000 07572nam a22002537a 4500
008 210125b2019 a|||f bm|| 00| 0 eng d
040 _aEG-CaNU
_cEG-CaNU
041 0 _aeng
_beng
082 _a658
100 0 _aMay Medhat Mohamed
_9306
245 1 _aA New Static-Based Framework for Ransomware Detection
_cMay Medhat Mohamed
260 _c2019
300 _a73 p.
_bill.
_c21 cm.
500 _3Supervisor: Nashwa Abd El-Baki
502 _aThesis (M.A.)—Nile University, Egypt, 2019 .
504 _a"Includes bibliographical references"
505 0 _aContents: Abstract ........................................................................................................................................... v Acknowledgments .......................................................................................................................... vii Ransomware................................................................................................................................... 1 1.1 Ransomware Types.............................................................................................................. 1 1.2 Ransomware infection vectors ............................................................................................ 3 1.3 Ransomware Attack............................................................................................................. 4 1.3.1 Ransomware Infection Execution .................................................................................... 5 1.3.2 Ransomware targeted files.............................................................................................. 5 1.3.3 Ransomware encryption process .................................................................................... 5 1.4 Conclusion ........................................................................................................................... 6 Background and Related Works ...................................................................................................... 7 2.1 Ransomware analysis .......................................................................................................... 7 2.1.1 Static analysis .................................................................................................................. 7 2.1.2 Dynamic analysis ............................................................................................................. 8 2.1.3 Hybrid analysis ................................................................................................................. 8 2.1.4 Research analysis and detection technique .................................................................... 9 2.2 Related Work ....................................................................................................................... 9 2.2.1 Ransomware evolution .................................................................................................... 9 2.2.2 Ransomware vs Crypto-Currencies ............................................................................... 10 2.2.3 Ransomware as a service (RAAS) .................................................................................. 12 2.2.4 Ransomware vs Phones ................................................................................................. 12 2.2.5 Ransomware vs Internet of things (IOT)........................................................................ 13 2.2.6 Ransomware analysis and detection ............................................................................. 13 2.2.7 Ransomware mitigation ................................................................................................ 18 2.2.8 Ransomware recovery ................................................................................................... 20 2.2.9 Ransomware research directions summary .................................................................. 20 2.3 Research problem statement ............................................................................................ 21 2.4 Conclusion ......................................................................................................................... 22 Ransomware detection framework .............................................................................................. 25 3.1 Data set selection .............................................................................................................. 25 3.2 Features selection ............................................................................................................. 28 3.3 Ransomware detection framework ................................................................................... 33 3.4 Framework Case Studies ................................................................................................... 36 3.4.1 BadRabbit ransomware case ......................................................................................... 36 3.4.2 Cryakl ransomware case ................................................................................................ 39 3.5 Conclusion ......................................................................................................................... 41 Framework Evaluation .................................................................................................................. 43 4.1 Framework Performance Metrics ..................................................................................... 43 4.2 Training set results ............................................................................................................ 45 4.3 Testing set results .............................................................................................................. 70 4.4 Framework results comparison ......................................................................................... 73 Conclusions and Future Work ....................................................................................................... 75 Bibliography ............................
520 3 _aAbstract: Nowadays, ransomware attacks are increasing rapidly. They damage critical infrastructures and organizations all over the world. Ransomware main target is encrypting important files on the targeted victim machine using encryption techniques to encrypt important files. Subsequently, a ransom-note displayed to the victim requesting payment to attacker in order to get the decryption key. Hence, ransomware attacks detection and prevention become crucial challenges for information security researchers. This research presents new rule-based detection framework for ransomware attacks. The decision rules of the presented framework are relying on static properties acquired from ransomware files. Once the scanned sample reached the threshold specified by rules, logical operations evaluates the triggered rule. Based on the logical operations results, a score is given to each file. Score given for each sample represents the certainty whether this file can be classified as a ransomware or not. Scores assigned to samples can be from critical to low. Various ransomware families have been detected with high accuracy and detection ratio using the presented framework.
546 _aText in English, abstracts in English.
650 4 _aInformation Security
_9294
655 7 _2NULIB
_aDissertation, Academic
_9187
690 _aInformation Security
_9294
942 _2ddc
_cTH
999 _c8867
_d8867