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2020-07-13
ahmad, sahan, Zobaed, SM, Gottumukkala, Raju, Salehi, Mohsen Amini.  2019.  Edge Computing for User-Centric Secure Search on Cloud-Based Encrypted Big Data. 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). :662–669.

Cloud service providers offer a low-cost and convenient solution to host unstructured data. However, cloud services act as third-party solutions and do not provide control of the data to users. This has raised security and privacy concerns for many organizations (users) with sensitive data to utilize cloud-based solutions. User-side encryption can potentially address these concerns by establishing user-centric cloud services and granting data control to the user. Nonetheless, user-side encryption limits the ability to process (e.g., search) encrypted data on the cloud. Accordingly, in this research, we provide a framework that enables processing (in particular, searching) of encrypted multiorganizational (i.e., multi-source) big data without revealing the data to cloud provider. Our framework leverages locality feature of edge computing to offer a user-centric search ability in a realtime manner. In particular, the edge system intelligently predicts the user's search pattern and prunes the multi-source big data search space to reduce the search time. The pruning system is based on efficient sampling from the clustered big dataset on the cloud. For each cluster, the pruning system dynamically samples appropriate number of terms based on the user's search tendency, so that the cluster is optimally represented. We developed a prototype of a user-centric search system and evaluated it against multiple datasets. Experimental results demonstrate 27% improvement in the pruning quality and search accuracy.

2020-01-07
Hammami, Hamza, Brahmi, Hanen, Ben Yahia, Sadok.  2018.  Secured Outsourcing towards a Cloud Computing Environment Based on DNA Cryptography. 2018 International Conference on Information Networking (ICOIN). :31-36.

Cloud computing denotes an IT infrastructure where data and software are stored and processed remotely in a data center of a cloud provider, which are accessible via an Internet service. This new paradigm is increasingly reaching the ears of companies and has revolutionized the marketplace of today owing to several factors, in particular its cost-effective architectures covering transmission, storage and intensive data computing. However, like any new technology, the cloud computing technology brings new problems of security, which represents the main restrain on turning to this paradigm. For this reason, users are reluctant to resort to the cloud because of security and protection of private data as well as lack of trust in cloud service providers. The work in this paper allows the readers to familiarize themselves with the field of security in the cloud computing paradigm while suggesting our contribution in this context. The security schema we propose allowing a distant user to ensure a completely secure migration of all their data anywhere in the cloud through DNA cryptography. Carried out experiments showed that our security solution outperforms its competitors in terms of integrity and confidentiality of data.

2018-02-21
Schiefer, G., Gabel, M., Mechler, J., Schoknecht, A., Citak, M..  2017.  Security in a Distributed Key Management Approach. 2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS). :816–821.

Cloud computing offers many advantages as flexibility or resource efficiency and can significantly reduce costs. However, when sensitive data is outsourced to a cloud provider, classified records can leak. To protect data owners and application providers from a privacy breach data must be encrypted before it is uploaded. In this work, we present a distributed key management scheme that handles user-specific keys in a single-tenant scenario. The underlying database is encrypted and the secret key is split into parts and only reconstructed temporarily in memory. Our scheme distributes shares of the key to the different entities. We address bootstrapping, key recovery, the adversary model and the resulting security guarantees.

2018-02-02
Ghosh, U., Chatterjee, P., Tosh, D., Shetty, S., Xiong, K., Kamhoua, C..  2017.  An SDN Based Framework for Guaranteeing Security and Performance in Information-Centric Cloud Networks. 2017 IEEE 10th International Conference on Cloud Computing (CLOUD). :749–752.

Cloud data centers are critical infrastructures to deliver cloud services. Although security and performance of cloud data centers have been well studied in the past, their networking aspects are overlooked. Current network infrastructures in cloud data centers limit the ability of cloud provider to offer guaranteed cloud network resources to users. In order to ensure security and performance requirements as defined in the service level agreement (SLA) between cloud user and provider, cloud providers need the ability to provision network resources dynamically and on the fly. The main challenge for cloud provider in utilizing network resource can be addressed by provisioning virtual networks that support information centric services by separating the control plane from the cloud infrastructure. In this paper, we propose an sdn based information centric cloud framework to provision network resources in order to support elastic demands of cloud applications depending on SLA requirements. The framework decouples the control plane and data plane wherein the conceptually centralized control plane controls and manages the fully distributed data plane. It computes the path to ensure security and performance of the network. We report initial experiment on average round-trip delay between consumers and producers.

2018-01-16
He, Z., Zhang, T., Lee, R. B..  2017.  Machine Learning Based DDoS Attack Detection from Source Side in Cloud. 2017 IEEE 4th International Conference on Cyber Security and Cloud Computing (CSCloud). :114–120.

Denial of service (DOS) attacks are a serious threat to network security. These attacks are often sourced from virtual machines in the cloud, rather than from the attacker's own machine, to achieve anonymity and higher network bandwidth. Past research focused on analyzing traffic on the destination (victim's) side with predefined thresholds. These approaches have significant disadvantages. They are only passive defenses after the attack, they cannot use the outbound statistical features of attacks, and it is hard to trace back to the attacker with these approaches. In this paper, we propose a DOS attack detection system on the source side in the cloud, based on machine learning techniques. This system leverages statistical information from both the cloud server's hypervisor and the virtual machines, to prevent network packages from being sent out to the outside network. We evaluate nine machine learning algorithms and carefully compare their performance. Our experimental results show that more than 99.7% of four kinds of DOS attacks are successfully detected. Our approach does not degrade performance and can be easily extended to broader DOS attacks.

2017-12-20
Althamary, I. A., El-Alfy, E. S. M..  2017.  A more secure scheme for CAPTCHA-based authentication in cloud environment. 2017 8th International Conference on Information Technology (ICIT). :405–411.

Cloud computing is a remarkable model for permitting on-demand network access to an elastic collection of configurable adaptive resources and features including storage, software, infrastructure, and platform. However, there are major concerns about security-related issues. A very critical security function is user authentication using passwords. Although many flaws have been discovered in password-based authentication, it remains the most convenient approach that people continue to utilize. Several schemes have been proposed to strengthen its effectiveness such as salted hashes, one-time password (OTP), single-sign-on (SSO) and multi-factor authentication (MFA). This study proposes a new authentication mechanism by combining user's password and modified characters of CAPTCHA to generate a passkey. The modification of the CAPTCHA depends on a secret agreed upon between the cloud provider and the user to employ different characters for some characters in the CAPTCHA. This scheme prevents various attacks including short-password attack, dictionary attack, keylogger, phishing, and social engineering. Moreover, it can resolve the issue of password guessing and the use of a single password for different cloud providers.