Loading...
Search for:
cloud-security
0.005 seconds
A key-policy attribute-based temporary keyword search scheme for secure cloud storage
, Article IEEE Transactions on Cloud Computing ; 2018 ; 21687161 (ISSN) ; Delavar, M ; Mohajeri, J ; Salmasizadeh, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2018
Abstract
Temporary keyword search on confidential data in a cloud environment is the main focus of this research. The cloud providers are not fully trusted. So, it is necessary to outsource data in the encrypted form. In the attribute-based keyword search (ABKS) schemes, the authorized users can generate some search tokens and send them to the cloud for running the search operation. These search tokens can be used to extract all the ciphertexts which are produced at any time and contain the corresponding keyword. Since this may lead to some information leakage, it is more secure to propose a scheme in which the search tokens can only extract the ciphertexts generated in a specified time interval. To...
Processing Queries with Mathematical Expressions on Encrypted Outsourced Databases
, M.Sc. Thesis Sharif University of Technology ; Jalil, Rasool (Supervisor)
Abstract
The ever-increasing volume of data and the lack of computational and storage facilities have caused a managerial challenge to organizations. The existence of these challenges on the one hand and the increase of storage services on the other hand have compelled the organizations to delegate their storage and management of data to the server providers of cloud storage services. The outsourcing of data to servers obviates the need for purchasing exorbitant storage equipment and recruiting professional workforce in the organization. Since the organization’s data will be kept outside the organization’s ambience in case of using such services in form of outsourcing, and the data will not be under...
Distributed Anomaly Detection on the IoT Edge
, M.Sc. Thesis Sharif University of Technology ; Amini, Morteza (Supervisor)
Abstract
With the growing trend of IoT, especially in critical areas like health system and city management, and the expectations of even higher growth with the advent of 5G networks, the security and preserving of users' privacy in IoT has gained significant importance. Anomaly detection is one of the approaches to monitor IoT devices which enables the identification of anomalous behaviors. This anomalous behavior could indicate malware infection, physical malfunctions, or tampering.Deep learning has been a common approach for anomaly detection for the past few years. The solutions are mostly suggested in a special purpose manner and because they are based on a particular deep learning model, they...
Encryption Aware Query Processing for Data Outsourcing
, Ph.D. Dissertation Sharif University of Technology ; Jalili, Rasool (Supervisor)
Abstract
Data outsourcing provides cost-saving and availability guarantees. However, privacy and confidentiality issues, disappoint owners from outsourcing their data. Although solutions such as CryptDB and SDB tried to provide secure and practical systems, their enforced limitations, made them useless in practice. Inability in search on encrypted data, is one of the most important existing challenges in such systems. Furthermore, the overhead of mechanisms such as FHEs, removes them from considering for any practical system. Indeed, special purpose encryptions would be the only usable mechanisms for such purposes. However, their limited functionality does not support some important required...
A Key-Policy Attribute-Based Temporary Keyword Search scheme for Secure Cloud Storage
, Article IEEE Transactions on Cloud Computing ; Volume 8, Issue 3 , 2020 , Pages 660-671 ; Delavar, M ; Mohajeri, J ; Salmasizadeh, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2020
Abstract
Temporary keyword search on confidential data in a cloud environment is the main focus of this research. The cloud providers are not fully trusted. So, it is necessary to outsource data in the encrypted form. In the attribute-based keyword search (ABKS) schemes, the authorized users can generate some search tokens and send them to the cloud for running the search operation. These search tokens can be used to extract all the ciphertexts which are produced at any time and contain the corresponding keyword. Since this may lead to some information leakage, it is more secure to propose a scheme in which the search tokens can only extract the ciphertexts generated in a specified time interval. To...
Security enhancement of an auditing scheme for shared cloud data
, Article International Journal of Internet Protocol Technology ; Volume 15, Issue 1 , 2022 , Pages 60-68 ; 17438209 (ISSN) ; Attari, M. A ; Asaar, M. R ; Aref, M. R ; Sharif University of Technology
Inderscience Publishers
2022
Abstract
In cloud storage services, public auditing mechanisms allow a third party to verify integrity of the outsourced data on behalf of data owners without the need to retrieve data from the cloud server. In some applications, the identity of data users should be kept private from the third party auditor. Oruta is a privacy preserving public auditing scheme for shared data in the cloud which exploits ring signatures to protect the identity privacy. In this paper, we propose two attacks and demonstrate that the scheme is insecure and a dishonest server can arbitrarily tamper the outsourced data without being detected by the auditor. We also propose a solution to remedy this weakness with the...
A hybrid heuristics artificial intelligence feature selection for intrusion detection classifiers in cloud of things
, Article Cluster Computing ; 2022 ; 13867857 (ISSN) ; Javadpour, A ; Ja’fari, F ; Pinto, P ; Zhang, W ; Balasubramanian, S ; Sharif University of Technology
Springer
2022
Abstract
Cloud computing environments provide users with Internet-based services and one of their main challenges is security issues. Hence, using Intrusion Detection Systems (IDSs) as a defensive strategy in such environments is essential. Multiple parameters are used to evaluate the IDSs, the most important aspect of which is the feature selection method used for classifying the malicious and legitimate activities. We have organized this research to determine an effective feature selection method to increase the accuracy of the classifiers in detecting intrusion. A Hybrid Ant-Bee Colony Optimization (HABCO) method is proposed to convert the feature selection problem into an optimization problem. We...