An Efficient Detection and Prevention Approach of Unknown Malicious Attack: A Novel Honeypot Approach

2021 ◽  
pp. 11-19
Author(s):  
Aatif Sarfaraz ◽  
Atul Jha ◽  
Avijit Mondal ◽  
Radha Tamal Goswami
Keyword(s):  
Malicious Attack ◽  
Efficient Detection ◽  
Prevention Approach

scholarly journals Efficient Detection of Link-Flooding Attacks with Deep Learning

2021 ◽  
Vol 13 (22) ◽  
pp. 12514
Author(s):  
Chih-Hsiang Hsieh ◽  
Wei-Kuan Wang ◽  
Cheng-Xun Wang ◽  
Shi-Chun Tsai ◽  
Yi-Bing Lin
Keyword(s):  
Deep Learning ◽  
Network Architecture ◽  
Defense Mechanism ◽  
Monitoring Network ◽  
Ddos Attacks ◽  
Malicious Attack ◽  
Ddos Attack ◽  
Efficient Detection ◽  
Flooding Attacks ◽  
The Difference

The DDoS attack is one of the most notorious attacks, and the severe impact of the DDoS attack on GitHub in 2018 raises the importance of designing effective defense methods for detecting this type of attack. Unlike the traditional network architecture that takes too long to cope with DDoS attacks, we focus on link-flooding attacks that do not directly attack the target. An effective defense mechanism is crucial since as long as a link-flooding attack is undetected, it will cause problems over the Internet. With the flexibility of software-defined networking, we design a novel framework and implement our ideas with a deep learning approach to improve the performance of the previous work. Through rerouting techniques and monitoring network traffic, our system can detect a malicious attack from the adversary. A CNN architecture is combined to assist in finding an appropriate rerouting path that can shorten the reaction time for detecting DDoS attacks. Therefore, the proposed method can efficiently distinguish the difference between benign traffic and malicious traffic and prevent attackers from carrying out link-flooding attacks through bots.

Efficient Detection of Suspected areas in Mammographic Breast Cancer Images

2015 ◽  
Vol 1 (4) ◽  
pp. 1-10 ◽  
Author(s):  
Bhagwati Charan Patel ◽  
◽  
Dr.G.R. Sinha ◽  
Keyword(s):  
Breast Cancer ◽  
Efficient Detection

scholarly journals Online Judging Platform Utilizing Dynamic Plagiarism Detection Facilities

Computers ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 47
Author(s):  
Fariha Iffath ◽  
A. S. M. Kayes ◽  
Md. Tahsin Rahman ◽  
Jannatul Ferdows ◽  
Mohammad Shamsul Arefin ◽  
...  
Keyword(s):  
Source Code ◽  
Large Data ◽  
Large Data Sets ◽  
Detection Technique ◽  
Data Sets ◽  
Plagiarism Detection ◽  
Source Codes ◽  
Efficient Detection ◽  
Mathematical Problems ◽  
Automatic Scoring

A programming contest generally involves the host presenting a set of logical and mathematical problems to the contestants. The contestants are required to write computer programs that are capable of solving these problems. An online judge system is used to automate the judging procedure of the programs that are submitted by the users. Online judges are systems designed for the reliable evaluation of the source codes submitted by the users. Traditional online judging platforms are not ideally suitable for programming labs, as they do not support partial scoring and efficient detection of plagiarized codes. When considering this fact, in this paper, we present an online judging framework that is capable of automatic scoring of codes by detecting plagiarized contents and the level of accuracy of codes efficiently. Our system performs the detection of plagiarism by detecting fingerprints of programs and using the fingerprints to compare them instead of using the whole file. We used winnowing to select fingerprints among k-gram hash values of a source code, which was generated by the Rabin–Karp Algorithm. The proposed system is compared with the existing online judging platforms to show the superiority in terms of time efficiency, correctness, and feature availability. In addition, we evaluated our system by using large data sets and comparing the run time with MOSS, which is the widely used plagiarism detection technique.

scholarly journals Highly-Efficient Sulfonated UiO-66(Zr) Optical Fiber for Rapid Detection of Trace Levels of Pb2+

2021 ◽  
Vol 22 (11) ◽  
pp. 6053
Author(s):  
Marziyeh Nazari ◽  
Abbas Amini ◽  
Nathan T. Eden ◽  
Mikel C. Duke ◽  
Chun Cheng ◽  
...  
Keyword(s):  
Optical Fiber ◽  
Rapid Detection ◽  
Chemical Sensor ◽  
Metal Organic Framework ◽  
Aqueous System ◽  
Icp Oes ◽  
Efficient Detection ◽  
Low Concentrations ◽  
Fabry Perot ◽  
Metal Organic

Lead detection for biological environments, aqueous resources, and medicinal compounds, rely mainly on either utilizing bulky lab equipment such as ICP-OES or ready-made sensors, which are based on colorimetry with some limitations including selectivity and low interference. Remote, rapid and efficient detection of heavy metals in aqueous solutions at ppm and sub-ppm levels have faced significant challenges that requires novel compounds with such ability. Here, a UiO-66(Zr) metal-organic framework (MOF) functionalized with SO3H group (SO3H-UiO-66(Zr)) is deposited on the end-face of an optical fiber to detect lead cations (Pb2+) in water at 25.2, 43.5 and 64.0 ppm levels. The SO3H-UiO-66(Zr) system provides a Fabry–Perot sensor by which the lead ions are detected rapidly (milliseconds) at 25.2 ppm aqueous solution reflecting in the wavelength shifts in interference spectrum. The proposed removal mechanism is based on the adsorption of [Pb(OH2)6]2+ in water on SO3H-UiO-66(Zr) due to a strong affinity between functionalized MOF and lead. This is the first work that advances a multi-purpose optical fiber-coated functional MOF as an on-site remote chemical sensor for rapid detection of lead cations at extremely low concentrations in an aqueous system.

DAP: Efficient Detection Against Probabilistic Cloning Attacks in Anonymous RFID Systems

2021 ◽  
pp. 1-1
Author(s):  
Honglong Chen ◽  
Xin Ai ◽  
Kai Lin ◽  
Na Yan ◽  
Zhibo Wang ◽  
...  
Keyword(s):  
Rfid Systems ◽  
Efficient Detection
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