International Research Journal of Engineering and Technology (IRJET) Volume: 04 Issue: 03 | Mar -2017
www.irjet.net
e-ISSN: 2395 -0056 p-ISSN: 2395-0072
IDENTIFYING MALICIOUS DATA IN SOCIAL MEDIA M.Sai Sri Lakshmi Yellari1, M.Manisha2, J.Dhanesh3 ,M.Srinivasa Rao4 ,Dr.S.Suhasini5 1Student,
Dept. of Information Technology, Velagapudi Ramakrishna Siddhartha Engineering College, Andhra Pradesh, India
2Student,
Dept. of Information Technology, Velagapudi Ramakrishna Siddhartha Engineering College, Andhra Pradesh, India
3Student,
Dept. of Information Technology, Velagapudi Ramakrishna Siddhartha Engineering College, Andhra Pradesh, India
4Student,
Dept. of Information Technology, Velagapudi Ramakrishna Siddhartha Engineering College, Andhra Pradesh, India
5Associate
professor, Dept. of Information Technology, Velagapudi Ramakrishna Siddhartha Engineering College, Andhra Pradesh, India
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Abstract - Network anomaly detection is a broad area of
research. The use of entropy and distributions of traffic features has received a lot of attention in the research community. Disclosing malicious traffic for network security using entropy based approach and power law distribution is proposed. To calculate entropy feature considered is packet size. Malware, most commonly known as malicious data is prevalent, arising a number of critical threat issues. With the increasing volume of contents users share through social media, the user is going to share large amount of information. Using power law distribution malware is detected which the users share in social media by making a comparison with Shannon entropy technique.
Key Words: Social media, Entropy, Malware, Power law, security, traffic.
1. INTRODUCTION A network consists of two or more computers that are linked in order to apportion resources (such as printers and CDs), exchange files, or allow electronic communications. The computers on a network may be linked through cables, telephone lines, radio waves, satellites, or infrared light beams. A network may be composed of any coalescence of LANs, or WANs. Network traffic can be defined in a number of ways. But in the simplest manner we can define it as the density of data present in any Network. Network data security should be a high priority when considering a network setup due to the growing threat of hackers endeavoring to infect as many computers possible. Due to the cumbersomely hefty utilization of the network now a day’s sundry attacks are been occurring and malicious data is injected into the user’s profile or document. Due to lack of security in the organization the data breaches. In this paper, we study the comparison between Entropy based anomaly © 2017, IRJET
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Impact Factor value: 5.181
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detection mechanism and Power law distribution. Entropy based anomaly detection captures more fine grained traffic patterns as compared to normal volume based metrics. Many traffic features such as IP address, port number, flow size etc are considered as attributes is calculating entropy where as Power law (also called the scaling law) states that a relative change in one quantity results in a proportional relative change in another.
1.1 Malicious Data Malicious data is data that, when introduced to a computer—usually by an operator unaware that he or she is doing so—will cause the computer to perform actions undesirable to the computer's owner. Malicious practices done by the local networks users that do not allow efficient sharing of the network resources. Common threats are: Unauthorized Access, Data Destruction, Administrative Access, System Crash/Hardware Failure, Virus. Malware is short for malicious software, denoting software that can be habituated to compromise computer functions, steal data, bypass access controls, or otherwise cause harm to the host computer. Malware is a broad term that refers to a variety of maleficent programs. This post will define several of the most mundane types of malware; adware, bots, bugs, rootkits, spyware, Trojan horses, viruses, and worms.
1.2 Problem Description Online social networks are widely use these days for the purpose of communication. Users can share more type of information among friends. But there exist some social network users who misuse the features of these social networks and promote the spreading of malicious content. They do this by uploading the malicious files. These contents spread at a fast rate. There is no proper mechanism to detect these malicious files immediately and remove it effectively. ISO 9001:2008 Certified Journal
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