CARRADS: Cross layer based adaptive real-time routing attack detection system for MANETS

2010 ◽  
Vol 54 (7) ◽  
pp. 1126-1141 ◽  
Author(s):  
John Felix Charles Joseph ◽  
Amitabha Das ◽  
Bu-Sung Lee ◽  
Boon-Chong Seet
Keyword(s):  
Real Time ◽  
Detection System ◽  
Attack Detection ◽  
Cross Layer ◽  
Routing Attack

scholarly journals Design a Monitoring Device for Heart-Attack Early Detection Based on Respiration Rate and Body Temperature Parameters

2021 ◽  
Vol 3 (3) ◽  
pp. 114-120
Author(s):  
Isna Fatimatuz Zahra ◽  
I Dewa Gede Hari Wisana ◽  
Priyambada Cahya Nugraha ◽  
Hayder J Hassaballah
Keyword(s):  
Body Temperature ◽  
Real Time ◽  
Respiration Rate ◽  
Heart Attack ◽  
Detection System ◽  
Warning System ◽  
Piezoelectric Sensor ◽  
Attack Detection ◽  
Sensor Data ◽  
Frequency Module

Acute myocardial infarction, commonly referred to as a heart attack, is the most common cause of sudden death where a monitoring tool is needed that is equipped with a system that can notify doctors to take immediate action. The purpose of this study was to design a heart attack detection device through indicators of vital human signs. The contribution of this research is that the system works in real-time, has more parameters, uses wireless, and is equipped with a system to detect indications of a heart attack. In order for wireless monitoring to be carried out in real-time and supported by a detection system, this design uses a radio frequency module as data transmission and uses a warning system that is used for detection. Respiration rate was measured using the piezoelectric sensor, and body temperature was measured using the DS18B20 temperature sensor. Processing of sensor data is done with ESP32, which is displayed wirelessly by the HC-12 module on the PC. If an indication of a heart attack is detected in the parameter value, the tool will activate a notification on the PC. In every indication of a heart attack, it was found that this design can provide notification properly. The results showed that the largest respiratory error value was 4%, and the largest body temperature error value was 0.55%. The results of this study can be implemented in patients who have been diagnosed with heart attack disease so that it can facilitate monitoring the patient's condition.

Real-Time Position Falsification Attack Detection System for Internet of Vehicles

2021 ◽  
Author(s):  
Goodness Oluchi Anyanwu ◽  
Cosmas Ifeanyi Nwakanma ◽  
Jae-Min Lee ◽  
Dong-Seong Kim
Keyword(s):  
Real Time ◽  
Detection System ◽  
Attack Detection ◽  
Internet Of Vehicles ◽  
Time Position

ContainerGuard: A Real-Time Attack Detection System in Container-based Big Data Platform

2020 ◽  
pp. 1-1
Author(s):  
Yulong Wang ◽  
Qixu Wang ◽  
Xingshu Chen ◽  
Dajiang Chen ◽  
Xiaojie Fang ◽  
...  
Keyword(s):  
Big Data ◽  
Real Time ◽  
Detection System ◽  
Attack Detection ◽  
Data Platform

scholarly journals Near-Real-Time IDS for the U.S. FAA’s NextGen ADS-B

2021 ◽  
Vol 5 (2) ◽  
pp. 27
Author(s):  
Dustin M. Mink ◽  
Jeffrey McDonald ◽  
Sikha Bagui ◽  
William B. Glisson ◽  
Jordan Shropshire ◽  
...  
Keyword(s):  
Real Time ◽  
Learning Algorithm ◽  
Detection System ◽  
Attack Detection ◽  
Support Vector ◽  
Network Attack ◽  
Ground Station ◽  
Traffic Systems ◽  
Attack Mitigation ◽  
The U.S

Modern-day aircraft are flying computer networks, vulnerable to ground station flooding, ghost aircraft injection or flooding, aircraft disappearance, virtual trajectory modifications or false alarm attacks, and aircraft spoofing. This work lays out a data mining process, in the context of big data, to determine flight patterns, including patterns for possible attacks, in the U.S. National Air Space (NAS). Flights outside the flight patterns are possible attacks. For this study, OpenSky was used as the data source of Automatic Dependent Surveillance-Broadcast (ADS-B) messages, NiFi was used for data management, Elasticsearch was used as the log analyzer, Kibana was used to visualize the data for feature selection, and Support Vector Machine (SVM) was used for classification. This research provides a solution for attack mitigation by packaging a machine learning algorithm, SVM, into an intrusion detection system and calculating the feasibility of processing US ADS-B messages in near real time. Results of this work show that ADS-B network attacks can be detected using network attack signatures, and volume and velocity calculations show that ADS-B messages are processable at the scale of the U.S. Next Generation (NextGen) Air Traffic Systems using commodity hardware, facilitating real time attack detection. Precision and recall close to 80% were obtained using SVM.

scholarly journals Integration of Low Interaction Honeypot and ELK Stack as Attack Detection Systems on Servers

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Fransiska Sisilia Mukti ◽  
R. Muhammad Sukmawan
Keyword(s):  
Information Technology ◽  
Comparative Study ◽  
Real Time ◽  
Delay Time ◽  
Detection System ◽  
Attack Detection ◽  
Average Delay ◽  
Visualization System ◽  
Detection Systems ◽  
System Solution

The high need for information technology that can be accessed anywhere and anytime indirectly opens a big opportunity for irresponsible parties to attack and destroy the system. The server farm is one of the targets most hunted by attackers, intending to damage, and even retrieving victim data. One of the efforts to deal with this problem is to add server security by using honeypot. The existence of a honeypot is one of the efforts to prevent system hacking by creating a fake server to divert attackers access. In its application, the logs generated from the honeypot are only letters and numbers, making it difficult to analyze the logs. It became a problem it will being a lot of log data being processed. To make it easier for administrators in analyzing logs, a visualization system using the ELK Stack is proposed. Honeypot and ELK Stack integration can be a security system solution in detecting attacks while providing visualization to administrators. Five testing schemes were carried out to provide a comparative study between the low interaction honeypot Cowrie and Dionaea. Cowrie delivers a better performance detection system (real-time) compared to the detection system offered by Dionaea, and the average delay time is 3.75 seconds, while ELK managed to provide better monitoring results to administrators through its visualization.

scholarly journals A Real-time Cache side-channel attack detection system on RISC-V Out-of-order processor

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Anh-Tien Le ◽  
Trong-Thuc Hoang ◽  
Ba-Anh Dao ◽  
Akira Tsukamoto ◽  
Kuniyasu Suzaki ◽  
...  
Keyword(s):  
Real Time ◽  
Detection System ◽  
Attack Detection ◽  
Side Channel ◽  
Side Channel Attack

scholarly journals CNN Based Real-Time DNS DDoS Attack Detection System

2017 ◽  
Vol 6 (3) ◽  
pp. 135-142 ◽  
Author(s):  
In Hyuk Seo ◽  
Ki-Taek Lee ◽  
Jinhyun Yu ◽  
Seungjoo Kim
Keyword(s):  
Real Time ◽  
Detection System ◽  
Attack Detection ◽  
Ddos Attack ◽  
Ddos Attack Detection
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