@article{huang_huang_xiao_wang_li_dai_2020, title={An Improved Broadcast Authentication Protocol for Wireless Sensor Networks Based on the Self-Reinitializable Hash Chains}, volume={2020}, ISSN={["1939-0122"]}, DOI={10.1155/2020/8897282}, abstractNote={Broadcast authentication is a fundamental security primitive in wireless sensor networks (WSNs), which is a critical sensing component of IoT. Although symmetric-key-based <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mi>μ</mml:mi></mml:math>TESLA protocol has been proposed, some concerns about the difficulty of predicting the network lifecycle in advance and the security problems caused by an overlong long hash chain still remain. This paper presents a scalable broadcast authentication scheme named DH-<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mi>μ</mml:mi></mml:math>TESLA, which is an extension and improvement of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M3"><mml:mi>μ</mml:mi></mml:math>TESLA and Multilevel <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M4"><mml:mi>μ</mml:mi></mml:math>TESLA, to achieve several vital properties, such as infinite lifecycle of hash chains, security authentication, scalability, and strong tolerance of message loss. The proposal consists of the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M5"><mml:mfenced open="(" close=")" separators="|"><mml:mrow><mml:mi>t</mml:mi><mml:mo>,</mml:mo><mml:mi>n</mml:mi></mml:mrow></mml:mfenced></mml:math>-threshold-based self-reinitializable hash chain scheme (SRHC-TD) and the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M6"><mml:mi>d</mml:mi></mml:math>-left-counting-Bloom-filter-based authentication scheme (AdlCBF). In comparison to other broadcast authentication protocols, our proposal achieves more security properties such as fresh node’s participation and DoS resistance. Furthermore, the reinitializable hash chain constructed in SRHC-TD is proved to be secure and has less computation and communication overhead compared with typical solutions, and efficient storage is realized based on AdlCBF, which can also defend against DoS attacks.}, journal={SECURITY AND COMMUNICATION NETWORKS}, author={Huang, Haiping and Huang, Qinglong and Xiao, Fu and Wang, Wenming and Li, Qi and Dai, Ting}, year={2020}, month={Sep} }
 @article{tunde-onadele_he_dai_gu_2019, title={A Study on Container Vulnerability Exploit Detection}, ISSN={["2373-3845"]}, DOI={10.1109/IC2E.2019.00026}, abstractNote={Containers have become increasingly popular for deploying applications in cloud computing infrastructures. However, recent studies have shown that containers are prone to various security attacks. In this paper, we conduct a study on the effectiveness of various vulnerability detection schemes for containers. Specifically, we implement and evaluate a set of static and dynamic vulnerability attack detection schemes using 28 real world vulnerability exploits that widely exist in docker images. Our results show that the static vulnerability scanning scheme only detects 3 out of 28 tested vulnerabilities and dynamic anomaly detection schemes detect 22 vulnerability exploits. Combining static and dynamic schemes can further improve the detection rate to 86% (i.e., 24 out of 28 exploits). We also observe that the dynamic anomaly detection scheme can achieve more than 20 seconds lead time (i.e., a time window before attacks succeed) for a group of commonly seen attacks in containers that try to gain a shell and execute arbitrary code.}, journal={2019 IEEE INTERNATIONAL CONFERENCE ON CLOUD ENGINEERING (IC2E)}, author={Tunde-Onadele, Olufogorehan and He, Jingzhu and Dai, Ting and Gu, Xiaohui}, year={2019}, pages={121–127} }
 @article{kang_dai_jean-louis_tao_gu_2019, title={FabZK: Supporting Privacy-Preserving, Auditable Smart Contracts in Hyperledger Fabric}, ISSN={["1530-0889"]}, DOI={10.1109/DSN.2019.00061}, abstractNote={On a Blockchain network, transaction data are exposed to all participants. To preserve privacy and confidentiality in transactions, while still maintaining data immutability, we design and implement FabZK. FabZK conceals transaction details on a shared ledger by storing only encrypted data from each transaction (e.g., payment amount), and by anonymizing the transactional relationship (e.g., payer and payee) between members in a Blockchain network. It achieves both privacy and auditability by supporting verifiable Pedersen commitments and constructing zero-knowledge proofs. FabZK is implemented as an extension to the open source Hyperledger Fabric. It provides APIs to easily enable data privacy in both client code and chaincode. It also supports on-demand, automated auditing based on encrypted data. Our evaluation shows that FabZK offers strong privacy-preserving capabilities, while delivering reasonable performance for the applications developed based on its framework.}, journal={2019 49TH ANNUAL IEEE/IFIP INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS AND NETWORKS (DSN 2019)}, author={Kang, Hui and Dai, Ting and Jean-Louis, Nerla and Tao, Shu and Gu, Xiaohui}, year={2019}, pages={543–555} }
 @article{dai_dean_wang_gu_lu_2019, title={Hytrace: A Hybrid Approach to Performance Bug Diagnosis in Production Cloud Infrastructures}, volume={30}, ISSN={["1558-2183"]}, DOI={10.1109/TPDS.2018.2858800}, abstractNote={Server applications running inside production cloud infrastructures are prone to various performance problems (e.g., software hang, performance slowdown). When those problems occur, developers often have little clue to diagnose those problems. In this paper, we present Hytrace, a novel hybrid approach to diagnosing performance problems in production cloud infrastructures. Hytrace combines rule-based static analysis and runtime inference techniques to achieve higher bug localization accuracy than pure-static and pure-dynamic approaches for performance bugs. Hytrace does not require source code and can be applied to both compiled and interpreted programs such as C/C++ and Java. We conduct experiments using real performance bugs from seven commonly used server applications in production cloud infrastructures. The results show that our approach can significantly improve the performance bug diagnosis accuracy compared to existing diagnosis techniques.}, number={1}, journal={IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS}, author={Dai, Ting and Dean, Daniel and Wang, Peipei and Gu, Xiaohui and Lu, Shan}, year={2019}, month={Jan}, pages={107–118} }
 @article{he_dai_gu_2019, title={TFix: Automatic Timeout Bug Fixing in Production Server Systems}, ISSN={["1063-6927"]}, DOI={10.1109/ICDCS.2019.00067}, abstractNote={Timeout is widely used to handle unexpected failures in distributed systems. However, improper use of timeout schemes can cause serious availability and performance issues, which is often difficult to fix due to lack of diagnostic information. In this paper, we present TFix, an automatic timeout bug fixing system for correcting misused timeout bugs in production systems. TFix adopts a drill-down bug analysis protocol that can narrow down the root cause of a misused timeout bug and producing recommendations for correcting the root cause. TFix first employs a system call frequent episode mining scheme to check whether a timeout bug is caused by a misused timeout variable. TFix then employs application tracing to identify timeout affected functions. Next, TFix uses taint analysis to localize the misused timeout variable. Last, TFix produces recommendations for proper timeout variable values based on the tracing results during normal runs. We have implemented a prototype of TFix and conducted extensive experiments using 13 real world server timeout bugs. Our experimental results show that TFix can correctly localize the misused timeout variables and suggest proper timeout values for fixing those bugs.}, journal={2019 39TH IEEE INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS (ICDCS 2019)}, author={He, Jingzhu and Dai, Ting and Gu, Xiaohui}, year={2019}, pages={612–623} }
 @article{dai_he_gu_lu_wang_2018, title={DScope: Detecting Real-World Data Corruption Hang Bugs in Cloud Server Systems}, DOI={10.1145/3267809.3267844}, abstractNote={Cloud server systems such as Hadoop and Cassandra have enabled many real-world data-intensive applications running inside computing clouds. However, those systems present many data-corruption and performance problems which are notoriously difficult to debug due to the lack of diagnosis information. In this paper, we present DScope, a tool that statically detects data-corruption related software hang bugs in cloud server systems. DScope statically analyzes I/O operations and loops in a software package, and identifies loops whose exit conditions can be affected by I/O operations through returned data, returned error code, or I/O exception handling. After identifying those loops which are prone to hang problems under data corruption, DScope conducts loop bound and loop stride analysis to prune out false positives. We have implemented DScope and evaluated it using 9 common cloud server systems. Our results show that DScope can detect 42 real software hang bugs including 29 newly discovered software hang bugs. In contrast, existing bug detection tools miss detecting most of those bugs.}, journal={PROCEEDINGS OF THE 2018 ACM SYMPOSIUM ON CLOUD COMPUTING (SOCC '18)}, author={Dai, Ting and He, Jingzhu and Gu, Xiaohui and Lu, Shan and Wang, Peipei}, year={2018}, pages={313–325} }
 @article{he_dai_gu_2018, title={TScope: Automatic Timeout Bug Identification for Server Systems}, ISSN={["2474-0756"]}, DOI={10.1109/ICAC.2018.00010}, abstractNote={Timeout is commonly used to handle unexpected failures in server systems. However, improper use of timeout can cause server systems to hang or experience performance degradation. In this paper, we present TScope, an automatic timeout bug identification tool for server systems. TScope leverages kernel-level system call tracing and machine learning based anomaly detection and feature extraction schemes to achieve timeout bug identification. TScope introduces a unique system call selection scheme to achieve higher accuracy than existing generic performance bug detection tools. We have implemented a prototype of TScope and conducted extensive experiments using 19 real-world server performance bugs, including 12 timeout bugs and 7 non-timeout performance bugs. The experimental results show that TScope correctly classifies 18 out of 19 bugs. Compared to existing runtime bug detection schemes, TScope reduces the average false positive rate from 47.24% to 0.8%. TScope is light-weight and does not require application instrumentation, which makes it practical for production server performance bug identification.}, journal={15TH IEEE INTERNATIONAL CONFERENCE ON AUTONOMIC COMPUTING (ICAC 2018)}, author={He, Jingzhu and Dai, Ting and Gu, Xiaohui}, year={2018}, pages={1–10} }
 @article{dai_dean_wang_gu_lu_2017, title={Hytrace: A Hybrid Approach to Performance Bug Diagnosis in Production Cloud Infrastructures}, DOI={10.1145/3127479.3132562}, abstractNote={Server applications running inside production cloud infrastructures are prone to various performance problems (e.g., software hang, performance slow down). When those problems occur, developers often have little clue to diagnose those problems. We present HyTrace, a novel hybrid approach to diagnosing performance problems in production cloud infrastructures. HyTrace combines rule-based static analysis and runtime inference techniques to achieve higher bug localization accuracy than pure-static and pure-dynamic approaches for performance bugs. HyTrace does not require source code and can be applied to both compiled and interpreted programs such as C/C++ and Java. We conduct experiments using real performance bugs from seven commonly used server applications. The results show that our approach can significantly improve the performance bug diagnosis accuracy compared to existing diagnosis techniques.}, journal={PROCEEDINGS OF THE 2017 SYMPOSIUM ON CLOUD COMPUTING (SOCC '17)}, author={Dai, Ting and Dean, Daniel and Wang, Peipei and Gu, Xiaohui and Lu, Shan}, year={2017}, pages={641–641} }
 @article{huang_gong_chen_xiong_pan_dai_2016, title={An Improved mu TESLA Protocol Based on Queuing Theory and Benaloh-Leichter SSS in WSNs}, volume={2016}, ISSN={["1687-7268"]}, DOI={10.1155/2016/9021650}, abstractNote={Broadcast authentication is a fundamental security technology in wireless sensor networks (ab. WSNs). As an authentication protocol, the most widely used in WSN, μ TESLA protocol, its publication of key is based on a fixed time interval, which may lead to unsatisfactory performance under the unstable network traffic environment. Furthermore, the frequent network communication will cause the delay authentication for some broadcast packets while the infrequent one will increase the overhead of key computation. To solve these problems, this paper improves the traditional μ TESLA by determining the publication of broadcast key based on the network data flow rather than the fixed time interval. Meanwhile, aiming at the finite length of hash chain and the problem of exhaustion, a self-renewal hash chain based on Benaloh-Leichter secret sharing scheme (SRHC-BL SSS) is designed, which can prolong the lifetime of network. Moreover, by introducing the queue theory model, we demonstrate that our scheme has much lower key consumption than μ TESLA through simulation evaluations. Finally, we analyze and prove the security and efficiency of the proposed self-renewal hash chain, comparing with other typical schemes.}, journal={JOURNAL OF SENSORS}, author={Huang, Haiping and Gong, Tianhe and Chen, Tao and Xiong, Mingliang and Pan, Xinxing and Dai, Ting}, year={2016} }