6 addresses, including 1.7B de-aliased active addresses and 0.4B aliased addresses, through continuous probing for three years.

   @article{song2024addrminer,
     title = {AddrMiner: A Fast, Efficient, and Comprehensive Global Active IPv6 Address Detection System},
     author = {Song, Guanglei and He, Lin and Zhu, Feiyu and Lin, Jinlei and Fan, Lina and Li, Chenglong and Wang, Zhiliang and Yang, Jiahai},
     journal = {IEEE/ACM Transactions on Networking},
     year = {2024},
     volume = {32},
     pages = {3870-3887},
     publisher = {IEEE},
     doi = {10.1109/TNET.2024.3406508},
   }

3. TMC

   AutoIoT: Automatically Updated IoT Device Identification with Semi-supervised Learning

   Linna Fan, Lin He^#, Yichao Wu, Shize Zhang, Zhiliang Wang, Jia Li, Jiahai Yang^#, Chaocan Xiang, and Xiaoqian Ma

   IEEE Transactions on Mobile Computing, 2023

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   IoT devices bring great convenience to a person’s life and industrial production. However, their rapid proliferation also troubles device management and network security. Network administrators usually need to know how many IoT devices are in the network and whether they behave normally. IoT device identification is the first step to achieving these goals. Previous IoT device identification methods reach high accuracy in a closed environment. But they are not applicable in the continuously changing environment. When new types of devices are plugged in, they cannot update themselves automatically. Besides, they usually rely on supervised learning and need lots of labeled data, which is costly. To solve these problems, we propose a novel IoT device identification model named AutoIoT, updating itself automatically when new types of devices are plugged in. Besides, it only needs a few labeled data and identifies IoT devices with high accuracy. The evaluation on two public datasets shows that AutoIoT can identify new device types only using 1.5∼2.5 hours’ traffic and still have high accuracy after updating. Moreover, it has a better performance than other works when there are only a few labeled data, especially in an environment with scanning traffic.

   @article{fan2022autoiot,
     title = {AutoIoT: Automatically Updated IoT Device Identification with Semi-supervised Learning},
     author = {Fan, Linna and He, Lin and Wu, Yichao and Zhang, Shize and Wang, Zhiliang and Li, Jia and Yang, Jiahai and Xiang, Chaocan and Ma, Xiaoqian},
     journal = {IEEE Transactions on Mobile Computing},
     year = {2023},
     volume = {22},
     number = {10},
     pages = {5769-5786},
     publisher = {IEEE},
     doi = {10.1109/TMC.2022.3183118},
   }

4. TON

   DET: Enabling Efficient Probing of IPv6 Active Addresses

   Guanglei Song, Jiahai Yang, Zhiliang Wang, Lin He^#, Jinlei Lin, Long Pan, Chenxin Duan, and Xiaowen Quan

   IEEE/ACM Transactions on Networking, 2022

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   Fast IPv4 scanning significantly improves network measurement and security research. Nevertheless, it is infeasible to perform brute-force scanning of the IPv6 address space. Alternatively, one can find active IPv6 addresses through scanning the candidate addresses generated by state-of-the-art algorithms. However, the probing efficiency of such algorithms is often very low. In this paper, our objective is to improve the probing efficiency of IPv6 addresses. We first perform a longitudinal active measurement study and build a high-quality dataset, hitlist, including more than 1.95,B IPv6 addresses distributed in 58.2,K BGP prefixes and collected over 17 months period. Different from the previous works, we probe the announced BGP prefixes using a pattern-based algorithm. This results in a dataset without uneven address distribution and low active rates. Further, we propose an efficient address generation algorithm, DET, which builds a density space tree to learn high-density address regions of the seed addresses with linear time complexity and improves the active addresses’ probing efficiency. We then compare our algorithm DET against state-of-the-art algorithms on the public hitlist and our hitlist by scanning 50,M addresses. Our analysis shows that DET increases the de-aliased active address ratio and active address (including aliased addresses) ratio by 10%, and 14%, respectively. Furthermore, we develop a fingerprint-based method to detect aliased prefixes. The proposed method for the first time directly verifies whether the prefix is aliased or not. Our method finds that 10.64% of the public aliased prefixes are false positive.

   @article{song2022det,
     title = {DET: Enabling Efficient Probing of IPv6 Active Addresses},
     author = {Song, Guanglei and Yang, Jiahai and Wang, Zhiliang and He, Lin and Lin, Jinlei and Pan, Long and Duan, Chenxin and Quan, Xiaowen},
     journal = {IEEE/ACM Transactions on Networking},
     year = {2022},
     volume = {30},
     number = {4},
     pages = {1629-1643},
     doi = {10.1109/TNET.2022.3145040},
   }

5. TON

   TurboNet: Faithfully Emulating Networks with Programmable Switches

   Jiamin Cao, Ying Liu, Yu Zhou, Lin He^#, and Mingwei Xu

   IEEE/ACM Transactions on Networking, 2022

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   Faithfully emulating networks is critical for verifying the correctness and effectiveness of new networking-related designs. Existing network experiment platforms either cannot faithfully emulate the functionality and performance of production networks or cannot scale well due to cost constraints. In this paper, we propose TurboNet, a new network emulator that utilizes one or more programmable switches to achieve faithful emulation of the network data plane and control plane. For data plane emulation, we propose a series of key designs, such as port mapper, queue mapper, and delayed queue, to emulate network topologies and performance metrics with high flexibility and accuracy. For control plane emulation, we support static routing configurations, distributed routing agents, and the centralized routing controllers. Meanwhile, we provide APIs for operators to simplify network emulation tasks. We implement TurboNet on Tofino switches. Evaluation results show that: (1) On the data plane, TurboNet can flexibly emulate various topologies, such as an 8-ary fat-tree with only one programmable switch and a 10-ary fat-tree with four programmable switches; (2) On the control plane, TurboNet supports about 200 BGP agents on a single programmable switch with a CPU usage of 25%; (3) TurboNet can accurately emulate different network performance metrics such as 10⁻⁸ link loss, and microsecond to millisecond link delay.

   @article{cao2022turbonet,
     title = {TurboNet: Faithfully Emulating Networks with Programmable Switches},
     author = {Cao, Jiamin and Liu, Ying and Zhou, Yu and He, Lin and Xu, Mingwei},
     journal = {IEEE/ACM Transactions on Networking},
     year = {2022},
     volume = {30},
     number = {3},
     pages = {1395-1409},
     doi = {10.1109/TNET.2022.3142126},
   }

6. TPDS

   CoFilter: High-Performance Switch-Accelerated Stateful Packet Filter for Bare-Metal Servers

   Jiamin Cao, Ying Liu, Yu Zhou, Lin He, Chen Sun, Yangyang Wang, and Mingwei Xu

   IEEE Transactions on Parallel and Distributed Systems, 2022

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   As one of the most critical cloud services, Bare-Metal Servers (BMS) introduce stringent performance requirements on data center networks (DCN). Stateful packet filter is an integral DCN component of ensuring connection security for BMS. However, the off-the-shelf stateful packet filters either are costly for cloud DCNs or introduce significant performance bottlenecks. In this article, we present CoFilter , which leverages low-cost programmable switches to accelerate the stateful packet filter for BMS. CoFilter uses (1) stateful process partition to enable complex stateful packet filtering logic on programmability-limited switching ASICs, (2) state compression to track tens of millions of connections with constrained hardware memory, and (3) per-tenant packet rate limit and tenant-aware flow migration to achieve efficient performance isolation among different tenants. Overall, CoFilter implements a high-performance stateful packet filter via the co-design of programmable switching ASIC and CPU. We evaluate CoFilter under various data center traffic traces with real-world flow distributions. The evaluation results show that CoFilter remarkably outperforms NetFilter, i.e., forwarding packets at line rate (13x throughput of NetFilter), keeping packet delay within 1us, and freeing a significant quantity of CPU cores, with rather small memory usage, i.e., accommodating over 107 connections with only 16MB SRAM.

   @article{cao2021cofilter,
     title = {CoFilter: High-Performance Switch-Accelerated Stateful Packet Filter for Bare-Metal Servers},
     author = {Cao, Jiamin and Liu, Ying and Zhou, Yu and He, Lin and Sun, Chen and Wang, Yangyang and Xu, Mingwei},
     journal = {IEEE Transactions on Parallel and Distributed Systems},
     year = {2022},
     volume = {33},
     number = {9},
     pages = {2249-2262},
     doi = {10.1109/TPDS.2021.3136575},
   }

7. TON

   PAVI: Bootstrapping Accountability and Privacy to IPv6 Internet

   Lin He, Gang Ren, Ying Liu, and Jiahai Yang

   IEEE/ACM Transactions on Networking, 2021

   Abs Bib HTML

   Accountability and privacy are considered valuable but conflicting properties in the Internet, which at present does not provide native support for either. Past efforts to balance accountability and privacy in the Internet have unsatisfactory deployability due to the introduction of new communication identifiers, and because of large-scale modifications to fully deployed infrastructures and protocols. The IPv6 is being deployed around the world and this trend will accelerate. In this paper, we propose a private and accountable proposal based on IPv6 called PAVI that seeks to bootstrap accountability and privacy to the IPv6 Internet without introducing new communication identifiers and large-scale modifications to the deployed base. A dedicated quantitative analysis shows that the proposed PAVI achieves satisfactory levels of accountability and privacy. The results of the evaluation of a PAVI prototype show that it incurs little performance overhead, and is widely deployable.

   @article{he2021pavi,
     title = {PAVI: Bootstrapping Accountability and Privacy to IPv6 Internet},
     author = {He, Lin and Ren, Gang and Liu, Ying and Yang, Jiahai},
     journal = {IEEE/ACM Transactions on Networking},
     year = {2021},
     volume = {29},
     number = {2},
     pages = {695-708},
     doi = {10.1109/TNET.2020.3047667},
   }