Evaluating the impact of eDoS attacks to cloud facilities

The complexity of modern cloud facilities requires attentive management policies that should encompass all aspects of the system. Security is a critical issue, as intrusions, misuse or denial of service attacks may damage both the users and the cloud provider including its reputation on the market. Disruptive attacks happen fast, cause evident and short term damages and are usually the result of operations that are hard to disguise. On the other hand, Energy oriented Denial of Service (eDoS) attacks aim at producing continuous minor damages, eventually with long term consequences. These long lasting attacks are difficult to detect. In this paper we model and analyse the behaviour of a system under eDoS attack. We study the impact in terms of cloud energy consumption of an attack strategy previously proposed in the literature and compare it with other strategies that we propose. Our findings show that the strategy previously proposed in the literature, based on keeping the cloud close to saturation, is not optimal (from the point of view of the attacker) in presence of non-constant workload and that there is a trade-off between the aggressiveness of the attacker and the duration of the attack in order to maximise the damage

Selected Computing Research Papers Volume 7 June 2018

Contents Critical Evaluation of Arabic Sentimental Analysis and Their Accuracy on Microblogs (Maha Al-Sakran) Evaluating Current Research on Psychometric Factors Affecting Teachers in ICT Integration (Daniel Otieno Aoko) A Critical Analysis of Current Measures for Preventing Use of Fraudulent Resources in Cloud Computing (Grant Bulman) An Analytical Assessment of Modern Human Robot Interaction Systems (Dominic Button) Critical Evaluation of Current Power Management Methods Used in Mobile Devices (One Lekula) A Critical Evaluation of Current Face Recognition Systems Research Aimed at Improving Accuracy for Class Attendance (Gladys B. Mogotsi) Usability of E-commerce Website Based on Perceived Homepage Visual Aesthetics (Mercy Ochiel) An Overview Investigation of Reducing the Impact of DDOS Attacks on Cloud Computing within Organisations (Jabed Rahman) Critical Analysis of Online Verification Techniques in Internet Banking Transactions (Fredrick Tshane

Pattern Analytical Module for EDOS Attacker Recognition

Abstract: Cloud computing has provided a platform to its users where they are charged on the basis of usage of the cloud resources; this is known as "pay-as-you-use". Today, Cloud computin

Analysis of the EDoS attack impact on elastic cloud services using finite queuing model

This paper proposes a logical model to examine the effect of the EDoS attack in cloud environment using finite queuing model and enhanced with experimental model. Due to this sophisticated attacks the computing resources are busy and buffer capacity of the cloud gets exhausted by both the legitimate and malicious user requests, because of this both types of requests could not get the service. The legitimate customers are unable to get service of web application. In this backdrop this paper investigates and evaluates the vendor loss factor from the cost factor of view since the legitimate client requests are denied service. The objective of this analysis is twofold i) to identify the dynamics of the EDoS attacks with different attack rates and to measure the various performance metrics (total number of busy virtual machines, utilization of the cloud resources, request response time, request loss probability, and throughput). ii) The cost function is defined and evaluated based on these performance metrics. Finally compared analytical and experimental results are presented and conclusions are drawn

Detecting Specific Types of DDoS Attacks in Cloud Environment by Using Anomaly Detection

RÉSUMÉ Un des avantages les plus importants de l'utilisation du cloud computing est d'avoir des services sur demande, et donc la méthode de paiement dans l'environnement du cloud est de type payer selon l'utilisation (pay per use). Cette caractéristique introduit un nouveau type d'attaque de déni des services appelée déni économique de la durabilité (Economic Denial of Sustainability EDoS) où le client paie des montants supplémentaires au fournisseur du cloud à cause de l'attaque. Les attaques DDoS avec leur nouvelle version sont divisées en trois catégories: 1) Les attaques de consommation de la bande passante. 2) Les attaques qui ciblent des applications spécifiques. 3) Les attaques d'épuisement sur la couche des connections. Dans ce travail, nous avons proposé un nouveau modèle pour détecter précisément les différents types des attaques DDoS et EDoS en comparant le trafic et l'utilisation des ressources dans des situations normale et d'attaque. Des caractéristiques (features) qui sont liées au trafic et à l'utilisation des ressources dans le cas de chaque attaque ont été recueillies. Elles constituent les métriques de notre modèle de détection. Dans la conception de notre modèle, nous avons utilisé les caractéristiques liées à tous les 3 types d'attaques puisque les caractéristiques d'un type d'attaque jouent un rôle important pour détecter un autre type. En effet, pour trouver un point de changement dans l'utilisation des ressources et le comportement du trafic nous avons utilisé l'algorithme des sommes cumulées CUSUM. La précision de notre algorithme a ensuite été étudiée en comparant sa performance avec celle d'un travail populaire précédent. Le taux de détection du modele était élevé, Ce qui indique la haute précision de l'algorithme conçu.----------ABSTRACT One of the most important benefits of using cloud computing is to have on-demand services; accordingly the method of payment in cloud environment is pay per use. This feature results in a new kind of DDOS attack called Economic Denial of Sustainability (EDoS) in which the customer pays extra to the cloud provider because of the attack. DDoS attacks and a new version of these attacks which called EDoS attack are divided into three different categories: 1) Bandwidth–consuming attacks, 2) Attacks which target specific applications and 3) Connection–layer exhaustion attacks. In this work we proposed a novel and inclusive model to precisely detect different types of DDoS and EDoS attacks by comparing the traffic and resource usage in normal and attack situations. Features which are related to traffic and resource usage in each attack were collected as the metrics of our detection model. In designing our model, we used the metrics related to all 3 types of attacks since features of one kind of attack play an important role to detect another type. Moreover, to find a change point in resource usage and traffic behavior we used CUSUM algorithm. The accuracy of our algorithm was then investigated by comparing its performance with one of the popular previous works. Achieving a higher rate of correct detection in our model proved the high accuracy of the designed algorithm

Split Federated Learning for 6G Enabled-Networks: Requirements, Challenges and Future Directions

Sixth-generation (6G) networks anticipate intelligently supporting a wide range of smart services and innovative applications. Such a context urges a heavy usage of Machine Learning (ML) techniques, particularly Deep Learning (DL), to foster innovation and ease the deployment of intelligent network functions/operations, which are able to fulfill the various requirements of the envisioned 6G services. Specifically, collaborative ML/DL consists of deploying a set of distributed agents that collaboratively train learning models without sharing their data, thus improving data privacy and reducing the time/communication overhead. This work provides a comprehensive study on how collaborative learning can be effectively deployed over 6G wireless networks. In particular, our study focuses on Split Federated Learning (SFL), a technique recently emerged promising better performance compared with existing collaborative learning approaches. We first provide an overview of three emerging collaborative learning paradigms, including federated learning, split learning, and split federated learning, as well as of 6G networks along with their main vision and timeline of key developments. We then highlight the need for split federated learning towards the upcoming 6G networks in every aspect, including 6G technologies (e.g., intelligent physical layer, intelligent edge computing, zero-touch network management, intelligent resource management) and 6G use cases (e.g., smart grid 2.0, Industry 5.0, connected and autonomous systems). Furthermore, we review existing datasets along with frameworks that can help in implementing SFL for 6G networks. We finally identify key technical challenges, open issues, and future research directions related to SFL-enabled 6G networks

Exploiting cloud utility models for profit and ruin

A key characteristic that has led to the early adoption of public cloud computing is the utility pricing model that governs the cost of compute resources consumed. Similar to public utilities like gas and electricity, cloud consumers only pay for the resources they consume and only for the time they are utilized. As a result and pursuant to a Cloud Service Provider\u27s (CSP) Terms of Agreement, cloud consumers are responsible for all computational costs incurred within and in support of their rented computing environments whether these resources were consumed in good faith or not. While initial threat modeling and security research on the public cloud model has primarily focused on the confidentiality and integrity of data transferred, processed, and stored in the cloud, little attention has been paid to the external threat sources that have the capability to affect the financial viability of cloud-hosted services. Bounded by a utility pricing model, Internet-facing web resources hosted in the cloud are vulnerable to Fraudulent Resource Consumption (FRC) attacks. Unlike an application-layer DDoS attack that consumes resources with the goal of disrupting short-term availability, a FRC attack is a considerably more subtle attack that instead targets the utility model over an extended time period. By fraudulently consuming web resources in sufficient volume (i.e. data transferred out of the cloud), an attacker is able to inflict significant fraudulent charges to the victim. This work introduces and thoroughly describes the FRC attack and discusses why current application-layer DDoS mitigation schemes are not applicable to a more subtle attack. The work goes on to propose three detection metrics that together form the criteria for detecting a FRC attack from that of normal web activity and an attribution methodology capable of accurately identifying FRC attack clients. Experimental results based on plausible and challenging attack scenarios show that an attacker, without knowledge of the training web log, has a difficult time mimicking the self-similar and consistent request semantics of normal web activity necessary to carryout a successful FRC attack

Advances in Information Security and Privacy

With the recent pandemic emergency, many people are spending their days in smart working and have increased their use of digital resources for both work and entertainment. The result is that the amount of digital information handled online is dramatically increased, and we can observe a significant increase in the number of attacks, breaches, and hacks. This Special Issue aims to establish the state of the art in protecting information by mitigating information risks. This objective is reached by presenting both surveys on specific topics and original approaches and solutions to specific problems. In total, 16 papers have been published in this Special Issue

Security in Cloud Computing: Evaluation and Integration

Au cours de la dernière décennie, le paradigme du Cloud Computing a révolutionné la manière dont nous percevons les services de la Technologie de l’Information (TI). Celui-ci nous a donné l’opportunité de répondre à la demande constamment croissante liée aux besoins informatiques des usagers en introduisant la notion d’externalisation des services et des données. Les consommateurs du Cloud ont généralement accès, sur demande, à un large éventail bien réparti d’infrastructures de TI offrant une pléthore de services. Ils sont à même de configurer dynamiquement les ressources du Cloud en fonction des exigences de leurs applications, sans toutefois devenir partie intégrante de l’infrastructure du Cloud. Cela leur permet d’atteindre un degré optimal d’utilisation des ressources tout en réduisant leurs coûts d’investissement en TI. Toutefois, la migration des services au Cloud intensifie malgré elle les menaces existantes à la sécurité des TI et en crée de nouvelles qui sont intrinsèques à l’architecture du Cloud Computing. C’est pourquoi il existe un réel besoin d’évaluation des risques liés à la sécurité du Cloud durant le procédé de la sélection et du déploiement des services. Au cours des dernières années, l’impact d’une efficace gestion de la satisfaction des besoins en sécurité des services a été pris avec un sérieux croissant de la part des fournisseurs et des consommateurs. Toutefois, l’intégration réussie de l’élément de sécurité dans les opérations de la gestion des ressources du Cloud ne requiert pas seulement une recherche méthodique, mais aussi une modélisation méticuleuse des exigences du Cloud en termes de sécurité. C’est en considérant ces facteurs que nous adressons dans cette thèse les défis liés à l’évaluation de la sécurité et à son intégration dans les environnements indépendants et interconnectés du Cloud Computing. D’une part, nous sommes motivés à offrir aux consommateurs du Cloud un ensemble de méthodes qui leur permettront d’optimiser la sécurité de leurs services et, d’autre part, nous offrons aux fournisseurs un éventail de stratégies qui leur permettront de mieux sécuriser leurs services d’hébergements du Cloud. L’originalité de cette thèse porte sur deux aspects : 1) la description innovatrice des exigences des applications du Cloud relativement à la sécurité ; et 2) la conception de modèles mathématiques rigoureux qui intègrent le facteur de sécurité dans les problèmes traditionnels du déploiement des applications, d’approvisionnement des ressources et de la gestion de la charge de travail au coeur des infrastructures actuelles du Cloud Computing. Le travail au sein de cette thèse est réalisé en trois phases.----------ABSTRACT: Over the past decade, the Cloud Computing paradigm has revolutionized the way we envision IT services. It has provided an opportunity to respond to the ever increasing computing needs of the users by introducing the notion of service and data outsourcing. Cloud consumers usually have online and on-demand access to a large and distributed IT infrastructure providing a plethora of services. They can dynamically configure and scale the Cloud resources according to the requirements of their applications without becoming part of the Cloud infrastructure, which allows them to reduce their IT investment cost and achieve optimal resource utilization. However, the migration of services to the Cloud increases the vulnerability to existing IT security threats and creates new ones that are intrinsic to the Cloud Computing architecture, thus the need for a thorough assessment of Cloud security risks during the process of service selection and deployment. Recently, the impact of effective management of service security satisfaction has been taken with greater seriousness by the Cloud Service Providers (CSP) and stakeholders. Nevertheless, the successful integration of the security element into the Cloud resource management operations does not only require methodical research, but also necessitates the meticulous modeling of the Cloud security requirements. To this end, we address throughout this thesis the challenges to security evaluation and integration in independent and interconnected Cloud Computing environments. We are interested in providing the Cloud consumers with a set of methods that allow them to optimize the security of their services and the CSPs with a set of strategies that enable them to provide security-aware Cloud-based service hosting. The originality of this thesis lies within two aspects: 1) the innovative description of the Cloud applications’ security requirements, which paved the way for an effective quantification and evaluation of the security of Cloud infrastructures; and 2) the design of rigorous mathematical models that integrate the security factor into the traditional problems of application deployment, resource provisioning, and workload management within current Cloud Computing infrastructures. The work in this thesis is carried out in three phases

Cyber-Storms Come from Clouds: Security of Cloud Computing in the IoT Era

The Internet of Things (IoT) is rapidly changing our society to a world where every "thing" is connected to the Internet, making computing pervasive like never before. This tsunami of connectivity and data collection relies more and more on the Cloud, where data analytics and intelligence actually reside. Cloud computing has indeed revolutionized the way computational resources and services can be used and accessed, implementing the concept of utility computing whose advantages are undeniable for every business. However, despite the benefits in terms of flexibility, economic savings, and support of new services, its widespread adoption is hindered by the security issues arising with its usage. From a security perspective, the technological revolution introduced by IoT and Cloud computing can represent a disaster, as each object might become inherently remotely hackable and, as a consequence, controllable by malicious actors. While the literature mostly focuses on security of IoT and Cloud computing as separate entities, in this article we provide an up-to-date and well-structured survey of the security issues of Cloud computing in the IoT era. We give a clear picture of where security issues occur and what their potential impact is. As a result, we claim that it is not enough to secure IoT devices, as cyber-storms come from Clouds