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DETECTION, TECHNICAL ANALYSIS AND SOLUTION OF TESLACRYPT RANSOMWARE VIRUS

Year 2018, Volume: 2 Issue: 2, 87 - 94, 28.12.2018

Abstract

Although the rapid developments in information
technologies have facilitated numerous things in the lives of Internet users,
these developments also allow malicious people to reach their goals faster.
Malicious software that completely drift away from their initial design goal
are now being designed by professional criminals for a wide range of
applications from cyber terrorism to ransom demands. These criminals reach
their goals easily by developing a variety of methods and tactics, and the
possibility of being exposed to this situation becomes the worst nightmare for
the users. Recently, a new generation of Ransomware, known as TeslaCrypt, has
begun to be seen worldwide. TeslaCrypt reaches users through e-mail and
encrypts many files in the system after execution of its payload found in the
e-mail attachment. It demands ransom to allow access to encrypted files of the
user. Although there are continuing works to find a solution to this problem
caused by TeslaCrypt, there is still no definitive solution. This study
discusses the detection of TeslaCrypt threat, and technical analysis on its
infiltration into the target system and file-directory actions in the system
and solution. The analysis has been performed by both static and dynamic
methods. As a result of the study, it was shown that the passwords caused by
the ransomware virus broke the password.

References

  • Aloul, F. A. (2012). The need for effective information security awareness. Journal of Advances in Information Technology, 3(3), 176-183.
  • Aurangzeb, S., Aleem, M., Iqbal, M. A., & Islam, M. A. (2017). Ransomware: A Survey and Trends. Journal of Information Assurance & Security, 6(2).
  • Bassett, R., Bass, L., & O'Brien, P. (2006). Computer forensics: An essential ingredient for cyber security. Journal of Information Science & Technology, 3(1).
  • Bhardwaj, A., Avasthi, V., Sastry, H., & Subrahmanyam, G. V. B. (2016). Ransomware digital extortion: a rising new age threat. Indian Journal of Science and Technology, 9(14), 1-5.
  • Feizollah, A., Anuar, N. B., Salleh, R., Suarez-Tangil, G., & Furnell, S. (2017). Androdialysis: Analysis of android intent effectiveness in malware detection. computers & security, 65, 121-134.
  • Garg, D., Thakral, A., Nalwa, T., & Choudhury, T. (2018). A Past Examination and Future Expectation: Ransomware. In 2018 International Conference on Advances in Computing and Communication Engineering (ICACCE) (pp. 243-247). IEEE.
  • Kara, İ., (2015). Türkiye de Zararlı Yazılımlarla Mücadelenin Uygulama Ve Hukuki Boyutunun Değerlendirilmesi. Akademik Bakış Uluslararası Hakemli Sosyal Bilimler Dergisi 52: 87-98.
  • Luo, X., & Liao, Q. (2007). Awareness education as the key to ransomware prevention. Information Systems Security, 16(4), 195-202.
  • Salz, J., Balakrishnan, H., & Snoeren, A. C. (2003). TESLA: A Transparent, Extensible Session-Layer Architecture for End-to-end Network Services. In USENIX Symposium on Internet Technologies and Systems.
  • Shen, J., Gong, S., & Bao, W. (2018). Analysis of Network Security in Daily Life. Information and Computer Security, 1(1).
  • Richardson, R., & North, M. (2017). Ransomware: Evolution, mitigation and prevention. International Management Review, 13(1), 10-21.
  • Rieck, K., Trinius, P., Willems, C., & Holz, T. (2011). Automatic analysis of malware behavior using machine learning. Journal of Computer Security, 19(4), 639-668.
  • Villeneuve, N. (2015). TeslaCrypt: Following the Money Trail and Learning the Human Costs of Ransomware. Threat Research Blog.
  • Yaqoob, I., Ahmed, E., ur Rehman, M. H., Ahmed, A. I. A., Al-garadi, M. A., Imran, M., & Guizani, M. (2017). The rise of ransomware and emerging security challenges in the Internet of Things. Computer Networks, 129, 444-458.
  • Zheng, B., Zhu, L., Shen, M., Du, X., Yang, J., Gao, F., ... & Yin, S. (2017). Malicious Bitcoin Transaction Tracing Using Incidence Relation Clustering. In International Conference on Mobile Networks and Management (pp. 313-323). Springer, Cham.

TESLACRYPT FİDYE YAZILIM VİRÜSÜNÜN TESPİTİ, TEKNİK ANALİZİ VE ÇÖZÜMÜ

Year 2018, Volume: 2 Issue: 2, 87 - 94, 28.12.2018

Abstract

Bilişim teknolojilerinde yaşanan hızlı
gelişmeler internet kullanıcılarının hayatında pek çok şeyi kolaylaştırmışken,
kötü niyetli kişilerinde amaçlarına daha hızlı ulaşması için yeni olanaklar
sağlamaktadır. İlk tasarım amacından tamamen uzaklaşan zararlı yazılımlar,
günümüzde profesyonel suçlular tarafından siber terörizmden fidye istemeye
kadar geniş bir uygulama alanı için tasarlanmaktadır. Bu suçlular çok çeşitli
yöntemler ve taktikler geliştirerek amaçlarına kolaylıkla ulaşmakta, bu duruma
maruz kalma olasılığı kullanıcıların korkulu rüyası haline gelmektedir. Son
günlerde dünya genelinde TeslaCrypt olarak adlandırılan yeni nesil fidye
yazılım siber saldırı vakaları görülmeye başlamıştır. TeslaCrypt, kullanıcılara
e-mail yoluyla ulaşarak ekinde bulunan zararlı yazılımın çalıştırılması ile
sistemdeki birçok dosyayı şifrelemektedir. Kullanıcının şifrelenmiş dosyalara
erişim sağlayabilmesi için fidye göndermesini istemektedir. TeslaCrypt’nin
sebep olduğu bu durum için çalışmalar devam etmekle birlikte hala kesin çözüm
bulunamamıştır. Bu çalışma, TeslaCrypt tehditinin tespiti, hedef sisteme sızma,
sistemdeki dosya-dizin hareketlerinin teknik analizini ve çözümünü içermektedir.
İncelemeler; hem statik hem de dinamik yöntemlerle gerçekleştirilmiştir. Çalışma
sonucunda fidye yazılımının neden olduğu şifrelerin kırılabilir olduğu
gösterilmiştir.

References

  • Aloul, F. A. (2012). The need for effective information security awareness. Journal of Advances in Information Technology, 3(3), 176-183.
  • Aurangzeb, S., Aleem, M., Iqbal, M. A., & Islam, M. A. (2017). Ransomware: A Survey and Trends. Journal of Information Assurance & Security, 6(2).
  • Bassett, R., Bass, L., & O'Brien, P. (2006). Computer forensics: An essential ingredient for cyber security. Journal of Information Science & Technology, 3(1).
  • Bhardwaj, A., Avasthi, V., Sastry, H., & Subrahmanyam, G. V. B. (2016). Ransomware digital extortion: a rising new age threat. Indian Journal of Science and Technology, 9(14), 1-5.
  • Feizollah, A., Anuar, N. B., Salleh, R., Suarez-Tangil, G., & Furnell, S. (2017). Androdialysis: Analysis of android intent effectiveness in malware detection. computers & security, 65, 121-134.
  • Garg, D., Thakral, A., Nalwa, T., & Choudhury, T. (2018). A Past Examination and Future Expectation: Ransomware. In 2018 International Conference on Advances in Computing and Communication Engineering (ICACCE) (pp. 243-247). IEEE.
  • Kara, İ., (2015). Türkiye de Zararlı Yazılımlarla Mücadelenin Uygulama Ve Hukuki Boyutunun Değerlendirilmesi. Akademik Bakış Uluslararası Hakemli Sosyal Bilimler Dergisi 52: 87-98.
  • Luo, X., & Liao, Q. (2007). Awareness education as the key to ransomware prevention. Information Systems Security, 16(4), 195-202.
  • Salz, J., Balakrishnan, H., & Snoeren, A. C. (2003). TESLA: A Transparent, Extensible Session-Layer Architecture for End-to-end Network Services. In USENIX Symposium on Internet Technologies and Systems.
  • Shen, J., Gong, S., & Bao, W. (2018). Analysis of Network Security in Daily Life. Information and Computer Security, 1(1).
  • Richardson, R., & North, M. (2017). Ransomware: Evolution, mitigation and prevention. International Management Review, 13(1), 10-21.
  • Rieck, K., Trinius, P., Willems, C., & Holz, T. (2011). Automatic analysis of malware behavior using machine learning. Journal of Computer Security, 19(4), 639-668.
  • Villeneuve, N. (2015). TeslaCrypt: Following the Money Trail and Learning the Human Costs of Ransomware. Threat Research Blog.
  • Yaqoob, I., Ahmed, E., ur Rehman, M. H., Ahmed, A. I. A., Al-garadi, M. A., Imran, M., & Guizani, M. (2017). The rise of ransomware and emerging security challenges in the Internet of Things. Computer Networks, 129, 444-458.
  • Zheng, B., Zhu, L., Shen, M., Du, X., Yang, J., Gao, F., ... & Yin, S. (2017). Malicious Bitcoin Transaction Tracing Using Incidence Relation Clustering. In International Conference on Mobile Networks and Management (pp. 313-323). Springer, Cham.
There are 15 citations in total.

Details

Primary Language Turkish
Subjects Computer Software
Journal Section Articles
Authors

İlker Kara This is me 0000-0003-3700-4825

Publication Date December 28, 2018
Published in Issue Year 2018 Volume: 2 Issue: 2

Cite

APA Kara, İ. (2018). TESLACRYPT FİDYE YAZILIM VİRÜSÜNÜN TESPİTİ, TEKNİK ANALİZİ VE ÇÖZÜMÜ. Uluslararası Yönetim Bilişim Sistemleri Ve Bilgisayar Bilimleri Dergisi, 2(2), 87-94.