ISSN 2394-5125
 

Research Article 


SOFTWARE BOT DETECTION BY KEYSTROKE DYNAMICS

Kiran Ahuja, Vinod Todwal.

Abstract
Modern life depends on technologies as communication systems and computing, although have also caused the enhancement in data exposure as well as, thus leading to theft of identity. Biometric technologies become the trending solution of such problems and recommended for user authentication. The assessment of possible technologies to be targeted on keystroke dynamics that makes use recognition depending on their typing rhythm. Interactive Internet applications like online blogs have become popular in the past decade. Currently the most common form of malicious exploit and the most difficult to thwart, is the use of automated programs known as bots to automatically perform human tasks on online applications. Bots have been found on a number of online systems, including online blogging and online social networking. Bots exploit these on-line systems to send spam, spread malware, and mount phishing attacks. Software bots which emulate a web browser are often used by criminals to harvest large amounts of data from websites. They can also abuse websites in other ways, such as by mass-posting adverts or malicious links in comment forms or forums, or by placing large numbers of reservations within, say, an airline booking system in order to prevent legitimate customers from making a booking. Software bots are often used for malicious political intensions as well such as spreading a false tweet. The abuse of online services by bots has caused serious damages and posed serious threats to on-line users. So far, the efforts to combat bots have focused on two different approaches as content-based filtering and human interactive proofs (HIPs).

Key words: Keystroke Dynamics, User Authentication, Typing Rhythm, Pattern Recognition, Artificial Intelligence, Machine Learning


 
ARTICLE TOOLS
Abstract
PDF Fulltext
How to cite this articleHow to cite this article
Citation Tools
Related Records
 Articles by Kiran Ahuja
Articles by Vinod Todwal
on Google
on Google Scholar


How to Cite this Article
Pubmed Style

Kiran Ahuja, Vinod Todwal. SOFTWARE BOT DETECTION BY KEYSTROKE DYNAMICS. JCR. 2020; 7(19): 9975-9982. doi: 10.31838/jcr.07.19.1105


Web Style

Kiran Ahuja, Vinod Todwal. SOFTWARE BOT DETECTION BY KEYSTROKE DYNAMICS. http://www.jcreview.com/?mno=21191 [Access: January 05, 2021]. doi: 10.31838/jcr.07.19.1105


AMA (American Medical Association) Style

Kiran Ahuja, Vinod Todwal. SOFTWARE BOT DETECTION BY KEYSTROKE DYNAMICS. JCR. 2020; 7(19): 9975-9982. doi: 10.31838/jcr.07.19.1105



Vancouver/ICMJE Style

Kiran Ahuja, Vinod Todwal. SOFTWARE BOT DETECTION BY KEYSTROKE DYNAMICS. JCR. (2020), [cited January 05, 2021]; 7(19): 9975-9982. doi: 10.31838/jcr.07.19.1105



Harvard Style

Kiran Ahuja, Vinod Todwal (2020) SOFTWARE BOT DETECTION BY KEYSTROKE DYNAMICS. JCR, 7 (19), 9975-9982. doi: 10.31838/jcr.07.19.1105



Turabian Style

Kiran Ahuja, Vinod Todwal. 2020. SOFTWARE BOT DETECTION BY KEYSTROKE DYNAMICS. Journal of Critical Reviews, 7 (19), 9975-9982. doi: 10.31838/jcr.07.19.1105



Chicago Style

Kiran Ahuja, Vinod Todwal. "SOFTWARE BOT DETECTION BY KEYSTROKE DYNAMICS." Journal of Critical Reviews 7 (2020), 9975-9982. doi: 10.31838/jcr.07.19.1105



MLA (The Modern Language Association) Style

Kiran Ahuja, Vinod Todwal. "SOFTWARE BOT DETECTION BY KEYSTROKE DYNAMICS." Journal of Critical Reviews 7.19 (2020), 9975-9982. Print. doi: 10.31838/jcr.07.19.1105



APA (American Psychological Association) Style

Kiran Ahuja, Vinod Todwal (2020) SOFTWARE BOT DETECTION BY KEYSTROKE DYNAMICS. Journal of Critical Reviews, 7 (19), 9975-9982. doi: 10.31838/jcr.07.19.1105