Aws Naser Jaber

Use of cryptography in cloud computing

Cloud computing is a platform for expanding capabilities and developing potentialities dynamically without employing new infrastructure, personnel, or software systems. In Addition, cloud computing originated from a commercial enterprise concept, and developed into a flourishing IT invention. However, given that considerable information on individuals and companies are identified in the cloud, concerns have been raised regarding the safety of the cloud environment. Despite the hype surrounding cloud computing, customers remain reluctant to deploy their commercial enterprise into the cloud. Nevertheless, lack of protection is the only major concern that hinders increased use of cloud computing. Furthermore, the complexity with which cloud computing manages data secrecy, and information security makes the market hesitant about cloud computing. The architecture of cloud models threatens the security of existing technologies when deployed in a cloud environment. Thus, users of cloud services should know the dangers of uploading data into this new environment. Therefore, in this paper different cryptography aspects that pose a threat to cloud computing are reviewed. This paper is a survey of specific security issues brought by the use of cryptography in a cloud computing system.

A study in data security in cloud computing

The vision of 21st century computing is that users can access Internet services over lightweight portable devices rather than via variants of the traditional desktop computer. Consequently, users will have no interest in large, powerful machines. How, then, will computing power be provided? The answer to this question lies in cloud computing. Cloud computing is a recent trend in IT in which computing power and knowledge are moved away from the desktop and desktop PCs into giant datacenters. In the cloud computing paradigm, applications are delivered as services over the Internet. The key driving forces behind cloud computing are the presence of broadband and wireless networking, falling storage prices, and progressive enhancements in Internet computing software packages. Cloud service shoppers can add additional capabilities at peak demand, reduce prices, experiment with new services, and remove unessential capabilities. Service suppliers can increase utilization via multiplexing and allow for larger investments in software packages and hardware.

Agent-based Big Data Analytics in retailing: A case study

The advent of social networks and the Internet of Things have created massive data sets with huge and complex structures. Thus, new technology for storage, analysis, and pattern visualization must be developed for further processing. Such data sets are appropriately termed as “Big Data.” Big data Analytics is concerned with exposing and visualizing hidden patterns, as well as with analyzing the knowledge that is produced to facilitate decision making. In retailing, analyzing the massive data generated from business transactions is crucial to enhancing the insights of vendors into consumer behaviors and purchases, thus providing them an advantage in decision making. The capability to extract value from big data is a relevant issue, but the process is difficult as the volume and velocity of data increase. As a result, traditional business intelligence methods become inadequate. Consequently, we propose an agent-based paradigm in this study to facilitate the use of Big Data Analytics in retailing. The paradigm exploits agent characteristics such as autonomy, pro-activity, and intelligence in performing data analytics processes. We also review the background of the situation and discuss the characteristics, properties, applications, and challenges of integrating Big Data with multi-agent systems in retailing.

Host Based Intrusion Detection and Prevention Model Against DDoS Attack in Cloud Computing

Cloud computing has become an innovative technology. Recent advances in hardware and software have put tremendous pressure on administrators, who manage these resources to provide an uninterrupted service. System administrators should be familiar with cloud-server monitoring and network tools. The main focus of the present research is the design of a model that prevents distributed denial-of-service attacks based on host-based intrusion detection protection systems over hypervisor environments. The prevention model uses principal component analysis and linear discriminant analysis with a hybrid, nature-inspired metaheuristic algorithm called Ant Lion optimisation for feature selection and artificial neural networks to classify and configure the cloud server. The current results represent a feasible outcome for a good intrusion detection and prevention framework for DDoS-cloud computing systems based on statistics and predicted techniques.

Data security analysis for DDoS defense of cloud based networks

Distributed computing has become an effective approach to enhance capabilities of an institution or organization and minimize requirements for additional resource. In this regard, the distributed computing helps in broadening institutes IT capabilities. One needs to note that distributed computing is now integral part of most expanding IT business sector. It is considered novel and efficient means for expanding business. As more organizations and individuals start to use the cloud to store their data and applications, significant concerns have developed to protect sensitive data from external and internal attacks over internet. Due to security concern many clients hesitate in relocating their sensitive data on the clouds, despite significant interest in cloud-based computing. Security is a significant issue, since data much of an organizations data provides a tempting target for hackers and those concerns will continue to diminish the development of distributed computing if not addressed. Therefore, this study presents a new test and insight into a honeypot. It is a device that can be classified into two types: handling and research honeypots. Handling honeypots are used to mitigate real life dangers. A research honeypot is utilized as an exploration instrument to study and distinguish the dangers on the internet. Therefore, the primary aim of this research project is to do an intensive network security analysis through a virtualized honeypot for cloud servers to tempt an attacker and provide a new means of monitoring their behavior.

Efficient Elliptic Curve Cryptography Encryption Framework for Cloud Computing

Cloud computing has benefited significantly from the ever-increasing capabilities of computer hardware, including faster microprocessors, larger memory capacity, and greater network bandwidth with high storage. This trend is expected to continue. Cloud computing enables the addition of colored displays to full-blown Web browsers. Some processes add embedded cloud warnings to investigate how data are stored on a local or intermediary system. For instance, all log files of a cloud computing server upload or download data, and all the sessions are stored in clear, unencrypted text on a local computer that multiple users have access to. The cloud client encrypts sessions with the standard method; however, the server does not fully protect such sessions. A high scheme with low-cost encryption and an elliptic curve is established in this study to solve this issue. A lookup table is integrated into the proposed framework.