Papers by Ramasankar Molleti
World Journal of Advanced Research and Reviews, 2024
The increase of cyber threats from individual cases to a worldwide problem is the reason why peop... more The increase of cyber threats from individual cases to a worldwide problem is the reason why people have shifted their cybersecurity perspectives. Basic defense processes, originally well understood and effective, fail to match modern attacks' complexity and velocity. Taking into consideration LLMs as a recent addition to AI, this paper aims at discussing their application in integrating threat detection and response automation systems. As a result, LLMs, which have higher capabilities for natural language processing, deliver a revolutionary perspective regarding cybersecurity. Since LLM agents can review massive amounts of security data, distinguish patterns, and create contextually appropriate responses, they can bridge the gap between emerging threats and stable security systems. The paper examines the tools used by LLM agents, such as natural language processing to analyse the logs, contextual anomaly detection, pattern identification in network traffic, and the analysis of the user's behaviour. Also, it describes how LLM agents can support automated threat handling in the context of threat identification, alert prioritization, context-driven response generation, security policy enforcement, and threat handling. The integration of LLM agents into already known systems, including SIEM systems and AI-Ops platforms, is also considered, which allows for further conclusions on the opportunities to create proactive cybersecurity systems. However, open dilemmas such as adversarial attacks and interpretability are still present, the future for LLM agents in cybersecurity is still bright, and there are more possibilities in multi-modal threat analysis and quantum-safe LLM-based cryptography.
Internation Journal of Communication and Information Technology, 2023
Integration of Machine Learning into modern threat intelligence provides series of benefits that ... more Integration of Machine Learning into modern threat intelligence provides series of benefits that will enhance organizational preparedness to fight cyber threats. The use of ML helps to leverage various qualities that will assist in managing cyber threats through data analysis and predictive analytics that spot threats and help companies to revamp their mitigation strategies. The application of ML in cybersecurity in detection of anomalies stems from deep learning techniques that highlight trends within the system and achieve a mechanism of detecting any deviations from the normal engagement. Behavior analysis also helps to prevent any intrusion from the system, managing an instrumental protection from threats before they occur on the system. However, including ML in cybersecurity stands as a difficulty because of the data quality issues and privacy concerns when using the ML learning methods. Additionally, ML does not have the capacity to provide transparent steps to handling their information. However, these challenges can be addressed through using Explainable AI and advanced behavioral analytics to help in detailing ML advances in cybersecurity. Organizations should thus employ ML In cyber threat intelligence to help identifying and automating response to risks.
American Journal of Science and Learning for Development (AJSLD), 2024
The article focuses on the vital function of AI (Artificial Intelligence) in cybersecurity measur... more The article focuses on the vital function of AI (Artificial Intelligence) in cybersecurity measures and argues for effective risk assessment techniques in AI-powered cybersecurity. In this section, the article explored AI in cybersecurity by emphasizing the AI technologies that are in use and what their applications are in the field of threat detection, vulnerability management, and proactive defense mechanisms. Moreover, the article looked into the AI security risk types, such as malicious AI, biases, fairness issues, potential vulnerabilities, and the ethical questions the AI process causes. The paper explained the concepts of frameworks and methodologies for assessing risks in AI systems, beginning with existing risk assessment frameworks, such as the NIST cybersecurity framework and the FAIR framework methodologies. Risk mitigation strategies of AI systems, regulatory and ethical issues, and future AI and cybersecurity problems concerning technological progress are also assessed. As concluded, implementing regulations for compliance, ethical principles, and technological developments is the key to meeting the new challenges and developing safe and sustainable digital systems. The recommendations comprise fostering transparency, accountability, and continuous education and awareness programs to enable people to manage ethical dilemmas and mitigate the risks very well.
INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING, 2021
This technical report explains how the key control of real-time application log analysis has been... more This technical report explains how the key control of real-time application log analysis has been dismantled in present day software development and activities. It looks at the definition, types, and importance of the real-time log and the tools and techniques for driving the analysis. Looking at the benefits and challenges of real-time log analysis, the report also provides recommendations for implementation and use cases as well as the best practices of using log data for decision-making processes. As real-life examples demonstrate, real-time log analysis can also foster application execution, update security, and redesign clients' experience according to this report.
International Journal of Scientific Research in Engineering and Management (IJSREM), Feb 2021
FaaS or Serverless computing extends the existing cloud computing by removing or abstracting the
... more FaaS or Serverless computing extends the existing cloud computing by removing or abstracting the
notion of a server and the need to scale up and down on demand. This paper seeks to discuss the
security issues that are associated with serverless architecture, with special focus on authentication,
data encryption, compliance issues and those risks that are unique to different vendors. It compares
existing security architectures and measures and current industry benchmarks originating from
premier cloud platforms such as AWS Lambda, Azure Functions, Google Cloud Functions. Some
of the critical risks including injection attacks, insecure deployments, and operational monitoring
have similar threat proneness models accompanied by secure coding, IAM integration, DevOps
rules, and recommendations.
International Journal of Scientific Research in Engineering and Management (IJSREM), Feb 2022
This paper focuses on how it is possible to bring advanced automation to cloud migrations so as t... more This paper focuses on how it is possible to bring advanced automation to cloud migrations so as to produce maximal cohesion. It starts with a literature review of cloud migration and focuses on the various automation objectives that simplify security, performance, and operational issues that arise during migration. The study can be divided into how organizations have classified cloud migration strategies and covers trends that include DevOps and serverless architectures. The strategies described in the post range from pre-migration planning, to an extensive guide to automated testing, as well as Infrastructure as Code (IaC) ideas and CI/CD pipelines. Integration and security aspects are also analyzed in the paper and advantages and possible disadvantages of automation solutions are discussed. Finally, it seeks to help IT managers on how to use automation in improving the cloud migration procedures.
International Scientific Journal of Engineering and Management(ISJEM), Sep 2022
This technical report aims to analyze the implementation of End-to-End Well-Architected Zero Trus... more This technical report aims to analyze the implementation of End-to-End Well-Architected Zero Trust Architecture in Fintech cloud settings. It discusses the enhancement of cybersecurity measures and focuses on the Zero Trust model within the context of Fintech. It then goes to the Artificial Intelligence in Fraud Detection Systems and its components and function within the Zero Trust architecture. It deconstructs the structure's ideas, advantages and drawbacks, in addition to, looking at the emerging patterns and future developments. The overview shall also present a guarded perspective on how Zero Trust principles can further enhance security in Fintech cloud setting and provide suggestions for possible implementation and development of collection to opportunity.
NTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING, 2024
The combination of artificial intelligence (AI) with cloud computing implies a promising future o... more The combination of artificial intelligence (AI) with cloud computing implies a promising future of novel technological solutions that have shifted the ways of creating, implementing, and maintaining AI systems. This paper aims at discussing the mutual synergy of AI and cloud technologies and how cloud solutions support and improve AI. Turning to the core elements of the work, we examine the premises of both AI and cloud computing, their mutual relationship. The paper aims to look into the extent to which cloud infrastructure has transformed the future for the development of AI, particularly with reference to the challenges of scalability and the possibilities of accessing high powered computing, not to mention the added bonus of cost efficiency. New techniques like Federated Learning, AutoML, and AI as a service are shared while contemplating ways of enabling AI to be a breakout of the circle of its enthusiasts. The article also discusses emerging forms of cloud computing, such as edge computing, serverless computing, and hybrid cloud, which will be evaluated concerning the prospects for developing AI and ML. Moreover, it discusses data management within the cloud, including big data analytics, data lakes, and ETL processes optimized for AI. It is important to stress that this article is an attempt to provide a synoptic view of these intertwined subjects in order to explain the change brought by cloud-driven AI and the impacts it can have on technology and society. These findings provide useful information concerning AI and cloud computing to scholars, professionals, and policymakers who are engaging in this growing, dynamic field.
INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING, 2024
Apache Kafka, an open-source distributed streaming platform, is now a critical part of any modern... more Apache Kafka, an open-source distributed streaming platform, is now a critical part of any modern data architecture, particularly in the hybrid setup. This paper aims to discuss best practices that can be employed regarding Kafka to make it more performant and robust in on-premise or Cloud hybrid environments. As this research compares theoretical strategies regarding cluster configuration, networks’ optimization, data partition, fault tolerance, disaster recovery, and security, it offers a practical reference for practitioners. Also, there are examples of industries to know how they have implemented the respective applications and what practices are considered effective. The discussion is wrapped up by the evaluation of present problems and possible development for further research, which is beneficial to both academics and practitioners.
INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING, 2023
This study examines and comprises analyses of various aspects of the secure high-performance cont... more This study examines and comprises analyses of various aspects of the secure high-performance container network mesh solutions in response to the container and microservices architecture. It looks at the historical development of these solutions, basic ingredients, and today's specifics of both open-source and commercial solutions. The focus of the study falls on the key security issues and their solutions as well as the performance. It provides information on how these can be done through case studies and benchmarks to show current practical implementations and performance comparisons. The study also identifies the future trends and research directions of this dynamic area of study. The results emphasize that security is of high value in container network meshes, also, performance and complexity should be optimal in the solutions. This study enhances the knowledge of today's potential and tomorrow's possibilities of these solutions and will be useful for researchers, practitioners, and decision-makers involved in containerized application deployment and management.
Educational Administration: Theory and Practice, 2023
Cloud modernization is critical to any organization planning to increase IT agility as well as op... more Cloud modernization is critical to any organization planning to increase IT agility as well as optimization of costs in the current technological disruption. This paper discusses AI as a service in the context of cloud modernization, specifically of infrastructure, capacity, and operation. AI technologies used in industries include predictive analytics, resource allocation, and secure connectivity reducing potential problems before they occur and therefore cutting instances of production interruptions. Nonetheless, there are some barriers when it comes to implementing AI in the process of cloud modernization. This work splits cloud modernization into approaches such as replatforming, refactoring, and containerization depending on apps’ requirements and business goals. It also presents and analyzes the place of AI in strengthening the safety of clusters, data stock, and automatization benefits in numerous fields such as healthcare, retail, finance, and manufacturing. Certain hindrances such as data elaborate and the dearth of experts in the field of AI should not deter organizations from incorporating AI in cloud strategies because of the advantages such as cost reduction, flexibility, and even increased efficiency. With proper negation of challenges by accurate model governance, adequate data management, and proper security, organizations can promote competitive benefits and excellent operation in the fully developed digital economy through artificial intelligence’s cloud modernization.
COVID-19 Pandemic timeframe confirms that cloud computing is a useful part of an international st... more COVID-19 Pandemic timeframe confirms that cloud computing is a useful part of an international structure that enables sharing computing facilities while working remotely. Though, the newly developed connected as well as automated cars have also amplified the susceptibility to cyber-crimes like phishing, malware, ransomware, and data breach. In this case, attention will be drawn to the new trends identified in the process of Cloud Computing during the pandemic, namely the increased level of sophistication of attacks by cybercriminals and hackers, and sometimes with the support of states. It narrates possible threats which are Sniffer attacks, DNS weaknesses, CAPTCHA cracking, Google hacking and many others, their effects on international security. This analysis shows that to secure such information for continued business, then efficient security controls like encryption of data, MFA, and monitoring should be incorporated. It also aims at new threats to be included into the system in addition to optimizing security measures with a view of improving on the protection of new complexes such as cloud environments. Therefore, the conclusion suggests that daily monitoring and the struggle for finding new approaches are critically important to safeguard cloud services in the dynamic environment and in the context of the post Covid-19 period.
International Journal on Recent and Innovation Trends in Computing and Communication, 2020
The unlocking value from Kubernetes-managed databases for modern enterprise applications plays a ... more The unlocking value from Kubernetes-managed databases for modern enterprise applications plays a major role in controlling the databases. For the robotized scaling it understands the management of the database. Statefulsets play an important role in maintaining the database more strongly for any kind of challenges and obstacles.
International Journal of Scientific Research in Engineering and Management (IJSREM), 2022
Blue-green deployment has become very important in ensuring that there is minimal time when the s... more Blue-green deployment has become very important in ensuring that there is minimal time when the system is offline and reducing other risks associated with updating the software in cloud-native architecture. This paper aims to discuss the modern trends in blue-green deployment, focusing on the change from simple to complex structures. In this paper, the discussion on Containerization, orchestration platforms, and automated testing pipelines has greatly improved the capability of blue-green deployment. Some of the issues that are covered include the issue of managing database schema, managing the resources that are used, and the real-life scenarios that are involved. Thus, the effectiveness of the metrics for measuring different aspects of the blue-green deployment is considered, and the influence of the approach on the frequency of deployment and system stability is discussed. This paper also discusses the future of the deployment research area and the possibility of incorporating artificial intelligence into the deployment processes suggesting that further development of intelligent and strong deployment in cloud-native environments is possible.
Journal of Electronics, 2019
The dispersed cloud has transformed the ways of organization IT management through flexible provi... more The dispersed cloud has transformed the ways of organization IT management through flexible provision resources over the internet, therefore changing IT operational models. Automation is considered a key enabler for cloud environments as it helps in the deployment, scalability, development, testing and production. Consequently, end-to-end automation in cloud infrastructure is researched in this paper where the focused tools are AWS CloudFormation, Puppet, Ansible, Chef, Kubernetes, Terraform, Azure Automation, SaltStack, VCM, CFEngine, and Foreman. It reviews their deployments in various clouds and talks about issues like security and integration difficulties. The goal of this research would be to provide pragmatic knowledge to working IT professionals in order to work on cloud automation technologies more efficiently.
International Journal of Scientific Research in Engineering and Management (IJSREM), 2022
This paper aims to review how AI can be implemented in DevSecOps for cloud environments for the i... more This paper aims to review how AI can be implemented in DevSecOps for cloud environments for the improvement of security across the SDLC. Authenticated automation, predictive analytics, and detecting threats are significant in realizing the cloud-native applications' complexity and speed. Some of the focused strategies are AI in Security Testing, AI Powered Vulnerability Management, and AI in Compliance with regular and deeper security checks against the latest threats that might threaten the system. Subsequent trends reveal factors that define the utilization of AI in threat intelligence as well as prediction for secure software development in the future. The paper presents continuity of security as an important aspect of cloud application development with the emphasis on AI's contributions to it.
International Scientific Journal of Engineering and Management(ISJEM), 2023
This technical report focuses on the concept of cloud governance in the context of FinOps which i... more This technical report focuses on the concept of cloud governance in the context of FinOps which is Financial Operations. The basics for effective governance and financial management becomes crucial as companies continue to adopt cloud technologies. The report examines the cloud governance framework, the parts of it, and tips for using it in FinOps. It leaps into FinOps standards and how they are embedded into cloud governance solutions and the relevant tools and technologies. These challenges and solutions related with this integration are described, nearby future models in the field. This extensive review aims to provide bits of information to organizations that would like to enhance their cloud activities but at the same time, keep an eye on costs and compliance.
Scientific Research and Community, 2022
This paper discusses some sophisticated autoscaling strategies in Kubernetes, and they include ho... more This paper discusses some sophisticated autoscaling strategies in Kubernetes, and they include horizontal and vertical pod autoscaling, cluster levels autoscaling, and metrics based autoscaling. In this regard, it covers the topics of both predictive and event-triggered auto scaling approaches and their applications, the advantages and the potential issues relating to them, and more. Some of the questions answered by the study include how to improve application throughput and resource efficiency and how to achieve cost-efficient K8s clusters for practitioners while providing directions for the research on CA autoscaling in container orchestration.
Journal of Engineering and Applied Sciences Technology, 2022
Additionally, there are several deployment models for Cloud computing: Public Cloud: Services are... more Additionally, there are several deployment models for Cloud computing: Public Cloud: Services are delivered over a network that is accessible by the public. Public cloud services may be free or come under the pay as you go model of remuneration for each use. Private Cloud: The cloud infrastructure is configured for specific usage of a single affiliation that has multiple customers. While it may be claimed, made, and worked by the affiliation, an outcast, or a blend of them, it might be on or off premises. Community Cloud: The cloud infrastructure is configured for a particular utilization by a particular community of clients from
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Papers by Ramasankar Molleti
notion of a server and the need to scale up and down on demand. This paper seeks to discuss the
security issues that are associated with serverless architecture, with special focus on authentication,
data encryption, compliance issues and those risks that are unique to different vendors. It compares
existing security architectures and measures and current industry benchmarks originating from
premier cloud platforms such as AWS Lambda, Azure Functions, Google Cloud Functions. Some
of the critical risks including injection attacks, insecure deployments, and operational monitoring
have similar threat proneness models accompanied by secure coding, IAM integration, DevOps
rules, and recommendations.
notion of a server and the need to scale up and down on demand. This paper seeks to discuss the
security issues that are associated with serverless architecture, with special focus on authentication,
data encryption, compliance issues and those risks that are unique to different vendors. It compares
existing security architectures and measures and current industry benchmarks originating from
premier cloud platforms such as AWS Lambda, Azure Functions, Google Cloud Functions. Some
of the critical risks including injection attacks, insecure deployments, and operational monitoring
have similar threat proneness models accompanied by secure coding, IAM integration, DevOps
rules, and recommendations.