Reza Ebrahimi Atani

Ali Habibzadeh, Farid Feyzi, Reza Ebrahimi Atani

Large Language Models (LLMs) have emerged as powerful tools capable of understanding and generating human-like text, offering transformative potential across diverse domains. The Security Operations Center (SOC), responsible for safeguarding digital infrastructure, represents one of these domains. SOCs serve as the frontline of defense in cybersecurity, tasked with continuous monitoring, detection, and response to incidents. However, SOCs face persistent challenges such as high alert volumes, limited resources, high demand for experts with advanced knowledge, delayed response times, and difficulties in leveraging threat intelligence effectively. In this context, LLMs can offer promising solutions by automating log analysis, streamlining triage, improving detection accuracy, and providing the required knowledge in less time. This survey systematically explores the integration of generative AI and more specifically LLMs into SOC workflow, providing a structured perspective on its capabilities, challenges, and future directions. We believe that this survey offers researchers and SOC managers a broad overview of the current state of LLM integration within academic study. To the best of our knowledge, this is the first comprehensive study to examine LLM applications in SOCs in details.

Seyed Pourya Miralavy, Reza Ebrahimi Atani, Navid Khoshrouz

Air pollution is a major concern in large urban areas. Various studies have been made to monitor and control the pollution level emitted by the vehicles but some main factors like ease of implementation or feasibility of the proposed approaches are not focused in the told studies. In this paper we propose a wireless sensor network solution to monitor vehicles exhaust systems pollution emission. Furthermore, we evaluate the feasibility of our proposed approach with respect to energy consumption and network lifetime by means of simulation. Our results indicate that our proposed scheme is practical for implementation using well known MAC layer protocols.

Mehran Alidoost Nia, Eduard Babulak, Benjamin Fabian et al.

Anonymous communication systems (ACS) offer privacy and anonymity through the Internet. They are mostly free tools and are popular among users all over the world. In the recent years, anonymity applications faced many problems regarding traffic engineering methods. Even though they ensure privacy under some conditions, their anonymity will be endangered by high performance processing units. To address these issues, this study is devoted to investigating traffic-engineering methods in anonymous communication systems, and proposes an analytical view of the current issues in ACS privacy and anonymity. Our study also indicates new types of solutions for these current issues with ACS.

SamanehSorournejad, Zahra Zojaji, Reza Ebrahimi Atani et al.

Credit card plays a very important rule in today's economy. It becomes an unavoidable part of household, business and global activities. Although using credit cards provides enormous benefits when used carefully and responsibly,significant credit and financial damages may be caused by fraudulent activities. Many techniques have been proposed to confront the growth in credit card fraud. However, all of these techniques have the same goal of avoiding the credit card fraud; each one has its own drawbacks, advantages and characteristics. In this paper, after investigating difficulties of credit card fraud detection, we seek to review the state of the art in credit card fraud detection techniques, data sets and evaluation criteria.The advantages and disadvantages of fraud detection methods are enumerated and compared.Furthermore, a classification of mentioned techniques into two main fraud detection approaches, namely, misuses (supervised) and anomaly detection (unsupervised) is presented. Again, a classification of techniques is proposed based on capability to process the numerical and categorical data sets. Different data sets used in literature are then described and grouped into real and synthesized data and the effective and common attributes are extracted for further usage.Moreover, evaluation employed criterions in literature are collected and discussed.Consequently, open issues for credit card fraud detection are explained as guidelines for new researchers.

Mehran Alidoost Nia, Aida Ghorbani, Reza Ebrahimi Atani

Anonymous cloud architecture provides secure environment for business and also e-commerce approaches. By using this type of architecture, we can propose anonymous online applications. Customers who need secure and reliable online services should pay for provided services. A big problem is electronic payment that is needed for billing customers. But customer identity should be remained anonymous during and also after payment procedure. In this paper we propose a novel and modified anonymous architecture that ensures customers that hide their identity from others. This architecture is used from common network protocols and we eliminate Tor anonymous service from architecture design space because of independency. The here is introduced scalability parameter in anonymous cloud architecture design space. After all we compare proposed architecture with other popular cloud architectures in this range and we obtain its advantages according to efficiency, security and anonymity.

Mona Pourghasem, Elham Ghare Sheikhloo, Reza Ebrahimi Atani

In today's world the use of computer and telecommunications networking is essential for human life. Among these, mobile tools and devices due to availability, have found a special impact on everyone life. This feature addition to providing sample facilities such as financial transactions at any place and time has raised the Sensitivities about security of these devices. In order to provide security, numerous techniques have been proposed which due to the limitations of mobile devices; an algorithm should be taken that have the ability to function for light weight ubiquitous computing. In this paper, four eSTREAM candidates from software profile were taken into account and analyzed and implemented by using J2ME technology. Then these algorithms were implemented on a variety of mobile phones and are compared with each other in terms of execution time and finally the obtained Results are expressed.