Results 41 to 50 of about 6,155,073 (227)
To the Editor: In a recent article (1), Kaplan et al. addressed the problems in detecting a bioterror attack from blood-donor screening. The main point of this comment is the "early approximation" used by Kaplan et al. to derive the probability of detecting an attack. The simplification used by Kaplan et al. leads to a probability that does not account
Edward H. Kaplan, Lawrence M. Wein
openaire +5 more sources
Controller Cyber-Attack Detection and Isolation
This article deals with the cyber security of industrial control systems. Methods for detecting and isolating process faults and cyber-attacks, consisting of elementary actions named “cybernetic faults” that penetrate the control system and destructively affect its operation, are analysed. FDI fault detection and isolation methods and the assessment of
Anna Sztyber-Betley +3 more
openaire +3 more sources
G-IDCS: Graph-Based Intrusion Detection and Classification System for CAN Protocol
The security of in-vehicle networks has become an important issue as automobiles become more connected and automated. In this paper, we propose a graph-based intrusion detection and classification system, named G-IDCS, which aims to enhance the security ...
Sung Bum Park, Hyo Jin Jo, Dong Hoon Lee
doaj +1 more source
Modeling and Detecting False Data Injection Attacks against Railway Traction Power Systems [PDF]
Modern urban railways extensively use computerized sensing and control technologies to achieve safe, reliable, and well-timed operations. However, the use of these technologies may provide a convenient leverage to cyber-attackers who have bypassed the ...
Lakshminarayana, Subhash +3 more
core +2 more sources
A Novel Web Attack Detection System for Internet of Things via Ensemble Classification
Internet of Things (IoT) has become one of the fastest-growing technologies and has been broadly applied in various fields. IoT networks contain millions of devices with the capability of interacting with each other and providing functionalities that ...
Chaochao Luo +5 more
semanticscholar +1 more source
Attack Detection in IoT using Machine Learning
Many researchers have examined the risks imposed by the Internet of Things (IoT) devices on big companies and smart towns. Due to the high adoption of IoT, their character, inherent mobility, and standardization limitations, smart mechanisms, capable of ...
M. Anwer +3 more
semanticscholar +1 more source
LSTM-Based Collaborative Source-Side DDoS Attack Detection
As denial of service attacks become more sophisticated, the source-side detection techniques are being studied to solve the limitations of target-side detection techniques such as delayed detection and difficulty in tracking attackers.
Sungwoong Yeom +2 more
doaj +1 more source
Low-Rate DDoS Attack Detection Based on Factorization Machine in Software Defined Network
As the Software Define Network (SDN) adopts centralized control logic, it is vulnerable to various types of Distributed Denial of Service (DDoS) attacks.
Wu Zhijun +4 more
doaj +1 more source
Wormhole attack detection techniques in ad-hoc network: A systematic review
Mobile ad hoc networks (MANETs) are considered as decentralized networks, which can communicate without pre-existing infrastructure. Owning to utilization of open medium access and dynamically changing network topology, MANETs are vulnerable to different
Gupta Chitvan +2 more
doaj +1 more source
Recurrent and Deep Learning Neural Network Models for DDoS Attack Detection
Distributed denial of service (DDoS) attack is a subclass of denial of service attack that performs severe attack in a cloud computing environment. It makes a malicious attempt to disturb the usual services of any network or server by using botnets ...
S. Sumathi, R. Rajesh, Sang-Kug Lim
semanticscholar +1 more source

