4 research outputs found
A Practical Framework for Storing and Searching Encrypted Data on Cloud Storage
Security has become a significant concern with the increased popularity of
cloud storage services. It comes with the vulnerability of being accessed by
third parties. Security is one of the major hurdles in the cloud server for the
user when the user data that reside in local storage is outsourced to the
cloud. It has given rise to security concerns involved in data confidentiality
even after the deletion of data from cloud storage. Though, it raises a serious
problem when the encrypted data needs to be shared with more people than the
data owner initially designated. However, searching on encrypted data is a
fundamental issue in cloud storage. The method of searching over encrypted data
represents a significant challenge in the cloud.
Searchable encryption allows a cloud server to conduct a search over
encrypted data on behalf of the data users without learning the underlying
plaintexts. While many academic SE schemes show provable security, they usually
expose some query information, making them less practical, weak in usability,
and challenging to deploy. Also, sharing encrypted data with other authorized
users must provide each document's secret key. However, this way has many
limitations due to the difficulty of key management and distribution.
We have designed the system using the existing cryptographic approaches,
ensuring the search on encrypted data over the cloud. The primary focus of our
proposed model is to ensure user privacy and security through a less
computationally intensive, user-friendly system with a trusted third party
entity. To demonstrate our proposed model, we have implemented a web
application called CryptoSearch as an overlay system on top of a well-known
cloud storage domain. It exhibits secure search on encrypted data with no
compromise to the user-friendliness and the scheme's functional performance in
real-world applications.Comment: 146 Pages, Master's Thesis, 6 Chapters, 96 Figures, 11 Table
A Multibranch Search Tree-Based Multi-Keyword Ranked Search Scheme over Encrypted Cloud Data
In the interest of privacy concerns, cloud service users choose to encrypt their personal data before outsourcing them to cloud. However, it is difficult to achieve efficient search over encrypted cloud data. Therefore, how to design an efficient and accurate search scheme over large-scale encrypted cloud data is a challenge. In this paper, we integrate bisecting k-means algorithm and multibranch tree structure and propose the α-filtering tree search scheme based on bisecting k-means clusters. The novel index tree is built from bottom-up, and a greedy depth first algorithm is used for filtering the nonrelevant document cluster by calculating the relevance score between the filtering vector and the query vector. The α-filtering tree can improve the efficiency without the loss of search accuracy. The experiment on a real-world dataset demonstrates the effectiveness of our scheme
Exploiting Spatio-Temporal Coherence for Video Object Detection in Robotics
This paper proposes a method to enhance video object detection for indoor environments in robotics. Concretely, it exploits knowledge about the camera motion between frames to propagate previously detected objects to successive frames. The proposal is rooted in the concepts of planar homography to propose regions of interest where to find objects, and recursive Bayesian filtering to integrate observations over time. The proposal is evaluated on six virtual, indoor environments, accounting for the detection of nine object classes over a total of ∼ 7k frames. Results show that our proposal improves the recall and the F1-score by a factor of 1.41 and 1.27, respectively, as well as it achieves a significant reduction of the object categorization entropy (58.8%) when compared to a two-stage video object detection method used as baseline, at the cost of small time overheads (120 ms) and precision loss (0.92).</p
Dependable Embedded Systems
This Open Access book introduces readers to many new techniques for enhancing and optimizing reliability in embedded systems, which have emerged particularly within the last five years. This book introduces the most prominent reliability concerns from today’s points of view and roughly recapitulates the progress in the community so far. Unlike other books that focus on a single abstraction level such circuit level or system level alone, the focus of this book is to deal with the different reliability challenges across different levels starting from the physical level all the way to the system level (cross-layer approaches). The book aims at demonstrating how new hardware/software co-design solution can be proposed to ef-fectively mitigate reliability degradation such as transistor aging, processor variation, temperature effects, soft errors, etc. Provides readers with latest insights into novel, cross-layer methods and models with respect to dependability of embedded systems; Describes cross-layer approaches that can leverage reliability through techniques that are pro-actively designed with respect to techniques at other layers; Explains run-time adaptation and concepts/means of self-organization, in order to achieve error resiliency in complex, future many core systems