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Articles 3721 - 3750 of 8636
Full-Text Articles in Entire DC Network
Explaining Regressions Via Alignment Slicing And Mending, Haijun Wang, Yun Lin, Zijiang Yang, Jun Sun, Yang Liu, Jinsong Dong, Qinghua Zheng, Ting Liu
Explaining Regressions Via Alignment Slicing And Mending, Haijun Wang, Yun Lin, Zijiang Yang, Jun Sun, Yang Liu, Jinsong Dong, Qinghua Zheng, Ting Liu
Research Collection School Of Computing and Information Systems
Regression faults, which make working code stop functioning, are often introduced when developers make changes to the software. Many regression fault localization techniques have been proposed. However, issues like inaccuracy and lack of explanation are still obstacles for their practical application. In this work, we propose a trace-based approach to identifying not only where the root cause of a regression bug lies, but also how the defect is propagated to its manifestation as the explanation. In our approach, we keep the trace of original correct version as reference and infer the faulty steps on the trace of regression version so …
Smartembed: A Tool For Clone And Bug Detection In Smart Contracts Through Structural Code Embedding, Zhipeng Gao, Magalle Hewa Vinoj Yasanga Jayasundara, Lingxiao Jiang, Xin Xia, David Lo, John C. Grundy
Smartembed: A Tool For Clone And Bug Detection In Smart Contracts Through Structural Code Embedding, Zhipeng Gao, Magalle Hewa Vinoj Yasanga Jayasundara, Lingxiao Jiang, Xin Xia, David Lo, John C. Grundy
Research Collection School Of Computing and Information Systems
Ethereum has become a widely used platform to enable secure, Blockchain-based financial and business transactions. However, a major concern in Ethereum is the security of its smart contracts. Many identified bugs and vulnerabilities in smart contracts not only present challenges to maintenance of blockchain, but also lead to serious financial loses. There is a significant need to better assist developers in checking smart contracts and ensuring their reliability. In this paper, we propose a web service tool, named SMARTEMBED, which can help Solidity developers to find repetitive contract code and clone-related bugs in smart contracts. Our tool is based on …
Towards Generating Transformation Rules Without Examples For Android Api Replacement, Ferdian Thung, Hong Jin Kang, Lingxiao Jiang, David Lo
Towards Generating Transformation Rules Without Examples For Android Api Replacement, Ferdian Thung, Hong Jin Kang, Lingxiao Jiang, David Lo
Research Collection School Of Computing and Information Systems
Deprecation of APIs in software libraries is common when library maintainers make changes to a library and will no longer support certain APIs in the future. When deprecation occurs, developers whose programs depend on the APIs need to replace the usages of the deprecated APIs sooner or later. Often times, software documentation specifies which new APIs the developers should use in place of a deprecated API. However, replacing the usages of a deprecated API remains a challenge since developers may not know exactly how to use the new APIs. The developers would first need to understand the API changes before …
New Challenges In Display-Saturated Environments, Mateusz Andrzej Mikusz, Tsu Wei Kenny Choo, Rajesh Krishna Balan, Nigel Davies, Youngki Lee
New Challenges In Display-Saturated Environments, Mateusz Andrzej Mikusz, Tsu Wei Kenny Choo, Rajesh Krishna Balan, Nigel Davies, Youngki Lee
Research Collection School Of Computing and Information Systems
We live in a world in which our physical spaces are becoming increasingly enriched with computing technology. Pervasive displays have been at the forefront of this progression and are now commonplace. In this paper, we focus on the natural end-point of this trend and consider the case when displays become truly ubiquitous and saturate our physical environments. We use as motivation a state-of-the-art display deployment in which mobile users navigating the space are simultaneously exposed to many hundreds of displays within their field of view and we highlight a number of new research challenges.
Parametric Timed Model Checking For Guaranteeing Timed Opacity, Étienne André, Jun Sun
Parametric Timed Model Checking For Guaranteeing Timed Opacity, Étienne André, Jun Sun
Research Collection School Of Computing and Information Systems
Information leakage can have dramatic consequences on systems security. Among harmful information leaks, the timing information leakage is the ability for an attacker to deduce internal information depending on the system execution time. We address the following problem: given a timed system, synthesize the execution times for which one cannot deduce whether the system performed some secret behavior. We solve this problem in the setting of timed automata (TAs). We first provide a general solution, and then extend the problem to parametric TAs, by synthesizing internal timings making the TA secure. We study decidability, devise algorithms, and show that our …
Detecting Cyberattacks In Industrial Control Systems Using Online Learning Algorithms, Guangxia Li, Yulong Shen, Peilin Zhao, Xiao Lu, Jia Liu, Yangyang Liu, Steven C. H. Hoi
Detecting Cyberattacks In Industrial Control Systems Using Online Learning Algorithms, Guangxia Li, Yulong Shen, Peilin Zhao, Xiao Lu, Jia Liu, Yangyang Liu, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Industrial control systems are critical to the operation of industrial facilities, especially for critical infrastructures, such as refineries, power grids, and transportation systems. Similar to other information systems, a significant threat to industrial control systems is the attack from cyberspace-the offensive maneuvers launched by "anonymous" in the digital world that target computer-based assets with the goal of compromising a system's functions or probing for information. Owing to the importance of industrial control systems, and the possibly devastating consequences of being attacked, significant endeavors have been attempted to secure industrial control systems from cyberattacks. Among them are intrusion detection systems that …
Generic Construction Of Elgamal-Type Attribute-Based Encryption Schemes With Revocability And Dual-Policy, Shengmin Xu, Yinghui Zhang, Yingjiu Li, Ximeng Liu, Guomin Yang
Generic Construction Of Elgamal-Type Attribute-Based Encryption Schemes With Revocability And Dual-Policy, Shengmin Xu, Yinghui Zhang, Yingjiu Li, Ximeng Liu, Guomin Yang
Research Collection School Of Computing and Information Systems
Cloud is a computing paradigm for allowing data owners to outsource their data to enjoy on-demand services and mitigate the burden of local data storage. However, secure sharing of data via cloud remains an essential issue since the cloud service provider is untrusted. Fortunately, asymmetric-key encryption, such as identity-based encryption (IBE) and attribute-based encryption (ABE), provides a promising tool to offer data confidentiality and has been widely applied in cloud-based applications. In this paper, we summarize the common properties of most of IBE and ABE and introduce a cryptographic primitive called ElGamal type cryptosystem. This primitive can be used to …
Mixed-Dish Recognition With Contextual Relation Networks, Lixi Deng, Jingjing Chen, Qianru Sun, Xiangnan He, Sheng Tang, Zhaoyan Ming, Yongdong Zhang, Tat-Seng Chua
Mixed-Dish Recognition With Contextual Relation Networks, Lixi Deng, Jingjing Chen, Qianru Sun, Xiangnan He, Sheng Tang, Zhaoyan Ming, Yongdong Zhang, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Mixed dish is a food category that contains different dishes mixed in one plate, and is popular in Eastern and Southeast Asia. Recognizing individual dishes in a mixed dish image is important for health related applications, e.g. calculating the nutrition values. However, most existing methods that focus on single dish classification are not applicable to mixed-dish recognition. The new challenge in recognizing mixed-dish images are the complex ingredient combination and severe overlap among different dishes. In order to tackle these problems, we propose a novel approach called contextual relation networks (CR-Nets) that encodes the implicit and explicit contextual relations among …
Sieve: Helping Developers Sift Wheat From Chaff Via Cross-Platform Analysis, Agus Sulistya, Gede A. A. P. Prana, David Lo, Christoph Treude
Sieve: Helping Developers Sift Wheat From Chaff Via Cross-Platform Analysis, Agus Sulistya, Gede A. A. P. Prana, David Lo, Christoph Treude
Research Collection School Of Computing and Information Systems
Software developers have benefited from various sources of knowledge such as forums, question-and-answer sites, and social media platforms to help them in various tasks. Extracting software-related knowledge from different platforms involves many challenges. In this paper, we propose an approach to improve the effectiveness of knowledge extraction tasks by performing cross-platform analysis. Our approach is based on transfer representation learning and word embedding, leveraging information extracted from a source platform which contains rich domain-related content. The information extracted is then used to solve tasks in another platform (considered as target platform) with less domain-related content. We first build a word …
Topicsummary: A Tool For Analyzing Class Discussion Forums Using Topic Based Summarizations, Swapna Gottipati, Venky Shankararaman, Renjini Ramesh
Topicsummary: A Tool For Analyzing Class Discussion Forums Using Topic Based Summarizations, Swapna Gottipati, Venky Shankararaman, Renjini Ramesh
Research Collection School Of Computing and Information Systems
This Innovative Practice full paper, describes the application of text mining techniques for extracting insights from a course based online discussion forum through generation of topic based summaries. Discussions, either in classroom or online provide opportunity for collaborative learning through exchange of ideas that leads to enhanced learning through active participation. Online discussions offer a number of benefits namely providing additional time to reflect and synthesize information before writing, providing a natural platform for students to voice their ideas without any one student dominating the conversation, and providing a record of the student’s thoughts. An online discussion forum provides a …
On Analysing Supply And Demand In Labor Markets: Framework, Model And System, Hendrik Santoso Sugiarto, Ee-Peng Lim, Ngak Leng Sim
On Analysing Supply And Demand In Labor Markets: Framework, Model And System, Hendrik Santoso Sugiarto, Ee-Peng Lim, Ngak Leng Sim
Research Collection School Of Computing and Information Systems
The labor market refers to the market between job seekers and employers. As much of job seeking and talent hiring activities are now performed online, a large amount of job posting and application data have been collected and can be re-purposed for labor market analysis. In the labor market, both supply and demand are the key factors in determining an appropriate salary for both job applicants and employers in the market. However, it is challenging to discover the supply and demand for any labor market. In this paper, we propose a novel framework to built a labor market model using …
Why Reinventing The Wheels? An Empirical Study On Library Reuse And Re-Implementation, Bowen Xu, Le An, Ferdian Thung, Foutse Khomh, David Lo
Why Reinventing The Wheels? An Empirical Study On Library Reuse And Re-Implementation, Bowen Xu, Le An, Ferdian Thung, Foutse Khomh, David Lo
Research Collection School Of Computing and Information Systems
Nowadays, with the rapid growth of open source software (OSS), library reuse becomes more and more popular since a large amount of third- party libraries are available to download and reuse. A deeper understanding on why developers reuse a library (i.e., replacing self-implemented code with an external library) or re-implement a library (i.e., replacing an imported external library with self-implemented code) could help researchers better understand the factors that developers are concerned with when reusing code. This understanding can then be used to improve existing libraries and API recommendation tools for researchers and practitioners by using the developers concerns identified …
Automatic Generation Of Non-Intrusive Updates For Third-Party Libraries In Android Applications, Yue Duan, Lian Gao, Jie Hu, Heng Yin
Automatic Generation Of Non-Intrusive Updates For Third-Party Libraries In Android Applications, Yue Duan, Lian Gao, Jie Hu, Heng Yin
Research Collection School Of Computing and Information Systems
Third-Party libraries, which are ubiquitous in Android apps,have exposed great security threats to end users as they rarelyget timely updates from the app developers, leaving manysecurity vulnerabilities unpatched. This issue is due to thefact that manually updating libraries can be technically nontrivialand time-consuming for app developers. In this paper,we propose a technique that performs automatic generationof non-intrusive updates for third-party libraries in Androidapps. Given an Android app with an outdated library and anewer version of the library, we automatically update the oldlibrary in a way that is guaranteed to be fully backward compatibleand imposes zero impact to the library’s interactionswith …
A Lattice-Based Linkable Ring Signature Supporting Stealth Addresses, Zhen Liu, Khoa Nguyen, Guomin Yang, Huaxiong Wang, Duncan S. Wong
A Lattice-Based Linkable Ring Signature Supporting Stealth Addresses, Zhen Liu, Khoa Nguyen, Guomin Yang, Huaxiong Wang, Duncan S. Wong
Research Collection School Of Computing and Information Systems
First proposed in CryptoNote, a collection of popular privacy-centric cryptocurrencies have employed Linkable Ring Signature and a corresponding Key Derivation Mechanism (KeyDerM) for keeping the payer and payee of a transaction anonymous and unlinkable. The KeyDerM is used for generating a fresh signing key and the corresponding public key, referred to as a stealth address, for the transaction payee. The stealth address will then be used in the linkable ring signature next time when the payee spends the coin. However, in all existing works, including Monero, the privacy model only considers the two cryptographic primitives separately. In addition, to be …
Generating Expensive Relationship Features From Cheap Objects, Xiaogang Wang, Qianru Sun, Tat-Seng Chua, Marcelo Ang
Generating Expensive Relationship Features From Cheap Objects, Xiaogang Wang, Qianru Sun, Tat-Seng Chua, Marcelo Ang
Research Collection School Of Computing and Information Systems
We investigate the problem of object relationship classification of visual scenes. For a relationship object1-predicate-object2 that captures the object interaction, its representation is composed by the combination of object1 and object2 features. As a result, relationship classification models usually bias to the frequent objects, leading to poor generalization to rare or unseen objects. Inspired by the data augmentation methods, we propose a novel Semantic Transform Generative Adversarial Network (ST-GAN) that synthesizes relationship features for rare objects, conditioned on the features from random instances of the objects. Specifically, ST-GAN essentially offers a semantic transform function from cheap object features to expensive …
Rotation Invariant Convolutions For 3d Point Clouds Deep Learning, Zhiyuan Zhang, Binh-Son Hua, David W. Rosen, Sai-Kit Yeung
Rotation Invariant Convolutions For 3d Point Clouds Deep Learning, Zhiyuan Zhang, Binh-Son Hua, David W. Rosen, Sai-Kit Yeung
Research Collection School Of Computing and Information Systems
Recent progresses in 3D deep learning has shown that it is possible to design special convolution operators to consume point cloud data. However, a typical drawback is that rotation invariance is often not guaranteed, resulting in networks that generalizes poorly to arbitrary rotations. In this paper, we introduce a novel convolution operator for point clouds that achieves rotation invariance. Our core idea is to use low-level rotation invariant geometric features such as distances and angles to design a convolution operator for point cloud learning. The well-known point ordering problem is also addressed by a binning approach seamlessly built into the …
Directional Co-Clustering, Aghiles Salah, Mohamed Nadif
Directional Co-Clustering, Aghiles Salah, Mohamed Nadif
Research Collection School Of Computing and Information Systems
Co-clustering addresses the problem of simultaneous clustering of both dimensions of a data matrix. When dealing with high dimensional sparse data, co-clustering turns out to be more beneficial than one-sided clustering even if one is interested in clustering along one dimension only. Aside from being high dimensional and sparse, some datasets, such as document-term matrices, exhibit directional characteristics, and the L2 normalization of such data, so that it lies on the surface of a unit hypersphere, is useful. Popular co-clustering assumptions such as Gaussian or Multinomial are inadequate for this type of data. In this paper, we extend the scope …
Self-Refining Deep Symmetry Enhanced Network For Rain Removal, Hong Liu, Hanrong Ye, Xia Li, Wei Shi, Mengyuan Liu, Qianru Sun
Self-Refining Deep Symmetry Enhanced Network For Rain Removal, Hong Liu, Hanrong Ye, Xia Li, Wei Shi, Mengyuan Liu, Qianru Sun
Research Collection School Of Computing and Information Systems
Rain removal aims to remove the rain streaks on rain images. Traditional methods based on convolutional neural network (CNN) have achieved impressive results. However, these methods are under-performed when dealing with tilted rain streaks, because CNN is not equivariant to object rotations. To tackle this problem, we propose the Deep Symmetry Enhanced Network (DSEN) that explicitly extracts and learns from rotation-equivariant features from rain images. In addition, we design a self-refining strategy to remove rain streaks in a coarse-to-fine manner. The key idea is to reuse DSEN with an information link which passes the gradient flow to the finer stage. …
Efficient Distributed Reachability Querying Of Massive Temporal Graphs, Tianming Zhang, Yunjun Gao, Chen Lu, Wei Guo, Shiliang Pu, Baihua Zheng, Christian S. Jensen
Efficient Distributed Reachability Querying Of Massive Temporal Graphs, Tianming Zhang, Yunjun Gao, Chen Lu, Wei Guo, Shiliang Pu, Baihua Zheng, Christian S. Jensen
Research Collection School Of Computing and Information Systems
Reachability computation is a fundamental graph functionality with a wide range of applications. In spite of this, little work has as yet been done on efficient reachability queries over temporal graphs, which are used extensively to model time-varying networks, such as communication networks, social networks, and transportation schedule networks. Moreover, we are faced with increasingly large real-world temporal networks that may be distributed across multiple data centers. This state of affairs motivates the paper's study of efficient reachability queries on distributed temporal graphs. We propose an efficient index, called Temporal Vertex Labeling (TVL), which is a labeling scheme for distributed …
Finding Flaws From Password Authentication Code In Android Apps, Siqi Ma, Elisa Bertino, Surya Nepal, Jianru Li, Ostry Diethelm, Robert H. Deng, Sanjay Jha
Finding Flaws From Password Authentication Code In Android Apps, Siqi Ma, Elisa Bertino, Surya Nepal, Jianru Li, Ostry Diethelm, Robert H. Deng, Sanjay Jha
Research Collection School Of Computing and Information Systems
Password authentication is widely used to validate users’ identities because it is convenient to use, easy for users to remember, and simple to implement. The password authentication protocol transmits passwords in plaintext, which makes the authentication vulnerable to eavesdropping and replay attacks, and several protocols have been proposed to protect against this. However, we find that secure password authentication protocols are often implemented incorrectly in Android applications (apps). To detect the implementation flaws in password authentication code, we propose GLACIATE, a fully automated tool combining machine learning and program analysis. Instead of creating detection templates/rules manually, GLACIATE automatically and accurately …
Can Earables Support Effective User Engagement During Weight-Based Gym Exercises?, Meeralakshmi Radhakrishnan, Archan Misra
Can Earables Support Effective User Engagement During Weight-Based Gym Exercises?, Meeralakshmi Radhakrishnan, Archan Misra
Research Collection School Of Computing and Information Systems
We explore the use of personal ‘earable’ devices (widely used by gym-goers) in providing personalized, quantified insights and feedback to users performing gym exercises. As in-ear sensing by itself is often too weak to pick up exercise-driven motion dynamics, we propose a novel, low-cost system that can monitor multiple concurrent users by fusing data from (a) wireless earphones, equipped with inertial and physiological sensors and (b) inertial sensors attached to exercise equipment. We share preliminary findings from a small-scale study to demonstrate the promise of this approach, as well as identify open challenges.
Be Sensitive And Collaborative: Analyzing Impact Of Coverage Metrics In Greybox Fuzzing, Jinghan Wang, Yue Duan, Wei Song, Heng Yin, Chengyu Song
Be Sensitive And Collaborative: Analyzing Impact Of Coverage Metrics In Greybox Fuzzing, Jinghan Wang, Yue Duan, Wei Song, Heng Yin, Chengyu Song
Research Collection School Of Computing and Information Systems
Coverage-guided greybox fuzzing has become one of the most common techniques for finding software bugs. Coverage metric, which decides how a fuzzer selects new seeds, is an essential parameter of fuzzing and can significantly affect the results. While there are many existing works on the effectiveness of different coverage metrics on software testing, little is known about how different coverage metrics could actually affect the fuzzing results in practice. More importantly, it is unclear whether there exists one coverage metric that is superior to all the other metrics. In this paper, we report the first systematic study on the impact …
A Common Approach For Consumer And Provider Fairness In Recommendations, Dimitris Sacharidis, Kyriakos Mouratidis, Dimitrios Kleftogiannis
A Common Approach For Consumer And Provider Fairness In Recommendations, Dimitris Sacharidis, Kyriakos Mouratidis, Dimitrios Kleftogiannis
Research Collection School Of Computing and Information Systems
We present a common approach for handling consumer and provider fairness in recommendations. Our solution requires defining two key components, a classification of items and a target distribution, which together define the case of perfect fairness. This formulation allows distinct fairness concepts to be specified in a common framework. We further propose a novel reranking algorithm that optimizes for a desired trade-off between utility and fairness of a recommendation list.
Puncturable Proxy Re-Encryption Supporting To Group Messaging Service, Tran Viet Xuan Phuong, Willy Susilo, Jongkil Kim, Guomin Yang, Dongxi Liu
Puncturable Proxy Re-Encryption Supporting To Group Messaging Service, Tran Viet Xuan Phuong, Willy Susilo, Jongkil Kim, Guomin Yang, Dongxi Liu
Research Collection School Of Computing and Information Systems
This work envisions a new encryption primitive for many-to-many paradigms such as group messaging systems. Previously, puncturable encryption (PE) was introduced to provide forward security for asynchronous messaging services. However, existing PE schemes were proposed only for one-to-one communication, and causes a significant overhead for a group messaging system. In fact, the group communication over PE can only be achieved by encrypting a message multiple times for each receiver by the sender’s device, which is usually suitable to restricted resources such as mobile phones or sensor devices. Our new suggested scheme enables to re-encrypt ciphertexts of puncturable encryption by a …
A Case Study On Automated Fuzz Target Generation For Large Codebases, Matthew Kelly, Christoph Treude, Alex Murray
A Case Study On Automated Fuzz Target Generation For Large Codebases, Matthew Kelly, Christoph Treude, Alex Murray
Research Collection School Of Computing and Information Systems
Fuzz Testing is a largely automated testing technique that provides random and unexpected input to a program in attempt to trigger failure conditions. Much of the research conducted thus far into Fuzz Testing has focused on developing improvements to available Fuzz Testing tools and frameworks in order to improve efficiency. In this paper however, we instead look at a way in which we can reduce the amount of developer time required to integrate Fuzz Testing to help maintain an existing codebase. We accomplish this with a new technique for automatically generating Fuzz Targets, the modified versions of programs on which …
Enhancing Python Compiler Error Messages Via Stack Overflow, Emillie Thiselton, Christoph Treude
Enhancing Python Compiler Error Messages Via Stack Overflow, Emillie Thiselton, Christoph Treude
Research Collection School Of Computing and Information Systems
Background: Compilers tend to produce cryptic and uninformative error messages, leaving programmers confused and requiring them to spend precious time to resolve the underlying error. To find help, programmers often take to online question-and-answer forums such as Stack Overflow to start discussion threads about the errors they encountered.Aims: We conjecture that information from Stack Overflow threads which discuss compiler errors can be automatically collected and repackaged to provide programmers with enhanced compiler error messages, thus saving programmers' time and energy.Method: We present Pycee, a plugin integrated with the popular Sublime Text IDE to provide enhanced compiler error messages for the …
Confusion And Information Triggered By Photos In Persona Profiles, Joni Salminen, Soon-Gyo Jung, Jisun An, Haewoon Kwak, Lene Nielsen, Bernard J. Jansen
Confusion And Information Triggered By Photos In Persona Profiles, Joni Salminen, Soon-Gyo Jung, Jisun An, Haewoon Kwak, Lene Nielsen, Bernard J. Jansen
Research Collection School Of Computing and Information Systems
We investigate whether additional photos beyond a single headshot makes a persona profile more informative without confusing the end user. We conduct an eye-tracking experiment and qualitative interviews with digital content creators after varying the persona in photos via a single headshot, a headshot and photo of the persona in different contexts, and a headshot with photos of different people with key persona attributes the gender and age. Findings show that contextual photos provide significantly more persona information to end users; however, showing photos of multiple people engenders confusion and lowers informativeness. Also, as anticipated, viewing additional photos requires more …
Detecting Toxicity Triggers In Online Discussions, Hamad Bin Khalifa University, Haewoon Kwak
Detecting Toxicity Triggers In Online Discussions, Hamad Bin Khalifa University, Haewoon Kwak
Research Collection School Of Computing and Information Systems
Despite the considerable interest in the detection of toxic comments, there has been little research investigating the causes -- i.e., triggers -- of toxicity. In this work, we first propose a formal definition of triggers of toxicity in online communities. We proceed to build an LSTM neural network model using textual features of comments, and then, based on a comprehensive review of previous literature, we incorporate topical and sentiment shift in interactions as features. Our model achieves an average accuracy of 82.5% of detecting toxicity triggers from diverse Reddit communities.
Efficient Oblivious Transfer With Membership Verification, Weiwei Liu, Dazhi Sun, Yangguang Tian
Efficient Oblivious Transfer With Membership Verification, Weiwei Liu, Dazhi Sun, Yangguang Tian
Research Collection School Of Computing and Information Systems
In this article, we introduce a new concept of oblivious transfer with membership verification that allows any legitimate group users to obtain services from a service provider in an oblivious manner. We present two oblivious transfer with membership verification schemes, differing in design. In the first scheme, a trusted group manager issues credentials for a pre-determined group of users so that the group of users with a valid group credential can obtain services from the service provider, while the choices made by group users remain oblivious to the service provider. The second scheme avoids the trusted group manager, which allows …
Lightweight Fine-Grained Search Over Encrypted Data In Fog Computing, Yinbin Miao, Jianfeng Ma, Ximeng Liu, Jian Weng, Hongwei Li, Hui Li
Lightweight Fine-Grained Search Over Encrypted Data In Fog Computing, Yinbin Miao, Jianfeng Ma, Ximeng Liu, Jian Weng, Hongwei Li, Hui Li
Research Collection School Of Computing and Information Systems
Fog computing, as an extension of cloud computing, outsources the encrypted sensitive data to multiple fog nodes on the edge of Internet of Things (IoT) to decrease latency and network congestion. However, the existing ciphertext retrieval schemes rarely focus on the fog computing environment and most of them still impose high computational and storage overhead on resource-limited end users. In this paper, we first present a Lightweight Fine-Grained ciphertexts Search (LFGS) system in fog computing by extending Ciphertext-Policy Attribute-Based Encryption (CP-ABE) and Searchable Encryption (SE) technologies, which can achieve fine-grained access control and keyword search simultaneously. The LFGS can shift …