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Articles 391 - 420 of 1102
Full-Text Articles in Information Security
An Extended Framework Of Privacy-Preserving Computation With Flexible Access Control, Wenxiu Ding, Rui Hu, Zheng Yan, Xinren Qian, Robert H. Deng, Laurence T. Yang, Mianxiong Dong
An Extended Framework Of Privacy-Preserving Computation With Flexible Access Control, Wenxiu Ding, Rui Hu, Zheng Yan, Xinren Qian, Robert H. Deng, Laurence T. Yang, Mianxiong Dong
Research Collection School Of Computing and Information Systems
Cloud computing offers various services based on outsourced data by utilizing its huge volume of resources and great computation capability. However, it also makes users lose full control over their data. To avoid the leakage of user data privacy, encrypted data are preferred to be uploaded and stored in the cloud, which unfortunately complicates data analysis and access control. In particular, few existing works consider the fine-grained access control over the computational results from ciphertexts. Though our previous work proposed a framework to support several basic computations (such as addition, multiplication and comparison) with flexible access control, privacy-preserving division calculations …
A New Framework For Privacy-Preserving Biometric-Based Remote User Authentication, Yangguang Tian, Yingjiu Li, Robert H. Deng, Nan Li, Pengfei Wu, Anyi Liu
A New Framework For Privacy-Preserving Biometric-Based Remote User Authentication, Yangguang Tian, Yingjiu Li, Robert H. Deng, Nan Li, Pengfei Wu, Anyi Liu
Research Collection School Of Computing and Information Systems
In this paper, we introduce the first general framework for strong privacy-preserving biometric-based remote user authentication based on oblivious RAM (ORAM) protocol and computational fuzzy extractors. We define formal security models for the general framework, and we prove that it can achieve user authenticity and strong privacy. In particular, the general framework ensures that: (1) a strong privacy and a log-linear time-complexity are achieved by using a new tree-based ORAM protocol; (2) a constant bandwidth cost is achieved by exploiting computational fuzzy extractors in the challenge-response phase of remote user authentications.
Editing-Enabled Signatures: A New Tool For Editing Authenticated Data, Binanda Sengupta, Yingjiu Li, Yangguang Tian, Robert H. Deng
Editing-Enabled Signatures: A New Tool For Editing Authenticated Data, Binanda Sengupta, Yingjiu Li, Yangguang Tian, Robert H. Deng
Research Collection School Of Computing and Information Systems
Data authentication primarily serves as a tool to achieve data integrity and source authentication. However, traditional data authentication does not fit well where an intermediate entity (editor) is required to modify the authenticated data provided by the source/data owner before sending the data to other recipients. To ask the data owner for authenticating each modified data can lead to higher communication overhead. In this article, we introduce the notion of editing-enabled signatures where the data owner can choose any set of modification operations applicable on the data and still can restrict any possibly untrusted editor to authenticate the data modified …
Provably Robust Decisions Based On Potentially Malicious Sources Of Information, Tim Muller, Dongxia Wang, Jun Sun
Provably Robust Decisions Based On Potentially Malicious Sources Of Information, Tim Muller, Dongxia Wang, Jun Sun
Research Collection School Of Computing and Information Systems
Sometimes a security-critical decision must be made using information provided by peers. Think of routing messages, user reports, sensor data, navigational information, blockchain updates. Attackers manifest as peers that strategically report fake information. Trust models use the provided information, and attempt to suggest the correct decision. A model that appears accurate by empirical evaluation of attacks may still be susceptible to manipulation. For a security-critical decision, it is important to take the entire attack space into account. Therefore, we define the property of robustness: the probability of deciding correctly, regardless of what information attackers provide. We introduce the notion of …
Talk Like Somebody Is Watching: Understanding And Supporting Novice Live Streamers, Terrance Mok, Colin Matthew Au Yueng, Anthony Tang, Lora Oehlberg
Talk Like Somebody Is Watching: Understanding And Supporting Novice Live Streamers, Terrance Mok, Colin Matthew Au Yueng, Anthony Tang, Lora Oehlberg
Research Collection School Of Computing and Information Systems
We built a chatbot system–Audience Bot–that simulates an audience for novice live streamers to engage with while streaming. New live streamers on platforms like Twitch are expected to perform and talk to themselves, even while no one is watching. We ran an observational lab study on how Audience Bot assists novice live streamers as they acclimate to multitasking–simultaneously playing a video game while performing for a (simulated) audience.
Regulating Personal Data Usage In Covid-19 Control Conditions, Mark Findlay, Nydia Remolina
Regulating Personal Data Usage In Covid-19 Control Conditions, Mark Findlay, Nydia Remolina
Centre for AI & Data Governance (2019-2025)
As the COVID-19 health pandemic ebbs and flows world-wide, governments and private companies across the globe are utilising AI-assisted surveillance, reporting, mapping and tracing technologies with the intention of slowing the spread of the virus. These technologies have capacity to amass and share personal data for community control and citizen safety motivations that empower state agencies and inveigle citizen co-operation which could only be imagined outside times of real and present personal danger. While not cavilling with the short-term necessity for these technologies and the data they control, process and share in the health regulation mission (provided that the technology …
Pmkt: Privacy-Preserving Multi-Party Knowledge Transfer For Financial Market Forecasting, Zhuoran Ma, Jianfeng Ma, Yinbin Miao, Kim-Kwang Raymond Choo, Ximeng Liu, Xiangyu Wang, Tengfei Yang
Pmkt: Privacy-Preserving Multi-Party Knowledge Transfer For Financial Market Forecasting, Zhuoran Ma, Jianfeng Ma, Yinbin Miao, Kim-Kwang Raymond Choo, Ximeng Liu, Xiangyu Wang, Tengfei Yang
Research Collection School Of Computing and Information Systems
While decision-making task is critical in knowledge transfer, particularly from multi-source domains, existing knowledge transfer approaches are not generally designed to be privacy preserving. This has potential legal and financial implications, particularly in sensitive applications such as financial market forecasting. Therefore, in this paper, we propose a Privacy-preserving Multi-party Knowledge Transfer system (PMKT), based on decision trees, for financial market forecasting. Specifically, in PMKT, we leverage a cryptographic-based model sharing technique to securely outsource knowledge reflected in decision trees of multiple parties, and design a secure computation mechanism to facilitate privacy-preserving knowledge transfer. An encrypted user-submitted request from the target …
Symbolic Verification Of Message Passing Interface Programs, Hengbiao Yu, Zhenbang Chen, Xianjin Fu, Ji Wang, Zhendong Su, Jun Sun, Chun Huang, Wei Dong
Symbolic Verification Of Message Passing Interface Programs, Hengbiao Yu, Zhenbang Chen, Xianjin Fu, Ji Wang, Zhendong Su, Jun Sun, Chun Huang, Wei Dong
Research Collection School Of Computing and Information Systems
Message passing is the standard paradigm of programming in high-performance computing. However, verifying Message Passing Interface (MPI) programs is challenging, due to the complex program features (such as non-determinism and non-blocking operations). In this work, we present MPI symbolic verifier (MPI-SV), the first symbolic execution based tool for automatically verifying MPI programs with non-blocking operations. MPI-SV combines symbolic execution and model checking in a synergistic way to tackle the challenges in MPI program verification. The synergy improves the scalability and enlarges the scope of verifiable properties. We have implemented MPI-SV and evaluated it with 111 real-world MPI verification tasks. The …
The Future Of Work Now: Cyber Threat Attribution At Fireeye, Thomas H. Davenport, Steven M. Miller
The Future Of Work Now: Cyber Threat Attribution At Fireeye, Thomas H. Davenport, Steven M. Miller
Research Collection School Of Computing and Information Systems
One of the most frequently-used phrases at business events these days is “the future of work.” It’s increasingly clear that artificial intelligence and other new technologies will bring substantial changes in work tasks and business processes. But while these changes are predicted for the future, they’re already present in many organizations for many different jobs. The job and incumbent described below is an example of this phenomenon. It’s a clear example of an existing job that’s been transformed by AI and related tools.
A Fully Distributed Hierarchical Attribute-Based Encryption Scheme, Ali Mohammad, Javad Mohajeri, Ximeng Liu, Ximeng Liu
A Fully Distributed Hierarchical Attribute-Based Encryption Scheme, Ali Mohammad, Javad Mohajeri, Ximeng Liu, Ximeng Liu
Research Collection School Of Computing and Information Systems
With the development of cloud computing, many enterprises have been interested in outsourcing their data to cloud servers to decrease IT costs and rise capabilities of provided services. To afford confidentiality and fine-grained data access control, attribute-based encryption (ABE) was proposed and used in several cloud storage systems. However, scalability and flexibility in key delegation and user revocation mechanisms are primary issues in ABE systems. In this paper, we introduce the concept of a fully distributed revocable ciphertext-policy hierarchical ABE (FDR-CP-HABE) and design the first FDR-CP-HABE scheme. Our scheme offers a high level of flexibility and scalability in the key …
A Lightweight Privacy-Preserving Cnn Feature Extraction Framework For Mobile Sensing, Kai Huang, Ximeng Liu, Shaojing Fu, Deke Guo, Ming Xu
A Lightweight Privacy-Preserving Cnn Feature Extraction Framework For Mobile Sensing, Kai Huang, Ximeng Liu, Shaojing Fu, Deke Guo, Ming Xu
Research Collection School Of Computing and Information Systems
The proliferation of various mobile devices equipped with cameras results in an exponential growth of the amount of images. Recent advances in the deep learning with convolutional neural networks (CNN) have made CNN feature extraction become an effective way to process these images. However, it is still a challenging task to deploy the CNN model on the mobile sensors, which are typically resource-constrained in terms of the storage space, the computing capacity, and the battery life. Although cloud computing has become a popular solution, data security and response latency are always the key issues. Therefore, in this paper, we propose …
Attribute-Based Cloud Data Integrity Auditing For Secure Outsourced Storage, Yong Yu, Yannan Li, Bo Yang, Willy Susilo, Guomin Yang, Jian Bai
Attribute-Based Cloud Data Integrity Auditing For Secure Outsourced Storage, Yong Yu, Yannan Li, Bo Yang, Willy Susilo, Guomin Yang, Jian Bai
Research Collection School Of Computing and Information Systems
Outsourced storage such as cloud storage can significantly reduce the burden of data management of data owners. Despite of a long list of merits of cloud storage, it triggers many security risks at the same time. Data integrity, one of the most burning challenges in secure cloud storage, is a fundamental and pivotal element in outsourcing services. Outsourced data auditing protocols enable a verifier to efficiently check the integrity of the outsourced files without downloading the entire file from the cloud, which can dramatically reduce the communication overhead between the cloud server and the verifier. Existing protocols are mostly based …
On The Security Of Lwe Cryptosystem Against Subversion Attacks, Zhichao Yang, Rongmao Chen, Chao Li, Longjiang Qu, Guomin Yang
On The Security Of Lwe Cryptosystem Against Subversion Attacks, Zhichao Yang, Rongmao Chen, Chao Li, Longjiang Qu, Guomin Yang
Research Collection School Of Computing and Information Systems
Subversion of cryptography has received wide attentions especially after the Snowden Revelations in 2013. Most of the currently proposed subversion attacks essentially rely on the freedom of randomness choosing in the cryptographic protocol to hide backdoors embedded in the cryptosystems. Despite the fact that significant progresses in this line of research have been made, most of them mainly considered the classical setting, while the research gap regarding subversion attacks against post-quantum cryptography remains tremendous. Inspired by this observation, we investigate a subversion attack against existing protocol that is proved post-quantum secure. Particularly, we show an efficient way to undetectably subvert …
Identity-Based Encryption Transformation For Flexible Sharing Of Encrypted Data In Public Cloud, Robert H. Deng, Zheng Qin, Qianhong Wu, Zhenyu Guan, Robert H. Deng, Yujue Wang, Yunya Zhou
Identity-Based Encryption Transformation For Flexible Sharing Of Encrypted Data In Public Cloud, Robert H. Deng, Zheng Qin, Qianhong Wu, Zhenyu Guan, Robert H. Deng, Yujue Wang, Yunya Zhou
Research Collection School Of Computing and Information Systems
With the rapid development of cloud computing, an increasing number of individuals and organizations are sharing data in the public cloud. To protect the privacy of data stored in the cloud, a data owner usually encrypts his data in such a way that certain designated data users can decrypt the data. This raises a serious problem when the encrypted data needs to be shared to more people beyond those initially designated by the data owner. To address this problem, we introduce and formalize an identity-based encryption transformation (IBET) model by seamlessly integrating two well-established encryption mechanisms, namely identity-basedencryption (IBE) and …
Leakage-Resilient Biometric-Based Remote User Authentication With Fuzzy Extractors, Yangguang Tian, Yingjiu Li, Binanda Sengupta, Nan Li, Chunhua Su
Leakage-Resilient Biometric-Based Remote User Authentication With Fuzzy Extractors, Yangguang Tian, Yingjiu Li, Binanda Sengupta, Nan Li, Chunhua Su
Research Collection School Of Computing and Information Systems
Fuzzy extractors convert biometrics and other noisy data into a cryptographic key for security applications such as remote user authentication. Leakage attacks, such as side channel attacks, have been extensively modelled and studied in the literature. However, to the best of our knowledge, leakage attacks to biometric-based remote user authentication with fuzzy extractors have never been studied rigorously. In this paper, we propose a generic framework of leakage-resilient and privacy-preserving biometric-based remote user authentication that allows an authorized user to securely authenticate herself to a remote authentication server using her biometrics. In particular, the authorized user relies only on her …
A New Construction For Linkable Secret Handshake, Yangguang Tian, Yingjiu Li, Robert H. Deng, Nan Li, Guomin Yang, Zheng Yang
A New Construction For Linkable Secret Handshake, Yangguang Tian, Yingjiu Li, Robert H. Deng, Nan Li, Guomin Yang, Zheng Yang
Research Collection School Of Computing and Information Systems
In this paper, we introduce a new construction for linkable secret handshake that allows authenticated users to perform handshake anonymously within allowable times. We define formal security models for the new construction, and prove that it can achieve session key security, anonymity, untraceability and linkable affiliation-hiding. In particular, the proposed construction ensures that (i) anyone can trace the real identities of dishonest users who perform handshakes for more than k times; and (ii) an optimal communication cost between authorized users is achieved by exploiting the proof of knowledges.
Privacy-Preserving Outsourced Support Vector Machine Design For Secure Drug Discovery, Ximeng Liu, Robert H. Deng, Kim-Kwang Raymond Choo, Yang Yang
Privacy-Preserving Outsourced Support Vector Machine Design For Secure Drug Discovery, Ximeng Liu, Robert H. Deng, Kim-Kwang Raymond Choo, Yang Yang
Research Collection School Of Computing and Information Systems
In this paper, we propose a framework for privacy-preserving outsourced drug discovery in the cloud, which we refer to as POD. Specifically, POD is designed to allow the cloud to securely use multiple drug formula providers' drug formulas to train Support Vector Machine (SVM) provided by the analytical model provider. In our approach, we design secure computation protocols to allow the cloud server to perform commonly used integer and fraction computations. To securely train the SVM, we design a secure SVM parameter selection protocol to select two SVM parameters and construct a secure sequential minimal optimization protocol to privately refresh …
Energy-Efficient Distance-Bounding With Residual Charge Computation, Yunhui Zhuang, Anjia Yang, Gerhard Hancke, Duncan S. Wong, Guomin Yang
Energy-Efficient Distance-Bounding With Residual Charge Computation, Yunhui Zhuang, Anjia Yang, Gerhard Hancke, Duncan S. Wong, Guomin Yang
Research Collection School Of Computing and Information Systems
Real-time location systems are often required in industrial applications. In addition to securely determining an item's location, these systems also need to accommodate energy-limited tracking tokens. Distance-bounding protocols enable a Verifier to cryptographically determine an upper-bound on the physical distance to a Prover by measuring the round-trip time of specially designed challenge-response messages. This type of protocols serve as countermeasure to three common attacks on location-based systems and have been extensively studied with the goal of achieving optimal security bounds for the respective attacks. In this paper, we propose a new energy-efficient distance-bounding protocol that protects against all three common …
Space Efficient Revocable Ibe For Mobile Devices In Cloud Computing, Baodong Qin, Ximeng Liu, Zhuo Wei, Dong Zheng
Space Efficient Revocable Ibe For Mobile Devices In Cloud Computing, Baodong Qin, Ximeng Liu, Zhuo Wei, Dong Zheng
Research Collection School Of Computing and Information Systems
Revocation capacity is one of the main properties for an identity-based encryption (IBE), as in practice users’ private keys are possibly leaked or expired. However, existing revocable IBE schemes usually lack of short keys. Recently, Lin et al. proposed a method to design space efficient revocable IBE scheme from non-monotonic key-policy attribute-based encryption scheme. But, it requires too many pairings (linear to the number of revoked users) to decrypt an IBE ciphertext. In this study, we overcome this problem by adopting the technique of server-aided revocation, recently proposed by Qin et al. in ESORICS 2015. The main contribution is a …
Privacy-Preserving Data Processing With Flexible Access Control, Wenxiu Ding, Zheng Yan, Robert H. Deng
Privacy-Preserving Data Processing With Flexible Access Control, Wenxiu Ding, Zheng Yan, Robert H. Deng
Research Collection School Of Computing and Information Systems
Cloud computing provides an efficient and convenient platform for cloud users to store, process and control their data. Cloud overcomes the bottlenecks of resource-constrained user devices and greatly releases their storage and computing burdens. However, due to the lack of full trust in cloud service providers, the cloud users generally prefer to outsource their sensitive data in an encrypted form, which, however, seriously complicates data processing, analysis, as well as access control. Homomorphic encryption (HE) as a single key system cannot flexibly control data sharing and access after encrypted data processing. How to realize various computations over encrypted data in …
Saga: Efficient And Large-Scale Detection Of Near-Miss Clones With Gpu Acceleration, Guanhua Li, Yijian Wu, Chanchal K. Roy, Jun Sun, Xin Peng, Nanjie Zhan, Bin Hu, Jingyi Ma
Saga: Efficient And Large-Scale Detection Of Near-Miss Clones With Gpu Acceleration, Guanhua Li, Yijian Wu, Chanchal K. Roy, Jun Sun, Xin Peng, Nanjie Zhan, Bin Hu, Jingyi Ma
Research Collection School Of Computing and Information Systems
Clone detection on large code repository is necessary for many big code analysis tasks. The goal is to provide rich information on identical and similar code across projects. Detecting near-miss code clones on big code is challenging since it requires intensive computing and memory resources as the scale of the source code increases. In this work, we propose SAGA, an efficient suffix-array based code clone detection tool designed with sophisticated GPU optimization. SAGA not only detects Type-l and Type-2 clones but also does so for cross-project large repositories and for the most computationally expensive Type-3 clones. Meanwhile, it also works …
Deepbindiff: Learning Program-Wide Code Representations For Binary Diffing, Yue Duan, Xuezixiang Li, Jinghan Wang, Wang, Heng Yin
Deepbindiff: Learning Program-Wide Code Representations For Binary Diffing, Yue Duan, Xuezixiang Li, Jinghan Wang, Wang, Heng Yin
Research Collection School Of Computing and Information Systems
Binary diffing analysis quantitatively measures the differences between two given binaries and produces fine-grained basic block matching. It has been widely used to enable different kinds of critical security analysis. However, all existing program analysis and machine learning based techniques suffer from low accuracy, poor scalability, coarse granularity, or require extensive labeled training data to function. In this paper, we propose an unsupervised program-wide code representation learning technique to solve the problem. We rely on both the code semantic information and the program-wide control flow information to generate block embeddings. Furthermore, we propose a k-hop greedy matching algorithm to find …
Privacy-Preserving Network Path Validation, Binanda Sengupta, Yingjiu Li, Kai Bu, Robert H. Deng
Privacy-Preserving Network Path Validation, Binanda Sengupta, Yingjiu Li, Kai Bu, Robert H. Deng
Research Collection School Of Computing and Information Systems
The end-users communicating over a network path currently have no control over the path. For a better quality of service, the source node often opts for a superior (or premium) network path to send packets to the destination node. However, the current Internet architecture provides no assurance that the packets indeed follow the designated path. Network path validation schemes address this issue and enable each node present on a network path to validate whether each packet has followed the specific path so far. In this work, we introduce two notions of privacy—path privacy and index privacy—in the context of network …
Joint Learning Of Answer Selection And Answer Summary Generation In Community Question Answering, Yang Deng, Wai Lam, Yuexiang Xie, Daoyuan Chen, Yaliang Li, Min Yang, Ying Shen
Joint Learning Of Answer Selection And Answer Summary Generation In Community Question Answering, Yang Deng, Wai Lam, Yuexiang Xie, Daoyuan Chen, Yaliang Li, Min Yang, Ying Shen
Research Collection School Of Computing and Information Systems
Community question answering (CQA) gains increasing popularity in both academy and industry recently. However, the redundancy and lengthiness issues of crowdsourced answers limit the performance of answer selection and lead to reading difficulties and misunderstandings for community users. To solve these problems, we tackle the tasks of answer selection and answer summary generation in CQA with a novel joint learning model. Specifically, we design a question-driven pointer-generator network, which exploits the correlation information between question-Answer pairs to aid in attending the essential information when generating answer summaries. Meanwhile, we leverage the answer summaries to alleviate noise in original lengthy answers …
Analysis Of Blockchain Protocol Against Static Adversarial Miners Corrupted By Long Delay Attackers, Quan Yuan, Puwen Wei, Keting Jia, Haiyang Xue
Analysis Of Blockchain Protocol Against Static Adversarial Miners Corrupted By Long Delay Attackers, Quan Yuan, Puwen Wei, Keting Jia, Haiyang Xue
Research Collection School Of Computing and Information Systems
Bitcoin, which was initially introduced by Nakamoto, is the most disruptive and impactive cryptocurrency. The core Bitcoin technology is the so-called blockchain protocol. In recent years, several studies have focused on rigorous analyses of the security of Nakamoto’s blockchain protocol in an asynchronous network where network delay must be considered. Wei, Yuan, and Zheng investigated the effect of a long delay attack against Nakamoto’s blockchain protocol. However, their proof only holds in the honest miner setting. In this study, we improve Wei, Yuan and Zheng’s result using a stronger model where the adversary can perform long delay attacks and corrupt …
Does Reputational Sanctions Deter Negligence In Information Security Management? A Field Quasi-Experiment, Qian Tang, Andrew B. Whinston
Does Reputational Sanctions Deter Negligence In Information Security Management? A Field Quasi-Experiment, Qian Tang, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
Security negligence, a major cause of data breaches, occurs when an organization’s information technology management fails to adequately address security vulnerabilities. By conducting a field quasi-experiment using outgoing spam as a focal security issue, this study investigates the effectiveness of reputational sanctions in reducing security negligence in a global context. In the quasi-experiment, a reputational sanction mechanism based on outgoing spam was established for four countries, and for each country, reputational sanctions were imposed on the 10 organizations with the largest outgoing spam volumes—that is, these organizations were listed publicly. We find that because of our reputational sanction mechanism, organizations …
Example-Based Colourization Via Dense Encoding Pyramids, Chufeng Xiao, Chu Han, Zhuming Zhang, Jing Qin, Tien-Tsin Wong, Guoqiang Han, Shengfeng He
Example-Based Colourization Via Dense Encoding Pyramids, Chufeng Xiao, Chu Han, Zhuming Zhang, Jing Qin, Tien-Tsin Wong, Guoqiang Han, Shengfeng He
Research Collection School Of Computing and Information Systems
We propose a novel deep example-based image colourization method called dense encoding pyramid network. In our study, we define the colourization as a multinomial classification problem. Given a greyscale image and a reference image, the proposed network leverages large-scale data and then predicts colours by analysing the colour distribution of the reference image. We design the network as a pyramid structure in order to exploit the inherent multi-scale, pyramidal hierarchy of colour representations. Between two adjacent levels, we propose a hierarchical decoder-encoder filter to pass the colour distributions from the lower level to higher level in order to take both …
Key Regeneration-Free Ciphertext-Policy Attribute-Based Encryption And Its Application, Hui Cui, Robert H. Deng, Baodong Qin, Jian Weng
Key Regeneration-Free Ciphertext-Policy Attribute-Based Encryption And Its Application, Hui Cui, Robert H. Deng, Baodong Qin, Jian Weng
Research Collection School Of Computing and Information Systems
Attribute-based encryption (ABE) provides a promising solution for enabling scalable access control over encrypted data stored in the untrusted servers (e.g., cloud) due to its ability to perform data encryption and decryption defined over descriptive attributes. In order to bind different components which correspond to different attributes in a user's attribute-based decryption key together, key randomization technique has been applied in most existing ABE schemes. This randomization method, however, also empowers a user the capability of regenerating a newly randomized decryption key over a subset of the attributes associated with the original decryption key. Because key randomization breaks the linkage …
Game Theoretical Study On Client-Controlled Cloud Data Deduplication, Xueqin Liang, Zheng Yan, Robert H. Deng
Game Theoretical Study On Client-Controlled Cloud Data Deduplication, Xueqin Liang, Zheng Yan, Robert H. Deng
Research Collection School Of Computing and Information Systems
Data deduplication eliminates redundant data and is receiving increasing attention in cloud storage services due to the proliferation of big data and the demand for efficient storage. Data deduplication not only requires a consummate technological designing, but also involves multiple parties with conflict interests. Thus, how to design incentive mechanisms and study their acceptance by all relevant stakeholders remain important open issues. In this paper, we detail the payoff structure of a client-controlled deduplication scheme and analyze the feasibilities of unified discount and individualized discount under this structure. Through game theoretical study, a privacy-preserving individualized discount-based incentive mechanism is further …
Systematic Classification Of Attackers Via Bounded Model Checking, Eric Rothstein-Morris, Jun Sun, Sudipta Chattopadyay
Systematic Classification Of Attackers Via Bounded Model Checking, Eric Rothstein-Morris, Jun Sun, Sudipta Chattopadyay
Research Collection School Of Computing and Information Systems
In this work, we study the problem of verification of systems in the presence of attackers using bounded model checking. Given a system and a set of security requirements, we present a methodology to generate and classify attackers, mapping them to the set of requirements that they can break. A naive approach suffers from the same shortcomings of any large model checking problem, i.e., memory shortage and exponential time. To cope with these shortcomings, we describe two sound heuristics based on cone-of-influence reduction and on learning, which we demonstrate empirically by applying our methodology to a set of hardware benchmark …