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Research Collection School Of Computing and Information Systems

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Full-Text Articles in Information Security

Effect Of Probable And Guaranteed Monetary Value Gains And Losses On Cybersecurity Behavior Of Users, S. Ravindran, Fiona Fui-Hoon Nah, M. Cheng May 2018

Effect Of Probable And Guaranteed Monetary Value Gains And Losses On Cybersecurity Behavior Of Users, S. Ravindran, Fiona Fui-Hoon Nah, M. Cheng

Research Collection School Of Computing and Information Systems

The objective of this research is to examine users’ cybersecurity behavior in monetary gain and loss scenarios. Using Prospect Theory, we hypothesize that users are more likely to engage in risky cybersecurity behavior to avoid monetary losses than to benefit from monetary gains. We also hypothesize that guaranteed gains have a greater effect on a user’s risk-taking behavior than potential gains, and potential losses have a greater effect on a user’s risk-taking behavior than guaranteed losses. An experimental study is proposed to test the research hypotheses.

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Expressive Query Over Outsourced Encrypted Data, Yang Yang, Ximeng Liu, Robert H. Deng May 2018

Expressive Query Over Outsourced Encrypted Data, Yang Yang, Ximeng Liu, Robert H. Deng

Research Collection School Of Computing and Information Systems

Data security and privacy concerns in cloud storage services compel data owners to encrypt their sensitive data before outsourcing. Standard encryption systems, however, hinder users from issuing search queries on encrypted data. Though various systems for search over encrypted data have been proposed in the literature, existing systems use different encrypted index structures to conduct search on different search query patterns and hence are not compatible with each other. In this paper, we propose a query over encrypted data system which supports expressive search query patterns, such as single/conjunctive keyword query, range query, boolean query and mixed boolean query, all …

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Doas: Efficient Data Owner Authorized Search Over Encrypted Cloud Data, Yibin Miao, Jianfeng Ma, Ximeng Liu, Zhiquan Liu, Junwei Zhang, Fushan Wei May 2018

Doas: Efficient Data Owner Authorized Search Over Encrypted Cloud Data, Yibin Miao, Jianfeng Ma, Ximeng Liu, Zhiquan Liu, Junwei Zhang, Fushan Wei

Research Collection School Of Computing and Information Systems

Data outsourcing service can shift the local data storage and maintenance to cloud service provider (CSP) to ease the burden from data owner, but it brings the data security threats as CSP is always considered to honest-but-curious. Therefore, searchable encryption (SE) technique which allows cloud clients (including data owner and data user) to securely search over ciphertext through keywords and selectively retrieve files of interest is of prime importance. However, in practice, data user’s access permission always dynamically varies with data owner’s preferences. Moreover, existing SE schemes which are based on attribute-based encryption (ABE) incur heavy computational burden through attribution …

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Learning From Mutants: Using Code Mutation To Learn And Monitor Invariants Of A Cyber-Physical System, Yuqi Chen, Christopher M. Poskitt, Jun Sun May 2018

Learning From Mutants: Using Code Mutation To Learn And Monitor Invariants Of A Cyber-Physical System, Yuqi Chen, Christopher M. Poskitt, Jun Sun

Research Collection School Of Computing and Information Systems

Cyber-physical systems (CPS) consist of sensors, actuators, and controllers all communicating over a network; if any subset becomes compromised, an attacker could cause significant damage. With access to data logs and a model of the CPS, the physical effects of an attack could potentially be detected before any damage is done. Manually building a model that is accurate enough in practice, however, is extremely difficult. In this paper, we propose a novel approach for constructing models of CPS automatically, by applying supervised machine learning to data traces obtained after systematically seeding their software components with faults ("mutants"). We demonstrate the …

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Deeprefiner: Multi-Layer Android Malware Detection System Applying Deep Neural Networks, Xu Ke, Yingjiu Li, Robert H. Deng, Kai Chen Apr 2018

Deeprefiner: Multi-Layer Android Malware Detection System Applying Deep Neural Networks, Xu Ke, Yingjiu Li, Robert H. Deng, Kai Chen

Research Collection School Of Computing and Information Systems

As malicious behaviors vary significantly across mobile malware, it is challenging to detect malware both efficiently and effectively. Also due to the continuous evolution of malicious behaviors, it is difficult to extract features by laborious human feature engineering and keep up with the speed of malware evolution. To solve these challenges, we propose DeepRefiner to identify malware both efficiently and effectively. The novel technique enabling effectiveness is the semantic-based deep learning. We use Long Short Term Memory on the semantic structure of Android bytecode, avoiding missing the details of method-level bytecode semantics. To achieve efficiency, we apply Multilayer Perceptron on …

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Sok: Towards The Science Of Security And Privacy In Machine Learning, Nicolas Papernot, Patrick Mcdaniel, Arunesh Sinha, Michael Wellman Apr 2018

Sok: Towards The Science Of Security And Privacy In Machine Learning, Nicolas Papernot, Patrick Mcdaniel, Arunesh Sinha, Michael Wellman

Research Collection School Of Computing and Information Systems

Advances in machine learning (ML) in recent years have enabled a dizzying array of applications such as data analytics, autonomous systems, and security diagnostics. ML is now pervasive—new systems and models are being deployed in every domain imaginable, leading to rapid and widespread deployment of software based inference and decision making. There is growing recognition that ML exposes new vulnerabilities in software systems, yet the technical community’s understanding of the nature and extent of these vulnerabilities remains limited. We systematize recent findings on ML security and privacy, focusing on attacks identified on these systems and defenses crafted to date. We …

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Modeling Security And Privacy Requirements: A Use Case-Driven Approach, Phu Xuan Mai, Arda Goknil, Lwin Khin Shar, Fabrizio Pastore, Lionel Briand, Shaban Shaame Apr 2018

Modeling Security And Privacy Requirements: A Use Case-Driven Approach, Phu Xuan Mai, Arda Goknil, Lwin Khin Shar, Fabrizio Pastore, Lionel Briand, Shaban Shaame

Research Collection School Of Computing and Information Systems

Context: Modern internet-based services, ranging from food-delivery to home-caring, leverage the availability of multiple programmable devices to provide handy services tailored to end-user needs. These services are delivered through an ecosystem of device-specific software components and interfaces (e.g., mobile and wearable device applications). Since they often handle private information (e.g., location and health status), their security and privacy requirements are of crucial importance. Defining and analyzing those requirements is a significant challenge due to the multiple types of software components and devices integrated into software ecosystems. Each software component presents peculiarities that often depend on the context and the devices …

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Empirical Study Of Face Authentication Systems Under Osnfd Attacks, Yan Li, Yingjiu Li, Xu, Ke, Qiang Yan, Robert H. Deng Apr 2018

Empirical Study Of Face Authentication Systems Under Osnfd Attacks, Yan Li, Yingjiu Li, Xu, Ke, Qiang Yan, Robert H. Deng

Research Collection School Of Computing and Information Systems

Face authentication has been widely available on smartphones, tablets, and laptops. As numerous personal images are published in online social networks (OSNs), OSN-based facial disclosure (OSNFD) creates significant threat against face authentication. We make the first attempt to quantitatively measure OSNFD threat to real-world face authentication systems on smartphones, tablets, and laptops. Our results show that the percentage of vulnerable users that are subject to spoofing attacks is high, which is about 64% for laptop users, and 93% smartphone/tablet users. We investigate liveness detection methods in the real-world face authentication systems against OSNFD threat. We discover that under protection of …

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Regularly Lossy Functions And Applications, Yu Chen, Baodong Qin, Haiyang Xue Apr 2018

Regularly Lossy Functions And Applications, Yu Chen, Baodong Qin, Haiyang Xue

Research Collection School Of Computing and Information Systems

In STOC 2008, Peikert and Waters introduced a powerful primitive called lossy trapdoor functions (LTFs). In a nutshell, LTFs are functions that behave in one of two modes. In the normal mode, functions are injective and invertible with a trapdoor. In the lossy mode, functions statistically lose information about their inputs. Moreover, the two modes are computationally indistinguishable. In this work, we put forward a relaxation of LTFs, namely, regularly lossy functions (RLFs). Compared to LTFs, the functions in the normal mode are not required to be efficiently invertible or even unnecessary to be injective. Instead, they could also be …

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Criteria-Based Encryption, Tran Viet Xuan Phuong, Guomin Yang, Willy Susilo Apr 2018

Criteria-Based Encryption, Tran Viet Xuan Phuong, Guomin Yang, Willy Susilo

Research Collection School Of Computing and Information Systems

We present a new type of public-key encryption called Criteria-based Encryption (or , for short). Different from Attribute-based Encryption, in , we consider the access policies as criteria carrying different weights. A user must hold some cases (or answers) satisfying the criteria and have sufficient weights in order to successfully decrypt a message. We then propose two Schemes under different settings: the first scheme requires a user to have at least one case for a criterion specified by the encryptor in the access structure, while the second scheme requires a user to have all the cases for each criterion. We …

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Every Step You Take, I’Ll Be Watching You: Practical Stepauth-Entication Of Rfid Paths, Kai Bu, Yingjiu Li Apr 2018

Every Step You Take, I’Ll Be Watching You: Practical Stepauth-Entication Of Rfid Paths, Kai Bu, Yingjiu Li

Research Collection School Of Computing and Information Systems

Path authentication thwarts counterfeits in RFID-based supply chains. Its motivation is that tagged products taking invalid paths are likely faked and injected by adversaries at certain supply chain partners/steps. Existing solutions are path-grained in that they simply regard a product as genuine if it takes any valid path. Furthermore, they enforce distributed authentication by offloading the sets of valid paths to some or all steps from a centralized issuer. This not only imposes network and storage overhead but also leaks transaction privacy. We present StepAuth, the first step-grained path authentication protocol that is practically efficient for authenticating products with strict …

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Vmkdo: Verifiable Multi-Keyword Search Over Encrypted Cloud Data For Dynamic Data-Owner, Yibin Miao, Jianfeng Ma, Ximeng Liu, Zhiquan Liu, Limin Shen, Fushan Wei Mar 2018

Vmkdo: Verifiable Multi-Keyword Search Over Encrypted Cloud Data For Dynamic Data-Owner, Yibin Miao, Jianfeng Ma, Ximeng Liu, Zhiquan Liu, Limin Shen, Fushan Wei

Research Collection School Of Computing and Information Systems

The advantages of cloud computing encourage individuals and enterprises to outsource their local data storage and computation to cloud server, however, data security and privacy concerns seriously hinder the practicability of cloud storage. Although searchable encryption (SE) technique enables cloud server to provide fundamental encrypted data retrieval services for data-owners, equipping with a result verification mechanism is still of prime importance in practice as semi-trusted cloud server may return incorrect search results. Besides, single keyword search inevitably incurs many irrelevant results which result in waste of bandwidth and computation resources. In this paper, we are among the first to tackle …

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An Efficient And Expressive Ciphertext-Policy Attribute-Based Encryption Scheme With Partially Hidden Access Structures, Revisited, Hui Cui, Robert H. Deng, Junzuo Lai, Xun Yi, Surya Nepal Mar 2018

An Efficient And Expressive Ciphertext-Policy Attribute-Based Encryption Scheme With Partially Hidden Access Structures, Revisited, Hui Cui, Robert H. Deng, Junzuo Lai, Xun Yi, Surya Nepal

Research Collection School Of Computing and Information Systems

Ciphertext-policy attribute-based encryption (CP-ABE) has been regarded as one of the promising solutions to protect data security and privacy in cloud storage services. In a CP-ABE scheme, an access structure is included in the ciphertext, which, however, may leak sensitive information about the underlying plaintext and the privileged recipients in that anyone who sees the ciphertext is able to learn the attributes of the privileged recipients from the associated access structure. In order to address this issue, CP-ABE with partially hidden access structures was introduced where each attribute is divided into an attribute name and an attribute value and the …

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Obfuscation At-Source: Privacy In Context-Aware Mobile Crowd-Sourcing, Thivya Kandappu, Archan Misra, Shih-Fen Cheng, Randy Tandriansyah, Hoong Chuin Lau Mar 2018

Obfuscation At-Source: Privacy In Context-Aware Mobile Crowd-Sourcing, Thivya Kandappu, Archan Misra, Shih-Fen Cheng, Randy Tandriansyah, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

By effectively reaching out to and engaging larger population of mobile users, mobile crowd-sourcing has become a strategy to perform large amount of urban tasks. The recent empirical studies have shown that compared to the pull-based approach, which expects the users to browse through the list of tasks to perform, the push-based approach that actively recommends tasks can greatly improve the overall system performance. As the efficiency of the push-based approach is achieved by incorporating worker's mobility traces, privacy is naturally a concern. In this paper, we propose a novel, 2-stage and user-controlled obfuscation technique that provides a trade off-amenable …

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Sclib: A Practical And Lightweight Defense Against Component Hijacking In Android Applications, Daoyuan Wu, Yao Cheng, Debin Gao, Yingjiu Li, Robert H. Deng Mar 2018

Sclib: A Practical And Lightweight Defense Against Component Hijacking In Android Applications, Daoyuan Wu, Yao Cheng, Debin Gao, Yingjiu Li, Robert H. Deng

Research Collection School Of Computing and Information Systems

Cross-app collaboration via inter-component communication is a fundamental mechanism on Android. Although it brings the benefits such as functionality reuse and data sharing, a threat called component hijacking is also introduced. By hijacking a vulnerable component in victim apps, an attack app can escalate its privilege for operations originally prohibited. Many prior studies have been performed to understand and mitigate this issue, but no defense is being deployed in the wild, largely due to the deployment difficulties and performance concerns. In this paper we present SCLib, a secure component library that performs in-app mandatory access control on behalf of app …

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Mining Sandboxes: Are We There Yet?, Lingfeng Bao, Tien Duy B. Le, David Lo Mar 2018

Mining Sandboxes: Are We There Yet?, Lingfeng Bao, Tien Duy B. Le, David Lo

Research Collection School Of Computing and Information Systems

The popularity of Android platform on mobile devices has attracted much attention from many developers and researchers, as well as malware writers. Recently, Jamrozik et al. proposed a technique to secure Android applications referred to as mining sandboxes. They used an automated test case generation technique to explore the behavior of the app under test and then extracted a set of sensitive APIs that were called. Based on the extracted sensitive APIs, they built a sandbox that can block access to APIs not used during testing. However, they only evaluated the proposed technique with benign apps but not investigated whether …

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Urlnet: Learning A Url Representation With Deep Learning For Malicious Url Detection, Hung Le, Hong Quang Pham, Doyen Sahoo, Steven C. H. Hoi Mar 2018

Urlnet: Learning A Url Representation With Deep Learning For Malicious Url Detection, Hung Le, Hong Quang Pham, Doyen Sahoo, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Malicious URLs host unsolicited content and are used to perpetrate cybercrimes. It is imperative to detect them in a timely manner. Traditionally, this is done through the usage of blacklists, which cannot be exhaustive, and cannot detect newly generated malicious URLs. To address this, recent years have witnessed several efforts to perform Malicious URL Detection using Machine Learning. The most popular and scalable approaches use lexical properties of the URL string by extracting Bag-of-words like features, followed by applying machine learning models such as SVMs. There are also other features designed by experts to improve the prediction performance of the …

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An Efficient And Expressive Ciphertext-Policy Attribute-Based Encryption Scheme With Partially Hidden Access Structures, Revisited, Hui Cui, Robert H. Deng, Junzuo Lai, Xun Yi, Surya Nepal Mar 2018

An Efficient And Expressive Ciphertext-Policy Attribute-Based Encryption Scheme With Partially Hidden Access Structures, Revisited, Hui Cui, Robert H. Deng, Junzuo Lai, Xun Yi, Surya Nepal

Research Collection School Of Computing and Information Systems

Ciphertext-policy attribute-based encryption (CP-ABE) has been regarded as one of the promising solutions to protect data security and privacy in cloud storage services. In a CP-ABE scheme, an access structure is included in the ciphertext, which, however, may leak sensitive information about the underlying plaintext and the privileged recipients in that anyone who sees the ciphertext is able to learn the attributes of the privileged recipients from the associated access structure. In order to address this issue, CP-ABE with partially hidden access structures was introduced where each attribute is divided into an attribute name and an attribute value and the …

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An Efficient And Privacy-Preserving Biometric Identification Scheme In Cloud Computing, Liehuang Zhu, Chuan Zhang, Chang Xu, Ximeng Liu, Cheng Huang Mar 2018

An Efficient And Privacy-Preserving Biometric Identification Scheme In Cloud Computing, Liehuang Zhu, Chuan Zhang, Chang Xu, Ximeng Liu, Cheng Huang

Research Collection School Of Computing and Information Systems

Biometric identification has become increasingly popular in recent years.With the development of cloud computing, database owners are motivated to outsource the large size of biometric data and identification tasks to the cloud to get rid of the expensive storage and computation costs, which, however, brings potential threats to users’ privacy. In this paper, we propose an efficient and privacy-preserving biometric identification outsourcing scheme. Specifically, the biometric: To execute a biometric identification, the database owner encrypts the query data and submits it to the cloud. The cloud performs identification operations over the encrypted database and returns the result to the database …

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Constant-Size Ciphertexts In Threshold Attribute-Based Encryption Without Dummy Attributes, Willy Susilo, Guomin Yang, Fuchun Guo, Qiong Huang Mar 2018

Constant-Size Ciphertexts In Threshold Attribute-Based Encryption Without Dummy Attributes, Willy Susilo, Guomin Yang, Fuchun Guo, Qiong Huang

Research Collection School Of Computing and Information Systems

Attribute-based encryption (ABE) is an augmentation of public key encryption that allows users to encrypt and decrypt messages based on users' attributes. In a (t, s) threshold ABE, users who can decrypt a ciphertext must hold at least t attributes among the s attributes specified by the encryptor. At PKC 2010, Herranz, Laguillaumie and Raft& proposed the first threshold ABE with constant-size ciphertexts. In order to ensure the encryptor can flexibly select the attribute set and a threshold value, they use dummy attributes to satisfy the decryption requirement. The advantage of their scheme is that any addition or removal of …

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Long Term Key Management Architecture For Scada Systems, Hendra Saputra, Zhigang Zhao Feb 2018

Long Term Key Management Architecture For Scada Systems, Hendra Saputra, Zhigang Zhao

Research Collection School Of Computing and Information Systems

A SCADA key management is required to provide a key management protocol that will be used to secure the communication channel of the SCADA entities. The SCADA key management scheme often uses symmetric cryptography due to resource constraints of the SCADA entities. Normally the use of symmetric cryptography mechanism is in the form of pre-shared keys, which are installed manually and are fixed. Then, these pre-shared keys or long term keys are used to generate session keys. However, it is important that these long term keys can be updated and refreshed dynamically. With the nature of SCADA systems which may …

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Attribute-Based Cloud Storage With Secure Provenance Over Encrypted Data, Hui Cui, Robert H. Deng, Yingjiu Li Feb 2018

Attribute-Based Cloud Storage With Secure Provenance Over Encrypted Data, Hui Cui, Robert H. Deng, Yingjiu Li

Research Collection School Of Computing and Information Systems

To securely and conveniently enjoy the benefits of cloud storage, it is desirable to design a cloud data storage system which protects data privacy from storage servers through encryption, allows fine-grained access control such that data providers can expressively specify who are eligible to access the encrypted data, enables dynamic user management such that the total number of data users is unbounded and user revocation can be carried out conveniently, supports data provider anonymity and traceability such that a data provider’s identity is not disclosed to data users in normal circumstances but can be traced by a trusted authority if …

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Secure Fine-Grained Access Control And Data Sharing For Dynamic Groups In The Cloud, Shengmin Xu, Guomin Yang, Yi Mu, Robert H. Deng Feb 2018

Secure Fine-Grained Access Control And Data Sharing For Dynamic Groups In The Cloud, Shengmin Xu, Guomin Yang, Yi Mu, Robert H. Deng

Research Collection School Of Computing and Information Systems

Cloud computing is an emerging computing paradigm that enables users to store their data in a cloud server to enjoy scalable and on-demand services. Nevertheless, it also brings many security issues, since cloud service providers (CSPs) are not in the same trusted domain as users. To protect data privacy against untrusted CSPs, existing solutions apply cryptographic methods (e.g., encryption mechanisms) and provide decryption keys only to authorized users. However, sharing cloud data among authorized users at a fine-grained level is still a challenging issue, especially when dealing with dynamic user groups. In this paper, we propose a secure and efficient …

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Consortium Blockchain-Based Sift: Outsourcing Encrypted Feature Extraction In The D2d Network, Xiaoqin Feng, Jianfeng Ma, Tao Feng, Yinbin Miao, Ximeng Liu Jan 2018

Consortium Blockchain-Based Sift: Outsourcing Encrypted Feature Extraction In The D2d Network, Xiaoqin Feng, Jianfeng Ma, Tao Feng, Yinbin Miao, Ximeng Liu

Research Collection School Of Computing and Information Systems

Privacy-preserving outsourcing algorithms for feature extraction not only reduce users' storage and computation overhead but also preserve the image privacy. However, the existing schemes still suffer from deficiencies induced by security, applications, efficiency and storage. To solve the problems, we implement a consortium chain-based outsourcing feature extraction scheme over encrypted images by using the smart contract, distributed autonomous corporation (DAC), sharding technique, and device to device (D2D) communication, which is secure, widely applied, highly efficient, and has less storage overhead. First, the effectiveness, security, and performance of our scheme are analyzed. Then, the efficiency and storage overhead of our scheme …

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Secure Smart Metering Based On Lora Technology, Yao Cheng, Hendra Saputra, Leng Meng Goh, Yongdong Wu Jan 2018

Secure Smart Metering Based On Lora Technology, Yao Cheng, Hendra Saputra, Leng Meng Goh, Yongdong Wu

Research Collection School Of Computing and Information Systems

Smart metering allows Substation Automation System (SAS) to remotely and timely read smart meters. Despite its advantages, smart metering brings some challenges. a) It introduces cyber attack risks to the metering system, which may lead to user privacy leakage or even the compromise of smart metering systems. b) Although the majority of meters are located within a regional power supply area, some hard-to-reach nodes are geographically far from the clustered area, which account for a big portion of the entire smart metering operation cost. Facing the above challenges, we propose a secure smart metering infrastructure based on LoRa technology which …

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Securing Display Path For Security-Sensitive Applications On Mobile Devices, Jinhua Cui, Yuanyuan Zhang, Zhiping Cai, Anfeng Liu, Yangyang Li Jan 2018

Securing Display Path For Security-Sensitive Applications On Mobile Devices, Jinhua Cui, Yuanyuan Zhang, Zhiping Cai, Anfeng Liu, Yangyang Li

Research Collection School Of Computing and Information Systems

While smart devices based on ARM processor bring us a lot of convenience, they also become an attractive target of cyber-attacks. The threat is exaggerated as commodity OSes usually have a large code base and suffer from various software vulnerabilities. Nowadays, adversaries prefer to steal sensitive data by leaking the content of display output by a security-sensitive application. A promising solution is to exploit the hardware visualization extensions provided by modern ARM processors to construct a secure display path between the applications and the display device. In this work, we present a scheme named SecDisplay for trusted display service, it …

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Hybrid Privacy-Preserving Clinical Decision Support System In Fog-Cloud Computing, Ximeng Liu, Robert H. Deng, Yang Yang, Ngoc Hieu Tran, Shangping Zhong Jan 2018

Hybrid Privacy-Preserving Clinical Decision Support System In Fog-Cloud Computing, Ximeng Liu, Robert H. Deng, Yang Yang, Ngoc Hieu Tran, Shangping Zhong

Research Collection School Of Computing and Information Systems

In this paper, we propose a framework for hybrid privacy-preserving clinical decision support system in fog cloud computing, called HPCS. In HPCS, a fog server uses a lightweight data mining method to securely monitor patients' health condition in real-time. The newly detected abnormal symptoms can be further sent to the cloud server for high-accuracy prediction in a privacy-preserving way. Specifically, for the fog servers, we design a new secure outsourced inner-product protocol for achieving secure lightweight single-layer neural network. Also, a privacy-preserving piecewise polynomial calculation protocol allows cloud server to securely perform any activation functions in multiple-layer neural network. Moreover, …

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Tinyvisor: An Extensible Secure Framework On Android Platforms, Dong Shen, Zhoujun Li, Xiaojing Su, Jinxin Ma, Deng, Robert H. Jan 2018

Tinyvisor: An Extensible Secure Framework On Android Platforms, Dong Shen, Zhoujun Li, Xiaojing Su, Jinxin Ma, Deng, Robert H.

Research Collection School Of Computing and Information Systems

As the utilization of mobile platform keeps growing, the security issue of mobile platform becomes a serious threat to user privacy. The current security measures mainly focus on the application level and the framework level, with little protection on the kernel. Virtualization technologies have been used in x86 platforms to protect the security of the kernel. With a higher privilege than the guest operating system, the hypervisor can effectively detect and defend against the malicious activity inside the guest kernel. In this paper, we build a hypervisor framework called TinyVisor leveraging the ARM virtualization extensions to protect the guest system …

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Improved Construction For Inner Product Functional Encryption, Qingsong Zhao, Qingkai Zeng, Ximeng Liu Jan 2018

Improved Construction For Inner Product Functional Encryption, Qingsong Zhao, Qingkai Zeng, Ximeng Liu

Research Collection School Of Computing and Information Systems

Functional encryption (FE) is a vast new paradigm for encryption scheme which allows tremendous flexibility in accessing encrypted data. In a FE scheme, a user can learn specific function of encrypted messages by restricted functional key and reveals nothing else about the messages. Besides the standard notion of data privacy in FE, it should protect the privacy of the function itself which is also crucial for practical applications. In this paper, we construct a secret key FE scheme for the inner product functionality using asymmetric bilinear pairing groups of prime order. Compared with the existing similar schemes, our construction reduces …

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Strong Identity-Based Proxy Signature Schemes, Revisited, Weiwei Liu, Yi Mu, Guomin Yang, Yangguang Tian Jan 2018

Strong Identity-Based Proxy Signature Schemes, Revisited, Weiwei Liu, Yi Mu, Guomin Yang, Yangguang Tian

Research Collection School Of Computing and Information Systems

Proxy signature is a useful cryptographic primitive that has been widely used in many applications. It has attracted a lot of attention since it was introduced. There have been lots of works in constructing efficient and secure proxy signature schemes. In this paper, we identify a new attack that has been neglected by many existing proven secure proxy signature schemes. We demonstrate this attack by launching it against an identity-based proxy signature scheme which is proven secure. We then propose one method that can effectively prevent this attack. The weakness in some other proxy signature schemes can also be fixed …

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