Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security最新文献

{"title":"Tight Consistency Bounds for Bitcoin","authors":"Peter Gazi, A. Kiayias, A. Russell","doi":"10.1145/3372297.3423365","DOIUrl":"https://doi.org/10.1145/3372297.3423365","url":null,"abstract":"We establish the optimal security threshold for the Bitcoin protocol in terms of adversarial hashing power, honest hashing power, and network delays. Specifically, we prove that the protocol is secure if [ra < 1/Δ0 + 1/rh,,] where rh is the expected number of honest proof-of-work successes in unit time, ra is the expected number of adversarial successes, and no message is delayed by more than Δ0 time units. In this regime, the protocol guarantees consistency and liveness with exponentially decaying failure probabilities. Outside this region, the simple private chain attack prevents consensus. Our analysis immediately applies to any Nakamoto-style proof-of-work protocol; in the full version of this paper we also present the adaptations needed to apply it in the proof-of-stake setting, establishing a similar threshold there.","PeriodicalId":20481,"journal":{"name":"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security","volume":"93 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84721838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"You've Changed: Detecting Malicious Browser Extensions through their Update Deltas","authors":"Nikolaos Pantelaios, Nick Nikiforakis, A. Kapravelos","doi":"10.1145/3372297.3423343","DOIUrl":"https://doi.org/10.1145/3372297.3423343","url":null,"abstract":"In this paper, we conduct the largest to-date analysis of browser extensions, by investigating 922,684 different extension versions collected in the past six years, and using this data to discover malicious versions of extensions. We propose a two-stage system that first identifies malicious extensions based on anomalous extension ratings and locates the code that was added to a benign extension in order to make it malicious. We encode these code deltas according to the APIs that they abuse and search our historical dataset for other similar deltas of extensions which have not yet been flagged, neither by users nor by Chrome's Web Store. We were able to discover 143 malicious extensions belonging to 21 malicious clusters, exhibiting a wide range of abuse, from history stealing and ad injection, to the hijacking of new tabs and search engines. Our results show that our proposed techniques operate in an abuse-agnostic way and can identify malicious extensions that are evading detection.","PeriodicalId":20481,"journal":{"name":"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security","volume":"105 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80801439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Talking with Familiar Strangers: An Empirical Study on HTTPS Context Confusion Attacks","authors":"Mingming Zhang, Xiaofeng Zheng, Kaiwen Shen, Ziqiao Kong, Chaoyi Lu, Yu Wang, Haixin Duan, S. Hao, Baojun Liu, Min Yang","doi":"10.1145/3372297.3417252","DOIUrl":"https://doi.org/10.1145/3372297.3417252","url":null,"abstract":"HTTPS is principally designed for secure end-to-end communication, which adds confidentiality and integrity to sensitive data transmission. While several man-in-the-middle attacks (e.g., SSL Stripping) are available to break the secured connections, state-of-the-art security policies (e.g., HSTS) have significantly increased the cost of successful attacks. However, the TLS certificates shared by multiple domains make HTTPS hijacking attacks possible again. In this paper, we term the HTTPS MITM attacks based on the shared TLS certificates as HTTPS Context Confusion Attack (SCC Attack). Despite a known threat, it has not yet been studied thoroughly. We aim to fill this gap with an in-depth empirical assessment of SCC Attack. We find the attack can succeed even for servers that have deployed current best practice of security policies. By rerouting encrypted traffic to another flawed server that shares the TLS certificate, attackers can bypass the security practices, hijack the ongoing HTTPS connections, and subsequently launch additional attacks including phishing and payment hijacking. Particularly, vulnerable HTTP headers from a third-party server are exploitable for this attack, and it is possible to hijack an already-established secure connection. Through tests on popular websites, we find vulnerable subdomains under 126 apex domains in Alexa top 500 sites, including large vendors like Alibaba, JD, and Microsoft. Meanwhile, through a large-scale measurement, we find that TLS certificate sharing is prominent, which uncovers the high potential of such attacks, and we summarize the security dependencies among different parties. For responsible disclosure, we have reported the issues to affected vendors and received positive feedback. Our study sheds light on an influential attack surface of the HTTPS ecosystem and calls for proper mitigation against MITM attacks.","PeriodicalId":20481,"journal":{"name":"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83218761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RTFM! Automatic Assumption Discovery and Verification Derivation from Library Document for API Misuse Detection","authors":"Tao Lv, Ruishi Li, Yi Yang, Kai Chen, Xiaojing Liao, Xiaofeng Wang, Peiwei Hu, Luyi Xing","doi":"10.1145/3372297.3423360","DOIUrl":"https://doi.org/10.1145/3372297.3423360","url":null,"abstract":"To use library APIs, a developer is supposed to follow guidance and respect some constraints, which we call integration assumptions (IAs). Violations of these assumptions can have serious consequences, introducing security-critical flaws such as use-after-free, NULL-dereference, and authentication errors. Analyzing a program for compliance with IAs involves significant effort and needs to be automated. A promising direction is to automatically recover IAs from a library document using Natural Language Processing (NLP) and then verify their consistency with the ways APIs are used in a program through code analysis. However, a practical solution along this line needs to overcome several key challenges, particularly the discovery of IAs from loosely formatted documents and interpretation of their informal descriptions to identify complicated constraints (e.g., data-/control-flow relations between different APIs). In this paper, we present a new technique for automated assumption discovery and verification derivation from library documents. Our approach, called Advance, utilizes a suite of innovations to address those challenges. More specifically, we leverage the observation that IAs tend to express a strong sentiment in emphasizing the importance of a constraint, particularly those security-critical, and utilize a new sentiment analysis model to accurately recover them from loosely formatted documents. These IAs are further processed to identify hidden references to APIs and parameters, through an embedding model, to identify the information-flow relations expected to be followed. Then our approach runs frequent subtree mining to discover the grammatical units in IA sentences that tend to indicate some categories of constraints that could have security implications. These components are mapped to verification code snippets organized in line with the IA sentence's grammatical structure, and can be assembled into verification code executed through CodeQL to discover misuses inside a program. We implemented this design and evaluated it on 5 popular libraries (OpenSSL, SQLite, libpcap, libdbus and libxml2) and 39 real-world applications. Our analysis discovered 193 API misuses, including 139 flaws never reported before.","PeriodicalId":20481,"journal":{"name":"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89393933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Session details: Session 6B: Exploitation and Defenses","authors":"Michael Franz","doi":"10.1145/3432983","DOIUrl":"https://doi.org/10.1145/3432983","url":null,"abstract":"","PeriodicalId":20481,"journal":{"name":"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security","volume":"57 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88251138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ligero++: A New Optimized Sublinear IOP","authors":"Rishabh Bhadauria, Zhiyong Fang, Carmit Hazay, Muthuramakrishnan Venkitasubramaniam, Tiancheng Xie, Yupeng Zhang","doi":"10.1145/3372297.3417893","DOIUrl":"https://doi.org/10.1145/3372297.3417893","url":null,"abstract":"This paper follows the line of works that design concretely efficient transparent sublinear zero-knowledge Interactive Oracle Proofs (IOP). Arguments obtained via this paradigm have the advantages of not relying on public-key cryptography, not requiring a trusted setup, and resistance to known quantum attacks. In the realm of transparent systems, Ligero and Aurora stand out with incomparable advantages where the former has a fast prover algorithm somewhat succinct proofs and the latter has somewhat fast prover and succinct proofs. In this work, we introduce Ligero++ that combines the best features of both approaches to achieve the best of both worlds. We implement our protocol and benchmark the results.","PeriodicalId":20481,"journal":{"name":"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78981577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bypassing Tor Exit Blocking with Exit Bridge Onion Services","authors":"Zhao Zhang, Wenchao Zhou, M. Sherr","doi":"10.1145/3372297.3417245","DOIUrl":"https://doi.org/10.1145/3372297.3417245","url":null,"abstract":"Tor exit blocking, in which websites disallow clients arriving from Tor, is a growing and potentially existential threat to the anonymity network. This paper introduces HebTor, a new and robust architecture for exit bridges---short-lived proxies that serve as alternative egress points for Tor. A key insight of HebTor is that exit bridges can operate as Tor onion services, allowing any device that can create outbound TCP connections to serve as an exit bridge, regardless of the presence of NATs and/or firewalls. HebTor employs a micropayment system that compensates exit bridge operators for their services, and a privacy-preserving reputation scheme that prevents freeloading. We show that HebTor effectively thwarts server-side blocking of Tor, and we describe the security, privacy, and legal implications of our design.","PeriodicalId":20481,"journal":{"name":"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security","volume":"140 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80049096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Session details: Session 4D: Distributed Protocols","authors":"Vassilis Zikas","doi":"10.1145/3432975","DOIUrl":"https://doi.org/10.1145/3432975","url":null,"abstract":"","PeriodicalId":20481,"journal":{"name":"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73287426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Phantom of the ADAS: Securing Advanced Driver-Assistance Systems from Split-Second Phantom Attacks","authors":"Ben Nassi, Yisroel Mirsky, Dudi Nassi, Raz Ben-Netanel, Oleg Drokin, Y. Elovici","doi":"10.1145/3372297.3423359","DOIUrl":"https://doi.org/10.1145/3372297.3423359","url":null,"abstract":"In this paper, we investigate \"split-second phantom attacks,\" a scientific gap that causes two commercial advanced driver-assistance systems (ADASs), Telsa Model X (HW 2.5 and HW 3) and Mobileye 630, to treat a depthless object that appears for a few milliseconds as a real obstacle/object. We discuss the challenge that split-second phantom attacks create for ADASs. We demonstrate how attackers can apply split-second phantom attacks remotely by embedding phantom road signs into an advertisement presented on a digital billboard which causes Tesla's autopilot to suddenly stop the car in the middle of a road and Mobileye 630 to issue false notifications. We also demonstrate how attackers can use a projector in order to cause Tesla's autopilot to apply the brakes in response to a phantom of a pedestrian that was projected on the road and Mobileye 630 to issue false notifications in response to a projected road sign. To counter this threat, we propose a countermeasure which can determine whether a detected object is a phantom or real using just the camera sensor. The countermeasure (GhostBusters) uses a \"committee of experts\" approach and combines the results obtained from four lightweight deep convolutional neural networks that assess the authenticity of an object based on the object's light, context, surface, and depth. We demonstrate our countermeasure's effectiveness (it obtains a TPR of 0.994 with an FPR of zero) and test its robustness to adversarial machine learning attacks.","PeriodicalId":20481,"journal":{"name":"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security","volume":"77 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74151532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Secure Single-Server Aggregation with (Poly)Logarithmic Overhead","authors":"James Bell, Kallista A. Bonawitz, Adrià Gascón, Tancrède Lepoint, Mariana Raykova","doi":"10.1145/3372297.3417885","DOIUrl":"https://doi.org/10.1145/3372297.3417885","url":null,"abstract":"Secure aggregation is a cryptographic primitive that enables a server to learn the sum of the vector inputs of many clients. Bonawitz et al. (CCS 2017) presented a construction that incurs computation and communication for each client linear in the number of parties. While this functionality enables a broad range of privacy preserving computational tasks, scaling concerns limit its scope of use. We present the first constructions for secure aggregation that achieve polylogarithmic communication and computation per client. Our constructions provide security in the semi-honest and the semi-malicious settings where the adversary controls the server and a δ-fraction of the clients, and correctness with up to δ-fraction dropouts among the clients. Our constructions show how to replace the complete communication graph of Bonawitz et al., which entails the linear overheads, with a k-regular graph of logarithmic degree while maintaining the security guarantees. Beyond improving the known asymptotics for secure aggregation, our constructions also achieve very efficient concrete parameters. The semi-honest secure aggregation can handle a billion clients at the per-client cost of the protocol of Bonawitz et al. for a thousand clients. In the semi-malicious setting with 10 4 clients, each client needs to communicate only with 3% of the clients to have a guarantee that its input has been added together with the inputs of at least 5000 other clients, while withstanding up to 5% corrupt clients and 5% dropouts. We also show an application of secure aggregation to the task of secure shuffling which enables the first cryptographically secure instantiation of the shuffle model of differential privacy.","PeriodicalId":20481,"journal":{"name":"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security","volume":"311 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77387974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}