Cloud Computing is a flexible, cost-effective, and proven delivery platform for providing business or consumer IT services over the Internet. However, cloud Computing presents an added level of risk because essential services are often outsourced to a third party, which makes it harder to maintain data security and privacy, support data and service availability, and demonstrate compliance. Cloud Computing leverages many technologies (SOA, virtualization, Web 2.0); it also inherits their security issues, which we discuss here, identifying the main vulnerabilities in this kind of systems and the most important threats found in the literature related to Cloud Computing and its environment as well as to identify and relate vulnerabilities and threats with possible solutions.

/pdf/an-analysis-of-security-issues-for-cloud-computing-1apnvpc3ez.pdf

An analysis of security issues for cloud computing

This paper describes the deployment of a large-scale study designed to measure human interactions across a variety of communication channels, with high temporal resolution and spanning multiple years—the Copenhagen Networks Study. Specifically, we collect data on face-to-face interactions, telecommunication, social networks, location, and background information (personality, demographics, health, politics) for a densely connected population of 1 000 individuals, using state-of-the-art smartphones as social sensors. Here we provide an overview of the related work and describe the motivation and research agenda driving the study. Additionally, the paper details the data-types measured, and the technical infrastructure in terms of both backend and phone software, as well as an outline of the deployment procedures. We document the participant privacy procedures and their underlying principles. The paper is concluded with early results from data analysis, illustrating the importance of multi-channel high-resolution approach to data collection.

/pdf/measuring-large-scale-social-networks-with-high-resolution-15l81adn09.pdf

Measuring large-scale social networks with high resolution.

Measuring large-scale social networks with high resolution. WORKING PAPER.

A survey of security issues for cloud computing

Homomorphic encryption is the encryption scheme which means the operations on the encrypted data. Homomorphic encryption can be applied in any system by using various public key algorithms. When the data is transferred to the public area, there are many encryption algorithms to secure the operations and the storage of the data. But to process data located on remote server and to preserve privacy, homomorphic encryption is useful that allows the operations on the cipher text, which can provide the same results after calculations as the working directly on the raw data. In this paper, the main focus is on public key cryptographic algorithms based on homomorphic encryption scheme for preserving security. The case study on various principles and properties of homomorphic encryption is given and then various homomorphic algorithms using asymmetric key systems such as RSA, ElGamal, Paillier algorithms as well as various homomorphic encryption schemes such as BrakerskiGentry-Vaikuntanathan (BGV), Enhanced homomorphic Cryptosystem (EHC), Algebra homomorphic encryption scheme based on updated ElGamal (AHEE), Non-interactive exponential homomorphic encryption scheme (NEHE) are investigated.

/pdf/survey-of-various-homomorphic-encryption-algorithms-and-4vxyib719m.pdf

Survey of Various Homomorphic Encryption algorithms and Schemes

 Abstract—Cloud computing security challenges and it's also an issue to many researchers; first priority was to focus on security which is the biggest concern of organizations that are considering a move to the cloud. The advantages of cloud computing include reduced costs, easy maintenance and re- provisioning of resources, and thereby increased profits. But the adoption and the passage to the Cloud Computing applies only if the security is ensured. How to guaranty a better data security and also how can we keep the client private information confidential? There are two major questions that present a challenge to Cloud Computing providers. When the data transferred to the Cloud we use standard encryption methods to secure the operations and the storage of the data. But to process data located on a remote server, the Cloud providers need to access the raw data. In this paper we are proposing an application of a method to execute operations on encrypted data without decrypting them which will provide us with the same results after calculations as if we have worked directly on the raw data.

/pdf/homomorphic-encryption-applied-to-the-cloud-computing-1r0whlddq1.pdf

Homomorphic Encryption Applied to the Cloud Computing Security

When the data transferred to the Cloud we use standard encryption methods to secure this data, but when we want to do the calculations on data located on a remote server, it is necessary that the Cloud provider has access to the raw data, and then it will decrypt them. In this paper we propose the application of a method to perform the operation on encrypted data without decrypted and provide the same result as well that the calculations were carried out on raw data.

Homomorphic encryption method applied to Cloud Computing

Newton's method for the common eigenvector problem

Bone is a biological tissue characterized by its hierarchical organization. This material has the ability to be continually renewed, which makes it highly adaptative to external loadings. Bone renewing is managed by a dynamic biological process called bone remodeling (BR), where continuous resorption of old bone and formation of new bone permits to change the bone composition and microstructure. Unfortunately, because of several factors, such as age, hormonal imbalance, and a variety of pathologies including cancer metastases, this process can be disturbed leading to various bone diseases. In this study, we have investigated the effect of breast cancer (BC) metastases causing osteolytic bone loss. BC has the ability to affect bone quantity in different ways in each of its primary and secondary stages. Based on a BR mathematical model, we modeled the BC cells’ interaction with bone cells to assess their effect on bone volume fraction (BV/TV) evolution during the remodeling process. Some of the parameters used in our model have been determined experimentally using the enzyme-linked immune-sorbent assay (ELISA) and the MTT assay. Our numerical simulations show that primary BC plays a significant role in enhancing bone-forming cells’ activity leading to a 6.22% increase in BV/TV over 1 year. On the other hand, secondary BC causes a noticeable decrease in BV/TV reaching 15.74% over 2 years. 

/pdf/experimental-based-mechanobiological-modeling-of-the-15l0692d.pdf

Experimental-based mechanobiological modeling of the anabolic and catabolic effects of breast cancer on bone remodeling

Smart environments consist of a collection of sensors, actuators, and numerous computing units that improve human life. With the booming of smart environments, data generation has been notably increasing in recent years, which must be managed in a smart and optimal manner. The components (i.e., workstations and cloud) used for data processing are not the best to recommend since it is risky and resource costing. For that matter, enterprises, firms and companies are deploying blockchain technologies (BT) as a more suitable alternative. In fact, blockchain is a distributed transaction ledger ensuring the reliability and transparency of data. However, BT faces some inherent security challenges such as DoS, eclipse and double spending attacks as well as Advanced Persistent Threat (APT) and malware. Thus, advanced anomaly detection and mitigation approaches, especially the ones using artificial intelligence (AI) techniques (e. g. Machine Learning, Deep Learning, Federated Learning) are required to address the aforementioned issues. In combination, AI and BT are capable of detecting anomalies within blockchain networks with high accuracy. In this paper, with a focus on cyber security issues, we explore the challenges of blockchain deployment in smart environments. Additionally, we explore the use of anomaly detection AI-based techniques as a ledger of blockchain technologies to address the security issues in smart environments. Thus, we propose a framework that emphasizes the challenges of BT, values and capabilities of BT-AI integration. We also present research trends to highlight potential research paths for improving the security of blockchain networks using artificial intelligence.

Abdellatif El Ghazi

Papers

Homomorphic Encryption Applied to the Cloud Computing Security

Homomorphic encryption method applied to Cloud Computing

Newton's method for the common eigenvector problem

Experimental-based mechanobiological modeling of the anabolic and catabolic effects of breast cancer on bone remodeling

A Survey on Blockchain and Artificial Intelligence Technologies for Enhancing Security and Privacy in Smart Environments