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Security and Privacy of Lightning Network Payments with Uncertain Channel Balances
Applying negative Bernoulli trials for single- and multi-part payments allows us to compute the expected number of payment attempts for a given amount, sender, and receiver.
Cryptography and Security
MiniCPS: A toolkit for security research on CPS Networks
While a great amount of research has been conducted on network security of office and home networks, recently the security of CPS and related systems has gained a lot of attention.
Networking and Internet Architecture Cryptography and Security
Provably Secure Networks: Methodology and Toolset for Configuration Management
Network administration is an inherently complex task, in particular with regard to security.
Networking and Internet Architecture Cryptography and Security
Evaluating Shallow and Deep Neural Networks for Network Intrusion Detection Systems in Cyber Security
In this paper, DNNs have been utilized to predict the attacks on Network Intrusion Detection System (N-IDS).
Ranked #1 on
Network Intrusion Detection
on KDD
Formal Security Analysis of Neural Networks using Symbolic Intervals
In this paper, we present a new direction for formally checking security properties of DNNs without using SMT solvers.
MobileAtlas: Geographically Decoupled Measurements in Cellular Networks for Security and Privacy Research
Thus, there is a need for controlled testbeds and measurement tools for cellular access networks doing justice to the technology's unique structure and global scope.
Networking and Internet Architecture Cryptography and Security
SecDD: Efficient and Secure Method for Remotely Training Neural Networks
We leverage what are typically considered the worst qualities of deep learning algorithms - high computational cost, requirement for large data, no explainability, high dependence on hyper-parameter choice, overfitting, and vulnerability to adversarial perturbations - in order to create a method for the secure and efficient training of remotely deployed neural networks over unsecured channels.
Nitriding: A tool kit for building scalable, networked, secure enclaves
Enclave deployments often fail to simultaneously be secure (e. g., resistant to side channel attacks), powerful (i. e., as fast as an off-the-shelf server), and flexible (i. e., unconstrained by development hurdles).
Cryptography and Security
Lifting Network Protocol Implementation to Precise Format Specification with Security Applications
It is well-known that static analysis does not rely on any input packets and can achieve high coverage by scanning every piece of code.
Cryptography and Security Programming Languages
Security Analysis of Deep Neural Networks Operating in the Presence of Cache Side-Channel Attacks
Based on the extracted architecture attributes, we also demonstrate that an attacker can build a meta-model that accurately fingerprints the architecture and family of the pre-trained model in a transfer learning setting.
