2019 16th International ISC (Iranian Society of Cryptology) Conference on Information Security and Cryptology (ISCISC)最新文献_第2页

Analysis of Machine Learning Techniques for Ransomware Detection 勒索软件检测中的机器学习技术分析

2019 16th International ISC (Iranian Society of Cryptology) Conference on Information Security and Cryptology (ISCISC) Pub Date : 2019-08-01 DOI: 10.1109/ISCISC48546.2019.8985139

Fakhroddin Noorbehbahani, Farzaneh Rasouli, Mohammad Saberi

{"title":"Analysis of Machine Learning Techniques for Ransomware Detection","authors":"Fakhroddin Noorbehbahani, Farzaneh Rasouli, Mohammad Saberi","doi":"10.1109/ISCISC48546.2019.8985139","DOIUrl":"https://doi.org/10.1109/ISCISC48546.2019.8985139","url":null,"abstract":"In parallel with the increasing growth of the Internet and computer networks, the number of malwares has been increasing every day. Today, one of the newest attacks and the biggest threats in cybersecurity is ransomware. The effectiveness of applying machine learning techniques for malware detection has been explored in much scientific research, however, there is few studies focused on machine learning-based ransomware detection. In this paper, the effectiveness of ransomware detection using machine learning methods applied to CICAndMal2017 dataset is examined in two experiments. First, the classifiers are trained on a single dataset containing different types of ransomware. Second, different classifiers are trained on datasets of 10 ransomware families distinctly. Our findings imply that in both experiments random forest outperforms other tested classifiers and the performance of the classifiers are not changed significantly when they are trained on each family distinctly. Therefore, the random forest classification method is very effective in ransomware detection.","PeriodicalId":128407,"journal":{"name":"2019 16th International ISC (Iranian Society of Cryptology) Conference on Information Security and Cryptology (ISCISC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129000839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 19

Cryptanalysis of SP2DAS and 3PDA, Two Data Aggregation Schemes for Smart Grid 智能电网两种数据聚合方案SP2DAS和3PDA的密码分析

2019 16th International ISC (Iranian Society of Cryptology) Conference on Information Security and Cryptology (ISCISC) Pub Date : 2019-08-01 DOI: 10.1109/ISCISC48546.2019.8985140

Hamid Amiryousefi, Z. Ahmadian

引用次数: 1

Investigating the Streaming Algorithms Usage in Website Fingerprinting Attack Against Tor Privacy Enhancing Technology 针对Tor隐私增强技术的流算法在网站指纹攻击中的应用研究

2019 16th International ISC (Iranian Society of Cryptology) Conference on Information Security and Cryptology (ISCISC) Pub Date : 2019-08-01 DOI: 10.1109/ISCISC48546.2019.8985162

Reyhane Attarian, S. Hashemi

引用次数: 3

CRT-Based Robust Data Hiding Method by Extracting Features in DCT Domain 基于ct的DCT域特征提取鲁棒数据隐藏方法

2019 16th International ISC (Iranian Society of Cryptology) Conference on Information Security and Cryptology (ISCISC) Pub Date : 2019-08-01 DOI: 10.1109/ISCISC48546.2019.8985163

Alireza Ghaemi, H. Danyali

引用次数: 0

Inferring API Correct Usage Rules: A Tree-based Approach 推断API正确使用规则:基于树的方法

2019 16th International ISC (Iranian Society of Cryptology) Conference on Information Security and Cryptology (ISCISC) Pub Date : 2019-08-01 DOI: 10.1109/ISCISC48546.2019.8985157

Majid Zolfaghari, Solmaz Salimi, M. Kharrazi

{"title":"Inferring API Correct Usage Rules: A Tree-based Approach","authors":"Majid Zolfaghari, Solmaz Salimi, M. Kharrazi","doi":"10.1109/ISCISC48546.2019.8985157","DOIUrl":"https://doi.org/10.1109/ISCISC48546.2019.8985157","url":null,"abstract":"The lack of knowledge about API correct usage rules is one of the main reasons that APIs are employed incorrectly by programmers, which in some cases lead to serious security vulnerabilities. However, finding a correct usage rule for an API is a time-consuming and error-prone task, particularly in the absence of an API documentation. Existing approaches to extract correct usage rules are mostly based on majority API usages, assuming the correct usage is prevalent. Although statistically extracting API correct usage rules achieves reasonable accuracy, it cannot work correctly in the absence of a fair amount of sample usages. We propose inferring API correct usage rules independent of the number of sample usages by leveraging an API tree structure. In an API tree, each node is an API, and each node's children are APIs called by the parent API. Starting from lower-level APIs, it is possible to infer the correct usage rules for them by utilizing the available correct usage rules of their children. We developed a tool based on our idea for inferring API correct usages rules hierarchically, and have applied it to the source code of Linux kernel v4.3 drivers and found 24 previously reported bugs.","PeriodicalId":128407,"journal":{"name":"2019 16th International ISC (Iranian Society of Cryptology) Conference on Information Security and Cryptology (ISCISC)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132759480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ransomware detection using process mining and classification algorithms 基于过程挖掘和分类算法的勒索软件检测

2019 16th International ISC (Iranian Society of Cryptology) Conference on Information Security and Cryptology (ISCISC) Pub Date : 2019-08-01 DOI: 10.1109/ISCISC48546.2019.8985149

A. Bahrani, Amir Jalaly Bidgly

{"title":"Ransomware detection using process mining and classification algorithms","authors":"A. Bahrani, Amir Jalaly Bidgly","doi":"10.1109/ISCISC48546.2019.8985149","DOIUrl":"https://doi.org/10.1109/ISCISC48546.2019.8985149","url":null,"abstract":"The fast growing of ransomware attacks has become a serious threat for companies, governments and internet users, in recent years. The increasing of computing power, memory and etc. and the advance in cryptography has caused the complicating the ransomware attacks. Therefore, effective methods are required to deal with ransomwares. Although, there are many methods proposed for ransomware detection, but these methods are inefficient in detection ransomwares, and more researches are still required in this field. In this paper, we have proposed a novel method for identify ransomware from benign software using process mining methods. The proposed method uses process mining to discover the process model from the events logs, and then extracts features from this process model and using these features and classification algorithms to classify ransomwares. This paper shows that the use of classification algorithms along with the process mining can be suitable to identify ransomware. The accuracy and performance of our proposed method is evaluated using a study of 21 ransomware families and some benign samples. The results show j48 and random forest algorithms have the best accuracy in our method and can achieve to 95% accuracy in detecting ransomwares.","PeriodicalId":128407,"journal":{"name":"2019 16th International ISC (Iranian Society of Cryptology) Conference on Information Security and Cryptology (ISCISC)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124799721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Classical-Quantum Multiple Access Wiretap Channel 经典量子多址窃听信道

2019 16th International ISC (Iranian Society of Cryptology) Conference on Information Security and Cryptology (ISCISC) Pub Date : 2019-08-01 DOI: 10.1109/ISCISC48546.2019.8985142

Hadi Aghaee, Bahareh Akhbari

引用次数: 10

Cryptanalysis of a Certificateless Signcryption Scheme 无证书签名加密方案的密码分析

2019 16th International ISC (Iranian Society of Cryptology) Conference on Information Security and Cryptology (ISCISC) Pub Date : 2019-08-01 DOI: 10.1109/ISCISC48546.2019.8985158

Parvin Rastegari, Mohammad Dakhilalian

引用次数: 1

Organazing Committee Organazing委员会

2019 16th International ISC (Iranian Society of Cryptology) Conference on Information Security and Cryptology (ISCISC) Pub Date : 2019-08-01 DOI: 10.1109/iscisc48546.2019.8985156

引用次数: 0

ISCISC 2019 Papers ISCISC 2019论文

2019 16th International ISC (Iranian Society of Cryptology) Conference on Information Security and Cryptology (ISCISC) Pub Date : 2019-08-01 DOI: 10.1109/iscisc48546.2019.8985151

引用次数: 0