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Full-Text Articles in Information Security
Privacy-Preserving Bloom Filter-Based Keyword Search Over Large Encrypted Cloud Data, Yanrong Liang, Jianfeng Ma, Yinbin Miao, Da Kuang, Xiangdong Meng, Robert H. Deng
Privacy-Preserving Bloom Filter-Based Keyword Search Over Large Encrypted Cloud Data, Yanrong Liang, Jianfeng Ma, Yinbin Miao, Da Kuang, Xiangdong Meng, Robert H. Deng
Research Collection School Of Computing and Information Systems
To achieve the search over encrypted data in cloud server, Searchable Encryption (SE) has attracted extensive attention from both academic and industrial fields. The existing Bloom filter-based SE schemes can achieve similarity search, but will generally incur high false positive rates, and even leak the privacy of values in Bloom filters (BF). To solve the above problems, we first propose a basic Privacy-preserving Bloom filter-based Keyword Search scheme using the Circular Shift and Coalesce-Bloom Filter (CSC-BF) and Symmetric-key Hidden Vector Encryption (SHVE) technology (namely PBKS), which can achieve effective search while protecting the values in BFs. Then, we design a …
Reks: Role-Based Encrypted Keyword Search With Enhanced Access Control For Outsourced Cloud Data, Yibin Miao, Feng Li, Xiaohua Jia, Huaxiong Wang, Ximeng Liu, Kim-Kwang Raymond Choo, Robert H. Deng
Reks: Role-Based Encrypted Keyword Search With Enhanced Access Control For Outsourced Cloud Data, Yibin Miao, Feng Li, Xiaohua Jia, Huaxiong Wang, Ximeng Liu, Kim-Kwang Raymond Choo, Robert H. Deng
Research Collection School Of Computing and Information Systems
Keyword-based search over encrypted data is an important technique to achieve both data confidentiality and utilization in cloud outsourcing services. While commonly used access control mechanisms, such as identity-based encryption and attribute-based encryption, do not generally scale well for hierarchical access permissions. To solve this problem, we propose a Role-based Encrypted Keyword Search (REKS) scheme by using the role-based access control and broadcast encryption. Specifically, REKS allows owners to deploy hierarchical access control by allowing users with parent roles to have access permissions from child roles. Using REKS, we further facilitate token generation preprocessing and efficient user management, thereby significantly …
Formal Modeling And Verification Of A Blockchain-Based Crowdsourcing Consensus Protocol, Hamra Afzaal, Muhammad Imran, Muhammad Umar Janjua, Sarada Prasad Gochhayat
Formal Modeling And Verification Of A Blockchain-Based Crowdsourcing Consensus Protocol, Hamra Afzaal, Muhammad Imran, Muhammad Umar Janjua, Sarada Prasad Gochhayat
VMASC Publications
Crowdsourcing is an effective technique that allows humans to solve complex problems that are hard to accomplish by automated tools. Some significant challenges in crowdsourcing systems include avoiding security attacks, effective trust management, and ensuring the system’s correctness. Blockchain is a promising technology that can be efficiently exploited to address security and trust issues. The consensus protocol is a core component of a blockchain network through which all the blockchain peers achieve an agreement about the state of the distributed ledger. Therefore, its security, trustworthiness, and correctness have vital importance. This work proposes a Secure and Trustworthy Blockchain-based Crowdsourcing (STBC) …
Breathprint: Breathing Acoustics-Based User Authentication, Jagmohan Chauhan, Yining Hu, Suranga Sereviratne, Archan Misra, Aruna Sereviratne, Youngki Lee
Breathprint: Breathing Acoustics-Based User Authentication, Jagmohan Chauhan, Yining Hu, Suranga Sereviratne, Archan Misra, Aruna Sereviratne, Youngki Lee
Research Collection School Of Computing and Information Systems
We propose BreathPrint, a new behavioural biometric signature based on audio features derived from an individual's commonplace breathing gestures. Specifically, BreathPrint uses the audio signatures associated with the three individual gestures: sniff, normal, and deep breathing, which are sufficiently different across individuals. Using these three breathing gestures, we develop the processing pipeline that identifies users via the microphone sensor on smartphones and wearable devices. In BreathPrint, a user performs breathing gestures while holding the device very close to their nose. Using off-the-shelf hardware, we experimentally evaluate the BreathPrint prototype with 10 users, observed over seven days. We show that users …
A System For Detecting Malicious Insider Data Theft In Iaas Cloud Environments, Jason Nikolai, Yong Wang
A System For Detecting Malicious Insider Data Theft In Iaas Cloud Environments, Jason Nikolai, Yong Wang
Research & Publications
The Cloud Security Alliance lists data theft and insider attacks as critical threats to cloud security. Our work puts forth an approach using a train, monitor, detect pattern which leverages a stateful rule based k-nearest neighbors anomaly detection technique and system state data to detect inside attacker data theft on Infrastructure as a Service (IaaS) nodes. We posit, instantiate, and demonstrate our approach using the Eucalyptus cloud computing infrastructure where we observe a 100 percent detection rate for abnormal login events and data copies to outside systems.
On Robust Image Spam Filtering Via Comprehensive Visual Modeling, Jialie Shen, Deng, Robert H., Zhiyong Cheng, Liqiang Nie, Shuicheng Yan
On Robust Image Spam Filtering Via Comprehensive Visual Modeling, Jialie Shen, Deng, Robert H., Zhiyong Cheng, Liqiang Nie, Shuicheng Yan
Research Collection School Of Computing and Information Systems
The Internet has brought about fundamental changes in the way peoples generate and exchange media information. Over the last decade, unsolicited message images (image spams) have become one of the most serious problems for Internet service providers (ISPs), business firms and general end users. In this paper, we report a novel system called RoBoTs (Robust BoosTrap based spam detector) to support accurate and robust image spam filtering. The system is developed based on multiple visual properties extracted from different levels of granularity, aiming to capture more discriminative contents for effective spam image identification. In addition, a resampling based learning framework …