Pub Date : 2018-01-01DOI: 10.14722/NDSS.2018.23166
Marius Muench, Jan Stijohann, F. Kargl, Aurélien Francillon, D. Balzarotti
—As networked embedded systems are becoming more ubiquitous, their security is becoming critical to our daily life. While manual or automated large scale analysis of those systems regularly uncover new vulnerabilities, the way those systems are analyzed follows often the same approaches used on desktop systems. More specifically, traditional testing approaches relies on observable crashes of a program, and binary instrumentation techniques are used to improve the detection of those faulty states. In this paper, we demonstrate that memory corruptions, a common class of security vulnerabilities, often result in different behavior on embedded devices than on desktop systems. In particular, on embedded devices, effects of memory corruption are often less visible. This reduces significantly the effectiveness of traditional dynamic testing techniques in general, and fuzzing in particular. Additionally, we analyze those differences in several categories of embedded devices and show the resulting impact on firmware analysis. We further describe and evaluate relatively simple heuristics which can be applied at run time (on an execution trace or in an emulator), during the analysis of an embedded device to detect previously undetected memory corruptions.
{"title":"What You Corrupt Is Not What You Crash: Challenges in Fuzzing Embedded Devices","authors":"Marius Muench, Jan Stijohann, F. Kargl, Aurélien Francillon, D. Balzarotti","doi":"10.14722/NDSS.2018.23166","DOIUrl":"https://doi.org/10.14722/NDSS.2018.23166","url":null,"abstract":"—As networked embedded systems are becoming more ubiquitous, their security is becoming critical to our daily life. While manual or automated large scale analysis of those systems regularly uncover new vulnerabilities, the way those systems are analyzed follows often the same approaches used on desktop systems. More specifically, traditional testing approaches relies on observable crashes of a program, and binary instrumentation techniques are used to improve the detection of those faulty states. In this paper, we demonstrate that memory corruptions, a common class of security vulnerabilities, often result in different behavior on embedded devices than on desktop systems. In particular, on embedded devices, effects of memory corruption are often less visible. This reduces significantly the effectiveness of traditional dynamic testing techniques in general, and fuzzing in particular. Additionally, we analyze those differences in several categories of embedded devices and show the resulting impact on firmware analysis. We further describe and evaluate relatively simple heuristics which can be applied at run time (on an execution trace or in an emulator), during the analysis of an embedded device to detect previously undetected memory corruptions.","PeriodicalId":20444,"journal":{"name":"Proceedings 2019 Network and Distributed System Security Symposium","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91397070","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}
Pub Date : 2017-02-01DOI: 10.14722/NDSS.2017.23465
Andrea Continella, Y. Fratantonio, Martina Lindorfer, Alessandro Puccetti, Ali Zand, Christopher Krügel, G. Vigna
Mobile apps are notorious for collecting a wealth of private information from users. Despite significant effort from the research community in developing privacy leak detection tools based on data flow tracking inside the app or through network traffic analysis, it is still unclear whether apps and ad libraries can hide the fact that they are leaking private information. In fact, all existing analysis tools have limitations: data flow tracking suffers from imprecisions that cause false positives, as well as false negatives when the data flow from a source of private information to a network sink is interrupted; on the other hand, network traffic analysis cannot handle encryption or custom encoding. We propose a new approach to privacy leak detection that is not affected by such limitations, and it is also resilient to obfuscation techniques, such as encoding, formatting, encryption, or any other kind of transformation performed on private information before it is leaked. Our work is based on blackbox differential analysis, and it works in two steps: first, it establishes a baseline of the network behavior of an app; then, it modifies sources of private information, such as the device ID and location, and detects leaks by observing deviations in the resulting network traffic. The basic concept of black-box differential analysis is not novel, but, unfortunately, it is not practical enough to precisely analyze modern mobile apps. In fact, their network traffic contains many sources of non-determinism, such as random identifiers, timestamps, and server-assigned session identifiers, which, when not handled properly, cause too much noise to correlate output changes with input changes. The main contribution of this work is to make black-box differential analysis practical when applied to modern Android apps. In particular, we show that the network-based non-determinism can often be explained and eliminated, and it is thus possible to reliably use variations in the network traffic as a strong signal to detect privacy leaks. We implemented this approach in a tool, called AGRIGENTO, and we evaluated it on more than one thousand Android apps. Our evaluation shows that our approach works well in practice and outperforms current state-of-the-art techniques. We conclude our study by discussing several case studies that show how popular apps and ad libraries currently exfiltrate data by using complex combinations of encoding and encryption mechanisms that other approaches fail to detect. Our results show that these apps and libraries seem to deliberately hide their data leaks from current approaches and clearly demonstrate the need for an obfuscation-resilient approach such as ours.
{"title":"Obfuscation-Resilient Privacy Leak Detection for Mobile Apps Through Differential Analysis","authors":"Andrea Continella, Y. Fratantonio, Martina Lindorfer, Alessandro Puccetti, Ali Zand, Christopher Krügel, G. Vigna","doi":"10.14722/NDSS.2017.23465","DOIUrl":"https://doi.org/10.14722/NDSS.2017.23465","url":null,"abstract":"Mobile apps are notorious for collecting a wealth of private information from users. Despite significant effort from the research community in developing privacy leak detection tools based on data flow tracking inside the app or through network traffic analysis, it is still unclear whether apps and ad libraries can hide the fact that they are leaking private information. In fact, all existing analysis tools have limitations: data flow tracking suffers from imprecisions that cause false positives, as well as false negatives when the data flow from a source of private information to a network sink is interrupted; on the other hand, network traffic analysis cannot handle encryption or custom encoding. We propose a new approach to privacy leak detection that is not affected by such limitations, and it is also resilient to obfuscation techniques, such as encoding, formatting, encryption, or any other kind of transformation performed on private information before it is leaked. Our work is based on blackbox differential analysis, and it works in two steps: first, it establishes a baseline of the network behavior of an app; then, it modifies sources of private information, such as the device ID and location, and detects leaks by observing deviations in the resulting network traffic. The basic concept of black-box differential analysis is not novel, but, unfortunately, it is not practical enough to precisely analyze modern mobile apps. In fact, their network traffic contains many sources of non-determinism, such as random identifiers, timestamps, and server-assigned session identifiers, which, when not handled properly, cause too much noise to correlate output changes with input changes. The main contribution of this work is to make black-box differential analysis practical when applied to modern Android apps. In particular, we show that the network-based non-determinism can often be explained and eliminated, and it is thus possible to reliably use variations in the network traffic as a strong signal to detect privacy leaks. We implemented this approach in a tool, called AGRIGENTO, and we evaluated it on more than one thousand Android apps. Our evaluation shows that our approach works well in practice and outperforms current state-of-the-art techniques. We conclude our study by discussing several case studies that show how popular apps and ad libraries currently exfiltrate data by using complex combinations of encoding and encryption mechanisms that other approaches fail to detect. Our results show that these apps and libraries seem to deliberately hide their data leaks from current approaches and clearly demonstrate the need for an obfuscation-resilient approach such as ours.","PeriodicalId":20444,"journal":{"name":"Proceedings 2019 Network and Distributed System Security Symposium","volume":"48 1","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91385584","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}
Pub Date : 2017-01-01DOI: 10.14722/NDSS.2017.23149
Claude Fachkha, E. Bou-Harb, A. Keliris, N. Memon, M. Ahamad
Although the security of Cyber-Physical Systems (CPS) has been recently receiving significant attention from the research community, undoubtedly, there still exists a substantial lack of a comprehensive and a holistic understanding of attackers’ malicious strategies, aims and intentions. To this end, this paper uniquely exploits passive monitoring and analysis of a newly deployed network telescope IP address space in a first attempt ever to build broad notions of real CPS maliciousness. Specifically, we approach this problem by inferring, investigating, characterizing and reporting large-scale probing activities that specifically target more than 20 diverse, heavily employed CPS protocols. To permit such analysis, we initially devise and evaluate a novel probabilistic model that aims at filtering noise that is embedded in network telescope traffic. Subsequently, we generate amalgamated statistics, inferences and insights characterizing such inferred scanning activities in terms of their probe types, the distribution of their sources and their packets’ headers, among numerous others, in addition to examining and visualizing the co-occurrence patterns of such events. Further, we propose and empirically evaluate an innovative hybrid approach rooted in time-series analysis and context triggered piecewise hashing to infer, characterize and cluster orchestrated and well-coordinated probing activities targeting CPS protocols, which are generated from Internet-scale unsolicited sources. Our analysis and evaluations, which draw upon extensive network telescope data observed over a recent one month period, demonstrate a staggering 33 thousand probes towards ample of CPS protocols, the lack of interest in UDP-based CPS services, and the prevalence of probes towards the ICCP and Modbus protocols. Additionally, we infer a considerable 74% of CPS probes that were persistent throughout the entire analyzed period targeting prominent protocols such as DNP3 and BACnet. Further, we uncover close to 9 thousand large-scale, stealthy, previously undocumented orchestrated probing events targeting a number of such CPS protocols. We validate the various outcomes through cross-validations against publicly available threat repositories. We concur that the devised approaches, techniques, and methods provide a solid first step towards better comprehending real CPS unsolicited objectives and intents.
{"title":"Internet-scale Probing of CPS: Inference, Characterization and Orchestration Analysis","authors":"Claude Fachkha, E. Bou-Harb, A. Keliris, N. Memon, M. Ahamad","doi":"10.14722/NDSS.2017.23149","DOIUrl":"https://doi.org/10.14722/NDSS.2017.23149","url":null,"abstract":"Although the security of Cyber-Physical Systems (CPS) has been recently receiving significant attention from the research community, undoubtedly, there still exists a substantial lack of a comprehensive and a holistic understanding of attackers’ malicious strategies, aims and intentions. To this end, this paper uniquely exploits passive monitoring and analysis of a newly deployed network telescope IP address space in a first attempt ever to build broad notions of real CPS maliciousness. Specifically, we approach this problem by inferring, investigating, characterizing and reporting large-scale probing activities that specifically target more than 20 diverse, heavily employed CPS protocols. To permit such analysis, we initially devise and evaluate a novel probabilistic model that aims at filtering noise that is embedded in network telescope traffic. Subsequently, we generate amalgamated statistics, inferences and insights characterizing such inferred scanning activities in terms of their probe types, the distribution of their sources and their packets’ headers, among numerous others, in addition to examining and visualizing the co-occurrence patterns of such events. Further, we propose and empirically evaluate an innovative hybrid approach rooted in time-series analysis and context triggered piecewise hashing to infer, characterize and cluster orchestrated and well-coordinated probing activities targeting CPS protocols, which are generated from Internet-scale unsolicited sources. Our analysis and evaluations, which draw upon extensive network telescope data observed over a recent one month period, demonstrate a staggering 33 thousand probes towards ample of CPS protocols, the lack of interest in UDP-based CPS services, and the prevalence of probes towards the ICCP and Modbus protocols. Additionally, we infer a considerable 74% of CPS probes that were persistent throughout the entire analyzed period targeting prominent protocols such as DNP3 and BACnet. Further, we uncover close to 9 thousand large-scale, stealthy, previously undocumented orchestrated probing events targeting a number of such CPS protocols. We validate the various outcomes through cross-validations against publicly available threat repositories. We concur that the devised approaches, techniques, and methods provide a solid first step towards better comprehending real CPS unsolicited objectives and intents.","PeriodicalId":20444,"journal":{"name":"Proceedings 2019 Network and Distributed System Security Symposium","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91397921","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}
Pub Date : 2014-01-01DOI: 10.14722/NDSS.2014.23125
Le Guan, Jingqiang Lin, Bo Luo, Jiwu Jing
Cryptographic systems are essential for computer and communication security, for instance, RSA is used in PGP Email clients and AES is employed in full disk encryption. In practice, the cryptographic keys are loaded and stored in RAM as plain-text, and therefore vulnerable to physical memory attacks (e.g., cold-boot attacks). To tackle this problem, we propose Copker, which implements asymmetric cryptosystems entirely within the CPU, without storing plain-text private keys in the RAM. In its active mode, Copker stores kilobytes of sensitive data, including the private key and the intermediate states, only in onchip CPU caches (and registers). Decryption/signing operations are performed without storing sensitive information in system memory. In the suspend mode, Copker stores symmetrically encrypted private keys in memory, while employs existing solutions to keep the key-encryption key securely in CPU registers. Hence, Copker releases the system resources in the suspend mode. In this paper, we implement Copker with the most common asymmetric cryptosystem, RSA, with the support of multiple private keys. We show that Copker provides decryption/signing services that are secure against physical memory attacks. Meanwhile, with intensive experiments, we demonstrate that our implementation of Copker is secure and requires reasonable overhead. Keywords—Cache-as-RAM; cold-boot attack; key management; asymmetric cryptography implementation.
{"title":"Copker: Computing with Private Keys without RAM","authors":"Le Guan, Jingqiang Lin, Bo Luo, Jiwu Jing","doi":"10.14722/NDSS.2014.23125","DOIUrl":"https://doi.org/10.14722/NDSS.2014.23125","url":null,"abstract":"Cryptographic systems are essential for computer and communication security, for instance, RSA is used in PGP Email clients and AES is employed in full disk encryption. In practice, the cryptographic keys are loaded and stored in RAM as plain-text, and therefore vulnerable to physical memory attacks (e.g., cold-boot attacks). To tackle this problem, we propose Copker, which implements asymmetric cryptosystems entirely within the CPU, without storing plain-text private keys in the RAM. In its active mode, Copker stores kilobytes of sensitive data, including the private key and the intermediate states, only in onchip CPU caches (and registers). Decryption/signing operations are performed without storing sensitive information in system memory. In the suspend mode, Copker stores symmetrically encrypted private keys in memory, while employs existing solutions to keep the key-encryption key securely in CPU registers. Hence, Copker releases the system resources in the suspend mode. In this paper, we implement Copker with the most common asymmetric cryptosystem, RSA, with the support of multiple private keys. We show that Copker provides decryption/signing services that are secure against physical memory attacks. Meanwhile, with intensive experiments, we demonstrate that our implementation of Copker is secure and requires reasonable overhead. Keywords—Cache-as-RAM; cold-boot attack; key management; asymmetric cryptography implementation.","PeriodicalId":20444,"journal":{"name":"Proceedings 2019 Network and Distributed System Security Symposium","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91396230","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}
Pub Date : 2014-01-01DOI: 10.14722/NDSS.2014.23287
Dongseok Jang, Zachary Tatlock, Sorin Lerner
Several defenses have increased the cost of traditional, low-level attacks that corrupt control data, e.g. return addresses saved on the stack, to compromise program execution. In response, creative adversaries have begun circumventing these defenses by exploiting programming errors to manipulate pointers to virtual tables, or vtables, of C++ objects. These attacks can hijack program control flow whenever a virtual method of a corrupted object is called, potentially allowing the attacker to gain complete control of the underlying system. In this paper we present SAFEDISPATCH, a novel defense to prevent such vtable hijacking by statically analyzing C++ programs and inserting sufficient runtime checks to ensure that control flow at virtual method call sites cannot be arbitrarily influenced by an attacker. We implemented SAFEDISPATCH as a Clang++/LLVM extension, used our enhanced compiler to build a vtable-safe version of the Google Chromium browser, and measured the performance overhead of our approach on popular browser benchmark suites. By carefully crafting a handful of optimizations, we were able to reduce average runtime overhead to just 2.1%.
{"title":"SafeDispatch: Securing C++ Virtual Calls from Memory Corruption Attacks","authors":"Dongseok Jang, Zachary Tatlock, Sorin Lerner","doi":"10.14722/NDSS.2014.23287","DOIUrl":"https://doi.org/10.14722/NDSS.2014.23287","url":null,"abstract":"Several defenses have increased the cost of traditional, low-level attacks that corrupt control data, e.g. return addresses saved on the stack, to compromise program execution. In response, creative adversaries have begun circumventing these defenses by exploiting programming errors to manipulate pointers to virtual tables, or vtables, of C++ objects. These attacks can hijack program control flow whenever a virtual method of a corrupted object is called, potentially allowing the attacker to gain complete control of the underlying system. In this paper we present SAFEDISPATCH, a novel defense to prevent such vtable hijacking by statically analyzing C++ programs and inserting sufficient runtime checks to ensure that control flow at virtual method call sites cannot be arbitrarily influenced by an attacker. We implemented SAFEDISPATCH as a Clang++/LLVM extension, used our enhanced compiler to build a vtable-safe version of the Google Chromium browser, and measured the performance overhead of our approach on popular browser benchmark suites. By carefully crafting a handful of optimizations, we were able to reduce average runtime overhead to just 2.1%.","PeriodicalId":20444,"journal":{"name":"Proceedings 2019 Network and Distributed System Security Symposium","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91396797","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}
Tor is vulnerable to network congestion and performance problems due to bulk data transfers. A large fraction of the available network capacity is consumed by a small percentage of Tor users, resulting in severe service degradation for the majority. Bulk users continuously drain relays of excess bandwidth, creating new network bottlenecks and exacerbating the effects of existing ones. While this problem may currently be attributed to rational users utilizing the network, it may also be exploited by a relatively low-resource adversary using similar techniques to contribute to a network denial of service (DoS) attack. Degraded service discourages the use of Tor, affecting both Tor's client diversity and anonymity. Equipped with mechanisms from communication networks, we design and implement three Tor-specific algorithms that throttle bulk transfers to reduce network congestion and increase network responsiveness. Unlike existing techniques, our algorithms adapt to network dynamics using only information local to a relay. We experiment with full-network deployments of our algorithms under a range of light to heavy network loads. We find that throttling results in significant improvements to web client performance while mitigating the negative effects of bulk transfers. We also analyze how throttling affects anonymity and compare the security of our algorithms under adversarial attack. We find that throttling reduces information leakage compared to unthrottled Tor while improving anonymity against realistic adversaries.
{"title":"Throttling Tor Bandwidth Parasites","authors":"Rob Jansen, Nicholas Hopper, P. Syverson","doi":"10.21236/ada559183","DOIUrl":"https://doi.org/10.21236/ada559183","url":null,"abstract":"Tor is vulnerable to network congestion and performance problems due to bulk data transfers. A large fraction of the available network capacity is consumed by a small percentage of Tor users, resulting in severe service degradation for the majority. Bulk users continuously drain relays of excess bandwidth, creating new network bottlenecks and exacerbating the effects of existing ones. While this problem may currently be attributed to rational users utilizing the network, it may also be exploited by a relatively low-resource adversary using similar techniques to contribute to a network denial of service (DoS) attack. Degraded service discourages the use of Tor, affecting both Tor's client diversity and anonymity. \u0000 \u0000Equipped with mechanisms from communication networks, we design and implement three Tor-specific algorithms that throttle bulk transfers to reduce network congestion and increase network responsiveness. Unlike existing techniques, our algorithms adapt to network dynamics using only information local to a relay. We experiment with full-network deployments of our algorithms under a range of light to heavy network loads. We find that throttling results in significant improvements to web client performance while mitigating the negative effects of bulk transfers. We also analyze how throttling affects anonymity and compare the security of our algorithms under adversarial attack. We find that throttling reduces information leakage compared to unthrottled Tor while improving anonymity against realistic adversaries.","PeriodicalId":20444,"journal":{"name":"Proceedings 2019 Network and Distributed System Security Symposium","volume":"49 1","pages":"349-363"},"PeriodicalIF":0.0,"publicationDate":"2012-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77659881","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}
Scott E. Coull, C. V. Wright, A. Keromytis, F. Monrose, M. Reiter
Anonymization plays a key role in enabling the public release of network datasets, and yet there are few, if any, techniques for evaluating the efficacy of network data anonymization techniques with respect to the privacy they afford. In fact, recent work suggests that many state-of-the-art anonymization techniques may leak more information than first thought. In this paper, we propose techniques for evaluating the anonymity of network data. Specifically, we simulate the behavior of an adversary whose goal is to deanonymize objects, such as hosts or web pages, within the network data. By doing so, we are able to quantify the anonymity of the data using information theoretic metrics, objectively compare the efficacy of anonymization techniques, and examine the impact of selective deanonymization on the anonymity of the data. Moreover, we provide several concrete applications of our approach on real network data in the hope of underscoring its usefulness to data
{"title":"Taming the Devil: Techniques for Evaluating Anonymized Network Data","authors":"Scott E. Coull, C. V. Wright, A. Keromytis, F. Monrose, M. Reiter","doi":"10.7916/D8BC47W0","DOIUrl":"https://doi.org/10.7916/D8BC47W0","url":null,"abstract":"Anonymization plays a key role in enabling the public release of network datasets, and yet there are few, if any, techniques for evaluating the efficacy of network data anonymization techniques with respect to the privacy they afford. In fact, recent work suggests that many state-of-the-art anonymization techniques may leak more information than first thought. In this paper, we propose techniques for evaluating the anonymity of network data. Specifically, we simulate the behavior of an adversary whose goal is to deanonymize objects, such as hosts or web pages, within the network data. By doing so, we are able to quantify the anonymity of the data using information theoretic metrics, objectively compare the efficacy of anonymization techniques, and examine the impact of selective deanonymization on the anonymity of the data. Moreover, we provide several concrete applications of our approach on real network data in the hope of underscoring its usefulness to data","PeriodicalId":20444,"journal":{"name":"Proceedings 2019 Network and Distributed System Security Symposium","volume":"1 1","pages":"125-135"},"PeriodicalIF":0.0,"publicationDate":"2008-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91395735","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}
Pub Date : 1996-02-22DOI: 10.1109/SNDSS.1996.10001
Nicholas Yialelis, M. Sloman
This paper describes a security framework for object-based distributed systems which is being developed in the CORBA-compliant OrbixTM environment. This framework allows the development of secure distributed applications on existing operating systems that do not support distributed security. The design aims at making the authentication and access control mechanisms transparent to the application level and supporting access control policies specified using the concept of the management domain. This concept has been developed as a means of specifying policies in terms of groups of objects. The description focuses on how the Access Control List paradigm is combined with pseudo capabilities which are used as hints to improve the time-efficiency of the access control decision mechanism. The protocols to support the (cascaded) delegation of access rights to agents acting on behalf of a grantor are explained. A brief description of the authentication mechanism is also given.
{"title":"A Security Framework Supporting Domain Based Access Control in Distributed Systems","authors":"Nicholas Yialelis, M. Sloman","doi":"10.1109/SNDSS.1996.10001","DOIUrl":"https://doi.org/10.1109/SNDSS.1996.10001","url":null,"abstract":"This paper describes a security framework for object-based distributed systems which is being developed in the CORBA-compliant OrbixTM environment. This framework allows the development of secure distributed applications on existing operating systems that do not support distributed security. The design aims at making the authentication and access control mechanisms transparent to the application level and supporting access control policies specified using the concept of the management domain. This concept has been developed as a means of specifying policies in terms of groups of objects. The description focuses on how the Access Control List paradigm is combined with pseudo capabilities which are used as hints to improve the time-efficiency of the access control decision mechanism. The protocols to support the (cascaded) delegation of access rights to agents acting on behalf of a grantor are explained. A brief description of the authentication mechanism is also given.","PeriodicalId":20444,"journal":{"name":"Proceedings 2019 Network and Distributed System Security Symposium","volume":"67 1","pages":"26-39"},"PeriodicalIF":0.0,"publicationDate":"1996-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83257160","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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