相关论文: Pacer: Comprehensive Network Side-Channel Mitigati…

This work focuses on eliminating timing-side channels in real-time safety-critical cyber-physical network protocols like Controller Area Networks (CAN). Automotive Electronic Control Units (ECUs) implement predictable scheduling decisions…

Deep learning is gaining importance in many applications. However, Neural Networks face several security and privacy threats. This is particularly significant in the scenario where Cloud infrastructures deploy a service with Neural Network…

This paper discusses that there is significant benefit in providing stronger security at lower layers of the network stack for hosts connected to a network. It claims to reduce the attack vulnerability of a networked host by providing…

Monitoring is an essential aspect of maintaining and developing computer systems that increases in difficulty proportional to the size of the system. The need for robust monitoring tools has become more evident with the advent of cloud…

This paper studies the problem of transmitting multiple independent layered video streams over single-hop wireless networks using network coding (NC). We combine feedback-free random linear NC (RLNC) with unequal error protection (UEP) and…

Payment channel networks (PCNs) are viewed as one of the most promising scalability solutions for cryptocurrencies today. Roughly, PCNs are networks where each node represents a user and each directed, weighted edge represents funds…

Centralized Virtual Private Networks (VPNs) when used in distributed systems have performance constraints as all traffic must traverse through a central server. In recent years, there has been a paradigm shift towards the use of P2P in VPNs…

Transport layer data leaks metadata unintentionally -- such as who communicates with whom. While tools for strong transport layer privacy exist, they have adoption obstacles, including performance overheads incompatible with mobile devices.…

The paper demonstrates how traffic load of a shared packet queue can be exploited as a side channel through which protected information leaks to an off-path attacker. The attacker sends to a victim a sequence of identical spoofed segments.…

We propose a novel and effective purification based adversarial defense method against pre-processor blind white- and black-box attacks. Our method is computationally efficient and trained only with self-supervised learning on general…

Cybersecurity continues to be a difficult issue for society especially as the number of networked systems grows. Techniques to protect these systems range from rules-based to artificial intelligence-based intrusion detection systems and…

Motivated by privacy issues caused by inference attacks on user activities in the packet sizes and timing information of Internet of Things (IoT) network traffic, we establish a rigorous event-level differential privacy (DP) model on…

Secure multi-party computation (MPC) facilitates privacy-preserving computation between multiple parties without leaking private information. While most secure deep learning techniques utilize MPC operations to achieve feasible…

The emergence of programmable switches has brought in-network computing (INC) into the spotlight in recent years. By offloading computation directly onto the data transmission process, INC improves network utilization, reduces latency to…

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,…

Cloud computing, offering on-demand access to computing resources through the Internet and the pay-as-you-go model, has marked the last decade with its three main service models; Infrastructure as a Service (IaaS), Platform as a Service…

This paper considers the secretive coded caching problem with shared caches in which no user must have access to the files that it did not demand. In a shared cache network, the users are served by a smaller number of helper caches and each…

This paper proposes Concurrent-Access Obfuscated Store (CAOS), a construction for remote data storage that provides access-pattern obfuscation in a honest-but-curious adversarial model, while allowing for low bandwidth overhead and client…

Dataset condensation aims to synthesize compact yet informative datasets that retain the training efficacy of full-scale data, offering substantial gains in efficiency. Recent studies reveal that the condensation process can be vulnerable…

We analyze the performance of TCP and TCP with network coding (TCP/NC) in lossy wireless networks. We build upon the simple framework introduced by Padhye et al. and characterize the throughput behavior of classical TCP as well as TCP/NC as…