Security intelligence for cloud management infrastructures

Berger, Stefan; Garion, Shelly; Moatti, Yosef; Naor, Dalit; Pendarakis, Dimitrios; Shulman‐Peleg, Alexandra; Rao, Josyula R.; Valdez, Enriquillo; Weinsberg, Yaron

doi:10.1147/jrd.2016.2572462

Cited by 13 publications

(3 citation statements)

References 14 publications

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“…Berger et al have discussed the problem revolving around the protection of cloud infrastructure and workloads with the help of logging, smart auditing and satisfying compliance requirements [2]. Cloud Security Intelligence (CSI) is a systematic approach that they have used for collection, aggregation, correlation and analysis of data on different planes of cloud based infrastructure, by making use of a closed-loop architecture.…”

Section: Literature Surveymentioning

confidence: 99%

Security Analytics and Benchmarking Log Aggregation in the Cloud

Pathak¹,

Rangasamy²,

Selvaraj³

2018

EAI Endorsed Transactions on Cloud Systems

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With increase in popularity of Cloud computing, most organizations are moving towards the Cloud. The main concern for these organizations when migrating to the Cloud is securing their data in the Cloud. There are security measures that can be deployed to address the risk the organization faces to the security threats posed within the Cloud. This project illustrates how the problem can be solved using data protection techniques and security analytics of the log data within the Cloud deployment. In PaaS implementation of Cloud, the customer and the Cloud vendor has a shared responsibility model and the project will discuss what customer can do for their responsibility in the areas highlighted above.Data is of paramount importance to any organization and protection of data becomes more complex in a Cloud offering as the storage is located off premise. Like any other environment devices, servers and applications in Cloud produce logs that can be aggregated and analyzed to identify security anomalies. Comparison of various log aggregation tools can give a detailed idea about what tool is better. Two log aggregation tools Splunk and the Elastic stack have been compared in this project. A combination of the above described strategies can address and point on various security risks, and help reduce the risk of the organization to a significant degree.

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Section: Literature Surveymentioning

confidence: 99%

Security Analytics and Benchmarking Log Aggregation in the Cloud

Pathak¹,

Rangasamy²,

Selvaraj³

2018

EAI Endorsed Transactions on Cloud Systems

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“…The security hazard is huge when we also c o n s i d e r t o u c h y s p a c e s l i k e t h e Telecommunications, Military, Health, Defence and other legislative or private substances. [11][12][13][14][15] In view of the foretold understanding, different authentication structures, conventions are first proposed then created to give start for the finish protection, security and checks all substances and areas. In any case, there remains bounty to cover and investigate regarding protection and security in Smart-phones, Cloud Computing authentication systems.…”

Section: Introductionmentioning

confidence: 99%

A Secure Communication using Smart Mobile and Cloud Process

2019

IJITEE

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Information storage and security is one of key areas where much research is been done in this digital world where we communicate the data over using third party devices such as cloud by using smart devices such as mobiles so the security is an quite challenging factor where we access our data across the globe and with the social media coming into factor for the storage and accessibility of the data so there are many risk factors coming into process so we need to implement a smart and secure system for the authentication threats so here in this paper we implement a smart system in which face recognition aunthication system is implement between the cloud and mobile activity which give more security in terms of data storage and communication and then we evaluate using different graphs and also analyses the attacks

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“…Secondly, Terraform uses a declarative language that allows users to specify the desired end-state of the infrastructure without detailing the steps to achieve it. This simplifies the configuration process and reduces the potential for errors, ultimately ensuring that the infrastructure remains consistent and maintainable [90,91]. The simplicity of the language accelerates the deployment of resources in response to a large-scale DDoS attack on the web server, enabling the system to recover faster and maintain its performance, scalability, and resilience.…”

Section: Proposed Smart City Iot Deploymentmentioning

confidence: 99%

A Scalable Approach to Improve Security and Resilience of Smart City IoT Architectures

Zakurdaev

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The swift emergence of smart technologies, notably the Internet of Things (IoT), has revolutionized numerous industry sectors. However, outdated IoT architectures constrain innovation in smart cities due to scalability issues, compromised resilience, and security vulnerabilities. This thesis scrutinizes these challenges, advocating a contemporary approach to IoT system design. Prioritizing performance, scalability, security, and resilience, the research delves into the applicability of Platform-as-a-Service (PaaS) and Infrastructure-as-Code (IaC) methodologies, endorsing containerization and cloud-centric patterns for smart city IoT. The introduced model is contrasted with prevailing architectures, highlighting a trajectory for IoT progression. Merging empirical and theoretical insights, this study furnishes guidelines for the future of IoT in smart industries, underscoring the benefits of service-based architectures for efficiency, resilience, and security. iii This MASc thesis owes its existence to the guidance and encouragement of many. My appreciation goes to Dr. Chung-Horng Lung, whose keen insights sparked my interest in cloud technologies, one of the most fascinating focus areas of this research. I am also indebted to Mohammed Ismail, a long-time friend and academic cohort. His eagerness to explore the complexities of containerization technologies along with me, combined with his invaluable advice during the implementation and testing phases of my experiments, contributed significantly to the success of this work. My family, a constant source of strength, and my patient fiancé, who has endured my long working hours and has always stood by me, deserve heartfelt recognition. I would be remiss not to mention my two feline companions, whose incessant meows formed a harmonic and cheering soundtrack outside my office door. Finally, I attribute the greatest part of this journey's success to the unwavering guidance of my supervisor, Dr. Jason Jaskolka. His mentorship, from igniting my interest in cybersecurity to the detailed critiques of my work and consistent support, has been profoundly inspirational. His exemplary efficiency and dedication to his students' success were guiding lights during challenging times, for which I am endlessly grateful.

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Security intelligence for cloud management infrastructures

Cited by 13 publications

References 14 publications

Security Analytics and Benchmarking Log Aggregation in the Cloud

Security Analytics and Benchmarking Log Aggregation in the Cloud

A Secure Communication using Smart Mobile and Cloud Process

A Scalable Approach to Improve Security and Resilience of Smart City IoT Architectures

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