Results 31 to 40 of about 42,568 (290)
Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagation [PDF]
, 2022 Graph contrastive learning is the state-of-the-art unsupervised graph representation learning framework and has shown comparable performance with supervised approaches.
Zhang, S, Li, Y, Xu, G, Chen, H, Sun, X
core +1 more source
ATTACK GRAPH ANALYSIS USING -NS2
, 2021 we describe large network environment needs multiple sensors to monitor network traffic. Deploying and managing sensors in network’s demanding task. Attack graph showing all possible paths.
Miss: Vijaya Desai, Mrs: Jyoti Nighot
core +1 more source
An Improved Attack Path Discovery Algorithm Through Compact Graph Planning
IEEE Access, 2019 Attack path discovery plays an important role in protecting network infrastructure. Unfortunately, previous attack path discovery algorithms are difficult for applying in reality because of the high computational complexity problem.
Zang Yichao +3 more
doaj +1 more source
Projective Ranking: A Transferable Evasion Attack Method on Graph Neural Networks
, 2021 Graph Neural Networks (GNNs) have emerged as a series of effective learning methods for graph-related tasks. However, GNNs are shown vulnerable to adversarial attacks, where attackers can fool GNNs into making wrong predictions on adversarial samples ...
Yuan, X +13 more
core +1 more source
Attacker-Parametrised Attack Graphs [PDF]
, 2016 Computer network attackers chain system exploits together to achieve their goals, which range from stealing data to corrupting systems. Attack graphs represent these paths through the network, and provide the basis for calculating many security metrics. In this paper, we seek to extend graph-based analysis from the consideration of single graphs to the
Janse van Rensburg, A +2 more
openaire +1 more source
FEBS Letters, EarlyView.The physical dimensions and shape of bacterial cells define the surface area available to acquire nutrients and the volume available for synthesizing proteins and DNA. Here, we use computational systems biology to decode the importance of cell geometry as a major determinant of prokaryotic phenotype, including growth rate and metabolic efficiency. This
Ross P. Carlson +6 more
wiley +1 more source
A reinforcement learning approach for attack graph analysis [PDF]
, 2018 Attack graph approach is a common tool for the analysis of network security. However, analysis of attack graphs could be complicated and difficult depending on the attack graph size.
Mtetwa, Nhamo +7 more
core +1 more source
The time for reconstructing the attack graph in DDoS attacks
Journal of Mathematical Analysis and ApplicationsDespite their frequency, denial-of-service (DoS\blfootnote{Denial of Service (DoS), Distributed Denial of Service (DDoS), Probabilistic Packet Marking (PPM), coupon collector's problem (CCP)}) and distributed-denial-of-service (DDoS) attacks are difficult to prevent and trace, thus posing a constant threat.
D. Barak-Pelleg, D. Berend
openaire +2 more sources
FEBS Letters, EarlyView.We present robust protocols for the preparation of supported lipid bilayers (SLBs) incorporating either Salmonella smooth LPS or outer membrane vesicles (OMVs). We use a combination of quartz crystal microbalance with dissipation (QCM‐D) and fluorescence microscopy to both characterize the SLBs of various compositions and to probe their interactions ...
Hudson P. Pace +6 more
wiley +1 more source