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Although Large Language Models (LLMs) have become increasingly integral to diverse applications, their capabilities raise significant privacy concerns. This survey offers a comprehensive overview of privacy risks associated with LLMs and…

In the rapidly evolving landscape of artificial intelligence, multimodal learning systems (MMLS) have gained traction for their ability to process and integrate information from diverse modality inputs. Their expanding use in vital sectors…

As artificial intelligence, machine learning, and data science continue to drive the data-centric economy, the challenges of implementing machine learning on a single machine due to extensive data and computational needs have led to the…

Textual data is often represented as real-numbered embeddings in NLP, particularly with the popularity of large language models (LLMs) and Embeddings as a Service (EaaS). However, storing sensitive information as embeddings can be…

Merging Large Language Models (LLMs) is a cost-effective technique for combining multiple expert LLMs into a single versatile model, retaining the expertise of the original ones. However, current approaches often overlook the importance of…

In this paper we study different options for the survivability implementation in MPLS over Optical Transport Networks (OTN) in terms of network resource usage and configuration cost. We investigate two approaches to the survivability…

-Multipath communications at the Internet scale have been a myth for a long time, with no actual protocol being deployed so that multiple paths could be taken by a same connection on the way towards an Internet destination. Recently, the…

Mobile Large Language Models (LLMs) are revolutionizing diverse fields such as healthcare, finance, and education with their ability to perform advanced natural language processing tasks on-the-go. However, the deployment of these models in…

Secure Multi-Party Computation (MPC) is an important enabling technology for data privacy in modern distributed applications. Currently, proof methods for low-level MPC protocols are primarily manual and thus tedious and error-prone, and…

Current trends in technology, such as cloud computing, allow outsourcing the storage, backup, and archiving of data. This provides efficiency and flexibility, but also poses new risks for data security. It in particular became crucial to…

The security evaluation for Mail Distribution Systems focuses on certification and reliability of sensitive data between mail servers. The need to certify the information conveyed is a result of known weaknesses in the simple mail transfer…

The MPLS Network Actions (MNA) framework enhances MPLS forwarding with a generalized encoding for manifold extensions such as network slicing and in-situ OAM (IOAM). Network actions in MNA are encoded in Label Stack Entries (LSEs) and are…

Despite the rapid advancements of Large Language Models (LLMs), safety risks remain a critical challenge for low-resource languages. Existing safety datasets are predominantly English centric, limiting progress in multilingual safety…

Multi-task learning (MTL) refers to the paradigm of learning multiple related tasks together. In contrast, in single-task learning (STL) each individual task is learned independently. MTL often leads to better trained models because they…

Machine Learning (ML) has emerged as a pivotal technology in the operation of large and complex systems, driving advancements in fields such as autonomous vehicles, healthcare diagnostics, and financial fraud detection. Despite its…

l. Introduction Modern network are multi-layer by their structure. This requires the development of new mathematical models, which would allow to adequately describe the existing physical and logical connections between the elements on its…

Cloud computing has brought a revolution in the field of information technology and improving the efficiency of computational resources. It offers computing as a service enabling huge cost and resource efficiency. Despite its advantages,…

Many machine learning and data mining algorithms rely on the assumption that the training and testing data share the same feature space and distribution. However, this assumption may not always hold. For instance, there are situations where…

Security has emerged as one of the critical requirements in future wireless networks. Unlike traditional cryptography-based security, physical layer security (PLS) exploits various features of the random wireless channel to secure not only…

Encrypted traffic poses new and unique challenges for network operators because information that is useful or necessary for management purposes is not accessible anymore. This paper examines proposed approaches to provide end-to-end…