{"title":"Session details: Session 2D: Mobile Security","authors":"Xusheng Xiao","doi":"10.1145/3432965","DOIUrl":"https://doi.org/10.1145/3432965","url":null,"abstract":"","PeriodicalId":20481,"journal":{"name":"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security","volume":"98 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80128649","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}
Differential privacy is a rigorous mathematical model of privacy protection that has been the subject of deep theoretical research and also been deployed in real-world systems. This workshop aims to bring together a diverse array of researchers and practitioners to provoke stimulating discussion about the current state of differential privacy, in theory and practice. TPDP aims to be an inclusive forum that seeks to grow and diversify the differential privacy community.
{"title":"TPDP'20: 6th Workshop on Theory and Practice of Differential Privacy","authors":"Rachel Cummings, Michael Hay","doi":"10.1145/3372297.3416253","DOIUrl":"https://doi.org/10.1145/3372297.3416253","url":null,"abstract":"Differential privacy is a rigorous mathematical model of privacy protection that has been the subject of deep theoretical research and also been deployed in real-world systems. This workshop aims to bring together a diverse array of researchers and practitioners to provoke stimulating discussion about the current state of differential privacy, in theory and practice. TPDP aims to be an inclusive forum that seeks to grow and diversify the differential privacy community.","PeriodicalId":20481,"journal":{"name":"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82161331","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}
Phishing websites are still a major threat in today's Internet ecosystem. Despite numerous previous efforts, similarity-based detection methods do not offer sufficient protection for the trusted websites, in particular against unseen phishing pages. This paper contributes VisualPhishNet, a new similarity-based phishing detection framework, based on a triplet Convolutional Neural Network (CNN). VisualPhishNet learns profiles for websites in order to detect phishing websites by a similarity metric that can generalize to pages with new visual appearances. We furthermore present VisualPhish, the largest dataset to date that facilitates visual phishing detection in an ecologically valid manner. We show that our method outperforms previous visual similarity phishing detection approaches by a large margin while being robust against a range of evasion attacks.
{"title":"VisualPhishNet: Zero-Day Phishing Website Detection by Visual Similarity","authors":"Sahar Abdelnabi, Katharina Krombholz, Mario Fritz","doi":"10.1145/3372297.3417233","DOIUrl":"https://doi.org/10.1145/3372297.3417233","url":null,"abstract":"Phishing websites are still a major threat in today's Internet ecosystem. Despite numerous previous efforts, similarity-based detection methods do not offer sufficient protection for the trusted websites, in particular against unseen phishing pages. This paper contributes VisualPhishNet, a new similarity-based phishing detection framework, based on a triplet Convolutional Neural Network (CNN). VisualPhishNet learns profiles for websites in order to detect phishing websites by a similarity metric that can generalize to pages with new visual appearances. We furthermore present VisualPhish, the largest dataset to date that facilitates visual phishing detection in an ecologically valid manner. We show that our method outperforms previous visual similarity phishing detection approaches by a large margin while being robust against a range of evasion attacks.","PeriodicalId":20481,"journal":{"name":"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security","volume":"74 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":"87801732","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}
Software patching is one of the most significant mechanisms to combat vulnerabilities. To demystify underlying patch details, the techniques of patch differential analysis (a.k.a. patch diffing) are proposed to find differences between patched and unpatched programs' binary code. Considering the sophisticated security patches, patch diffing is expected to not only correctly locate patch changes but also provide sufficient explanation for understanding patch details and the fixed vulnerabilities. Unfortunately, none of the existing patch diffing techniques can meet these requirements. In this study, we first perform a large-scale study on code changes of security patches for better understanding their patterns. We then point out several challenges and design principles for patch diffing. To address the above challenges, we design a dynamic patch diffing technique PatchScope. Our technique is motivated by two key observations: 1) the way that a program processes its input reveals a wealth of semantic information, and 2) most memory corruption patches regulate the handling of malformed inputs via updating the manipulations of input-related data structures. The core of PatchScope is a new semantics-aware program representation, memory object access sequence, which characterizes how a program references data structures to manipulate inputs. The representation can not only deliver succinct patch differences but also offer rich patch context information such as input-patch correlations. Such information can interpret patch differences and further help security analysts understand patch details, locate vulnerability root causes, and even detect buggy patches.
{"title":"PatchScope: Memory Object Centric Patch Diffing","authors":"Lei Zhao, Yuncong Zhu, Jiang Ming, Yichen Zhang, Haotian Zhang, Heng Yin","doi":"10.1145/3372297.3423342","DOIUrl":"https://doi.org/10.1145/3372297.3423342","url":null,"abstract":"Software patching is one of the most significant mechanisms to combat vulnerabilities. To demystify underlying patch details, the techniques of patch differential analysis (a.k.a. patch diffing) are proposed to find differences between patched and unpatched programs' binary code. Considering the sophisticated security patches, patch diffing is expected to not only correctly locate patch changes but also provide sufficient explanation for understanding patch details and the fixed vulnerabilities. Unfortunately, none of the existing patch diffing techniques can meet these requirements. In this study, we first perform a large-scale study on code changes of security patches for better understanding their patterns. We then point out several challenges and design principles for patch diffing. To address the above challenges, we design a dynamic patch diffing technique PatchScope. Our technique is motivated by two key observations: 1) the way that a program processes its input reveals a wealth of semantic information, and 2) most memory corruption patches regulate the handling of malformed inputs via updating the manipulations of input-related data structures. The core of PatchScope is a new semantics-aware program representation, memory object access sequence, which characterizes how a program references data structures to manipulate inputs. The representation can not only deliver succinct patch differences but also offer rich patch context information such as input-patch correlations. Such information can interpret patch differences and further help security analysts understand patch details, locate vulnerability root causes, and even detect buggy patches.","PeriodicalId":20481,"journal":{"name":"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86437085","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}
B. Abdolmaleki, Sebastian Ramacher, Daniel Slamanig
Zero-knowledge proofs and in particular succinct non-interactive zero-knowledge proofs (so called zk-SNARKs) are getting increasingly used in real-world applications, with cryptocurrencies being the prime example. Simulation extractability (SE) is a strong security notion for zk-SNARKs which informally ensures non-malleability of proofs. The high importance of this property is acknowledged by leading companies in this field such as Zcash and underpinned by various attacks against the malleability of cryptographic primitives in the past. Another problematic issue for the practical use of zk-SNARKs is the requirement of a fully trusted setup, as especially for large-scale decentralized applications finding a trusted party that runs the setup is practically impossible. Quite recently, the study of approaches to relax or even remove the trust in the setup procedure, and in particular subversion as well as updatable zk-SNARKs (with latter being the most promising approach), has been initiated and received considerable attention since then. Unfortunately, so far SE-SNARKs with the aforementioned properties are only constructed in an ad-hoc manner and no generic techniques are available. In this paper, we are interested in such generic techniques and therefore firstly revisit the only available lifting technique due to Kosba et al. (called COCO) to generically obtain SE-SNARKs. By exploring the design space of many recently proposed SNARK- and STARK-friendly symmetric-key primitives we thereby achieve significant improvements in the prover computation and proof size. Unfortunately, the COCO framework as well as our improved version (called OCOCO) is not compatible with updatable SNARKs. Consequently, we propose a novel generic lifting transformation called LAMASSU. It is built using different underlying ideas compared to COCO (and OCOCO). In contrast to COCO it only requires key-homomorphic signatures (which allow to shift keys) covering well studied schemes such as Schnorr or ECDSA. This makes LAMASSU highly interesting, as by using the novel concept of so called updatable signatures, which we introduce in this paper, we can prove that LAMASSU preserves the subversion and in particular updatable properties of the underlying zk-SNARK. This makes LAMASSU the first technique to also generically obtain SE subversion and updatable SNARKs. As its performance compares favorably to OCOCO, LAMASSU is an attractive alternative that in contrast to COCO is only based on well established cryptographic assumptions.
{"title":"Lift-and-Shift: Obtaining Simulation Extractable Subversion and Updatable SNARKs Generically","authors":"B. Abdolmaleki, Sebastian Ramacher, Daniel Slamanig","doi":"10.1145/3372297.3417228","DOIUrl":"https://doi.org/10.1145/3372297.3417228","url":null,"abstract":"Zero-knowledge proofs and in particular succinct non-interactive zero-knowledge proofs (so called zk-SNARKs) are getting increasingly used in real-world applications, with cryptocurrencies being the prime example. Simulation extractability (SE) is a strong security notion for zk-SNARKs which informally ensures non-malleability of proofs. The high importance of this property is acknowledged by leading companies in this field such as Zcash and underpinned by various attacks against the malleability of cryptographic primitives in the past. Another problematic issue for the practical use of zk-SNARKs is the requirement of a fully trusted setup, as especially for large-scale decentralized applications finding a trusted party that runs the setup is practically impossible. Quite recently, the study of approaches to relax or even remove the trust in the setup procedure, and in particular subversion as well as updatable zk-SNARKs (with latter being the most promising approach), has been initiated and received considerable attention since then. Unfortunately, so far SE-SNARKs with the aforementioned properties are only constructed in an ad-hoc manner and no generic techniques are available. In this paper, we are interested in such generic techniques and therefore firstly revisit the only available lifting technique due to Kosba et al. (called COCO) to generically obtain SE-SNARKs. By exploring the design space of many recently proposed SNARK- and STARK-friendly symmetric-key primitives we thereby achieve significant improvements in the prover computation and proof size. Unfortunately, the COCO framework as well as our improved version (called OCOCO) is not compatible with updatable SNARKs. Consequently, we propose a novel generic lifting transformation called LAMASSU. It is built using different underlying ideas compared to COCO (and OCOCO). In contrast to COCO it only requires key-homomorphic signatures (which allow to shift keys) covering well studied schemes such as Schnorr or ECDSA. This makes LAMASSU highly interesting, as by using the novel concept of so called updatable signatures, which we introduce in this paper, we can prove that LAMASSU preserves the subversion and in particular updatable properties of the underlying zk-SNARK. This makes LAMASSU the first technique to also generically obtain SE subversion and updatable SNARKs. As its performance compares favorably to OCOCO, LAMASSU is an attractive alternative that in contrast to COCO is only based on well established cryptographic assumptions.","PeriodicalId":20481,"journal":{"name":"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security","volume":"53 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86238971","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 5D: Secure Computation","authors":"Dov S. Gordon","doi":"10.1145/3432980","DOIUrl":"https://doi.org/10.1145/3432980","url":null,"abstract":"","PeriodicalId":20481,"journal":{"name":"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82645417","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 3B: Malware","authors":"L. Cavallaro","doi":"10.1145/3432968","DOIUrl":"https://doi.org/10.1145/3432968","url":null,"abstract":"","PeriodicalId":20481,"journal":{"name":"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security","volume":"2016 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82820821","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}
Insider threat is a well-recognized problem in the cyber-security domain. There is good amount of research on detecting and predicting an insider attack. However, none of them addresses the influence of an insider over other individuals, and the spread of impact due to direct and indirect access to enterprise assets by having such influence. In this work, we propose a graph-based influence profiling solution called rProfiler that analyzes the data from multiple sources to determine the influence spread and calculate the probability of loss of data from an affected device using pertinent graph features. We also highlight multiple enterprise scenarios that may benefit from this work.
{"title":"rProfiler -- Assessing Insider Influence on Enterprise Assets","authors":"Manish Shukla, S. Lodha","doi":"10.1145/3372297.3420026","DOIUrl":"https://doi.org/10.1145/3372297.3420026","url":null,"abstract":"Insider threat is a well-recognized problem in the cyber-security domain. There is good amount of research on detecting and predicting an insider attack. However, none of them addresses the influence of an insider over other individuals, and the spread of impact due to direct and indirect access to enterprise assets by having such influence. In this work, we propose a graph-based influence profiling solution called rProfiler that analyzes the data from multiple sources to determine the influence spread and calculate the probability of loss of data from an affected device using pertinent graph features. We also highlight multiple enterprise scenarios that may benefit from this work.","PeriodicalId":20481,"journal":{"name":"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89096667","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}
HoneyBadgerBFT, proposed by Miller et al. [34] as the first practical asynchronous atomic broadcast protocol, demonstrated impressive performance. The core of HoneyBadgerBFT (HB-BFT) is to achieve batching consensus using asynchronous common subset protocol (ACS) of Ben-Or et al., constituted with n reliable broadcast protocol (RBC) to have each node propose its input, followed by n asynchronous binary agreement protocol (ABA) to make a decision for each proposed value (n is the total number of nodes). In this paper, we propose two new atomic broadcast protocols (called Dumbo1, Dumbo2) both of which have asymptotically and practically better efficiency. In particular, the ACS of Dumbo1 only runs a small κ (independent of n) instances of ABA, while that of Dumbo2 further reduces it to constant! At the core of our techniques are two major observations: (1) reducing the number of ABA instances significantly improves efficiency; and (2) using multi-valued validated Byzantine agreement (MVBA) which was considered sub-optimal for ACS in [34] in a more careful way could actually lead to a much more efficient ACS. We implement both Dumbo1, Dumbo2 and deploy them as well as HB-BFT on 100 Amazon EC2 t2.medium instances uniformly distributed throughout 10 different regions across the globe, and run extensive experiments in the same environments. The experimental results show that our protocols achieve multi-fold improvements over HoneyBadgerBFT on both latency and throughput, especially when the system scale becomes moderately large.
{"title":"Dumbo: Faster Asynchronous BFT Protocols","authors":"Bingyong Guo, Zhenliang Lu, Qiang Tang, Jing Xu, Zhenfeng Zhang","doi":"10.1145/3372297.3417262","DOIUrl":"https://doi.org/10.1145/3372297.3417262","url":null,"abstract":"HoneyBadgerBFT, proposed by Miller et al. [34] as the first practical asynchronous atomic broadcast protocol, demonstrated impressive performance. The core of HoneyBadgerBFT (HB-BFT) is to achieve batching consensus using asynchronous common subset protocol (ACS) of Ben-Or et al., constituted with n reliable broadcast protocol (RBC) to have each node propose its input, followed by n asynchronous binary agreement protocol (ABA) to make a decision for each proposed value (n is the total number of nodes). In this paper, we propose two new atomic broadcast protocols (called Dumbo1, Dumbo2) both of which have asymptotically and practically better efficiency. In particular, the ACS of Dumbo1 only runs a small κ (independent of n) instances of ABA, while that of Dumbo2 further reduces it to constant! At the core of our techniques are two major observations: (1) reducing the number of ABA instances significantly improves efficiency; and (2) using multi-valued validated Byzantine agreement (MVBA) which was considered sub-optimal for ACS in [34] in a more careful way could actually lead to a much more efficient ACS. We implement both Dumbo1, Dumbo2 and deploy them as well as HB-BFT on 100 Amazon EC2 t2.medium instances uniformly distributed throughout 10 different regions across the globe, and run extensive experiments in the same environments. The experimental results show that our protocols achieve multi-fold improvements over HoneyBadgerBFT on both latency and throughput, especially when the system scale becomes moderately large.","PeriodicalId":20481,"journal":{"name":"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security","volume":"41 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91503413","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}
Vadim Lyubashevsky, Ngoc Khanh Nguyen, Gregor Seiler
We present a novel lattice-based zero-knowledge proof system for showing that (arbitrary-sized) committed integers satisfy additive and multiplicative relationships. The proof sizes of our schemes are between two to three orders of magnitude smaller than in the lattice proof system of Libert et al. (CRYPTO 2018) for the same relations. Because the proof sizes of our protocols grow linearly in the integer length, our proofs will eventually be longer than those produced by quantum-safe succinct proof systems for general circuits (e.g. Ligero, Aurora, etc.). But for relations between reasonably-sized integers (e.g. $512$-bit), our proofs still result in the smallest zero-knowledge proof system based on a quantum-safe assumption. Of equal importance, the run-time of our proof system is at least an order of magnitude faster than any other quantum-safe scheme.
{"title":"Practical Lattice-Based Zero-Knowledge Proofs for Integer Relations","authors":"Vadim Lyubashevsky, Ngoc Khanh Nguyen, Gregor Seiler","doi":"10.1145/3372297.3417894","DOIUrl":"https://doi.org/10.1145/3372297.3417894","url":null,"abstract":"We present a novel lattice-based zero-knowledge proof system for showing that (arbitrary-sized) committed integers satisfy additive and multiplicative relationships. The proof sizes of our schemes are between two to three orders of magnitude smaller than in the lattice proof system of Libert et al. (CRYPTO 2018) for the same relations. Because the proof sizes of our protocols grow linearly in the integer length, our proofs will eventually be longer than those produced by quantum-safe succinct proof systems for general circuits (e.g. Ligero, Aurora, etc.). But for relations between reasonably-sized integers (e.g. $512$-bit), our proofs still result in the smallest zero-knowledge proof system based on a quantum-safe assumption. Of equal importance, the run-time of our proof system is at least an order of magnitude faster than any other quantum-safe scheme.","PeriodicalId":20481,"journal":{"name":"Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security","volume":"01 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91406801","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}
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