2022 6th International Conference on Cryptography, Security and Privacy (CSP)最新文献

Multifaceted Analysis of Malicious Ethereum Accounts and Corresponding Activities 恶意以太坊账户及其相关活动的多方面分析

2022 6th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2022-01-01 DOI: 10.1109/csp55486.2022.00022

J. Wang, Takayuki Sasaki, Kazumasa Omote, K. Yoshioka, Tsutomu Matsumoto

{"title":"Multifaceted Analysis of Malicious Ethereum Accounts and Corresponding Activities","authors":"J. Wang, Takayuki Sasaki, Kazumasa Omote, K. Yoshioka, Tsutomu Matsumoto","doi":"10.1109/csp55486.2022.00022","DOIUrl":"https://doi.org/10.1109/csp55486.2022.00022","url":null,"abstract":"In recent years, Ethereum, one of the leading applications to realize the service of blockchain technology, has received a great deal of attention with the usability and functionality to execute smart contracts, arbitrary programmable calculations in addition to cryptocurrency trading. However, misconfigured Ethereum clients with application programming interface (API) enabled, JSON-RPC in particular, are targeted by cyberattacks. In this research, we propose a new framework to detect malicious and suspicious Ethereum accounts using 3 different data sources (honeypot, Internet-wide scanner and blockchain explorer). The honeypot, named Etherpot, utilizes a proxy server placed between a real Ethereum client and the Internet. It modifies responses from the Ethereum client to attract attackers, identifies malicious accounts and analyzes their behaviors. With the Internet-wide scan results from Shodan, we also detect suspicious Ethereum accounts that are registered on multiple nodes. Finally, we utilize Etherscan, a well-known blockchain explorer for Ethereum, to track and analyze the activities related to the detected accounts. Through the observation of 6 weeks, we observed 538 hosts trying to call JSON- RPC of our honeypots with 41 different types of methods, including 2 types of unreported attacks in the wild. We detected 16 malicious accounts from the honeypots and 64 suspicious accounts from Shodan scan results, 5 out of which are overlapped. Finally, from Etherscan, we collected records of activities related to the detected accounts, including transactions of 21.50 ETH and mining of 22.61 ETH (equivalent to 167,560 USS at the rate of 2021/10/14). To an end, we provide a much brighter view of malicious activities on Ethereum.","PeriodicalId":187713,"journal":{"name":"2022 6th International Conference on Cryptography, Security and Privacy (CSP)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117349042","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

Differential Privacy under Incalculable Sensitivity 不可计算敏感性下的差分隐私

2022 6th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2022-01-01 DOI: 10.1109/CSP55486.2022.00013

Tomoaki Mimoto, Masayuki Hashimoto, Hiroyuki Yokoyama, Toru Nakamura, T. Isohara, R. Kojima, Aki Hasegawa, Yasushi Okuno

{"title":"Differential Privacy under Incalculable Sensitivity","authors":"Tomoaki Mimoto, Masayuki Hashimoto, Hiroyuki Yokoyama, Toru Nakamura, T. Isohara, R. Kojima, Aki Hasegawa, Yasushi Okuno","doi":"10.1109/CSP55486.2022.00013","DOIUrl":"https://doi.org/10.1109/CSP55486.2022.00013","url":null,"abstract":"Differential privacy mechanisms have been proposed to guarantee the privacy of individuals in various types of statistical information. When constructing a probabilistic mechanism to satisfy differential privacy, it is necessary to consider the impact of an arbitrary record on its statistics, i.e., sensitivity, but there are situations where sensitivity is difficult to derive. In this paper, we first summarize the situations in which it is difficult to derive sensitivity in general, and then propose a definition equivalent to the conventional definition of differential privacy to deal with them. This definition considers neighboring datasets as in the conventional definition. Therefore, known differential privacy mechanisms can be applied. Next, as an example of the difficulty in deriving sensitivity, we focus on the t-test, a basic tool in statistical analysis, and show that a concrete differential privacy mechanism can be constructed in practice. Our proposed definition can be treated in the same way as the conventional differential privacy definition, and can be applied to cases where it is difficult to derive sensitivity.","PeriodicalId":187713,"journal":{"name":"2022 6th International Conference on Cryptography, Security and Privacy (CSP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130286348","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

A Lightweight Advertisement Ecosystem Simulation Platform for Security Analysis 面向安全分析的轻型广告生态系统仿真平台

2022 6th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2022-01-01 DOI: 10.1109/CSP55486.2022.00016

Chenjia Yu, M. Gheisari, Yang Liu

引用次数: 1

Blockchain-based Smart Parking System using Ring Learning With Errors based Signature 基于区块链的基于错误签名的环形学习智能停车系统

2022 6th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2022-01-01 DOI: 10.1109/CSP55486.2022.00036

Jihan Lailatul Atiqoh, A. Barmawi, Farah Afianti

引用次数: 0

From Machine Learning Based Intrusion Detection to Cost Sensitive Intrusion Response 从基于机器学习的入侵检测到成本敏感的入侵响应

2022 6th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2022-01-01 DOI: 10.1109/CSP55486.2022.00031

Tazar Hussain, Alfie Beard, Liming Chen, Chris D. Nugent, Jun Liu, A. Moore

{"title":"From Machine Learning Based Intrusion Detection to Cost Sensitive Intrusion Response","authors":"Tazar Hussain, Alfie Beard, Liming Chen, Chris D. Nugent, Jun Liu, A. Moore","doi":"10.1109/CSP55486.2022.00031","DOIUrl":"https://doi.org/10.1109/CSP55486.2022.00031","url":null,"abstract":"Machine learning (ML) based intrusion detection systems (IDS) are increasingly used to discover abnormal patterns in network data and predict cyberattacks. However, the construction of intrusion response systems (IRS) used to deploy countermeasures and prevent malicious activities is more challenging because they require in-depth understanding of attack patterns, attacker behavior, and the correlation between different types of attacks. Furthermore, IDSs generate a large number of false positives and the confidence with which an attack can be predicted is usually unknown. As a result of these challenges in IDS and IRSs, inappropriate actions may be deployed, which may reduce network performance and users’ ability to perform typical tasks. Therefore, the present work proposes an intrusion detection and response method based on the Calibrated Random Forest (CRF) algorithm to overcome the key challenges related to the construction of an efficient IRS. The proposed CRF is used to quantify uncertainty in the prediction of cyberattacks and expresses each attack as a probability distribution. Subsequently, the predicted probabilities are used as confidence scores and integrated with domain expert knowledge for decision making in an IRS. We then use publicly available intrusion detection data sets to test and evaluate the proposed method based on three metrics: log loss, Brier score, and expected calibration error (ECE). Experimental results show that the proposed method makes intrusion response more reasonable and cost-sensitive, and has the ability to manage criticality, integrate domain knowledge and explain model behavior. It also demonstrates that this method provides an effective solution for security analysts in how to appropriately deploy and prioritize actions.","PeriodicalId":187713,"journal":{"name":"2022 6th International Conference on Cryptography, Security and Privacy (CSP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130843931","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

An approach to construct feedforward clock-controlled sequence with high linear complexity 一种构造高线性复杂度前馈时钟控制序列的方法

2022 6th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2022-01-01 DOI: 10.1109/CSP55486.2022.00034

Yangpan Zhang

引用次数: 0

Anonymity-driven Measures for Privacy 匿名驱动的隐私措施

2022 6th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2022-01-01 DOI: 10.1109/CSP55486.2022.00009

Sevgi Arca, R. Hewett

{"title":"Anonymity-driven Measures for Privacy","authors":"Sevgi Arca, R. Hewett","doi":"10.1109/CSP55486.2022.00009","DOIUrl":"https://doi.org/10.1109/CSP55486.2022.00009","url":null,"abstract":"In today’s world, digital data are enormous due to technologies that advance data collection, storage, and analyses. As more data are shared or publicly available, privacy is of great concern. Having privacy means having control over your data. The first step towards privacy protection is to understand various aspects of privacy and have the ability to quantify them. Much work in structured data, however, has focused on approaches to transforming the original data into a more anonymous form (via generalization and suppression) while preserving the data integrity. Such anonymization techniques count data instances of each set of distinct attribute values of interest to signify the required anonymity to protect an individual’s identity or confidential data. While this serves the purpose, our research takes an alternative approach to provide quick privacy measures by way of anonymity especially when dealing with large-scale data. This paper presents a study of anonymity measures based on their relevant properties that impact privacy. Specifically, we identify three properties: uniformity, variety, and diversity, and formulate their measures. The paper provides illustrated examples to evaluate their validity and discusses the use of multi-aspects of anonymity and privacy measures.","PeriodicalId":187713,"journal":{"name":"2022 6th International Conference on Cryptography, Security and Privacy (CSP)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124978528","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

Analysis of the Propagation of Miner Botnet 矿工僵尸网络的传播分析

2022 6th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2022-01-01 DOI: 10.1109/CSP55486.2022.00026

Yuxi Cheng, Zi Jin, Wei Ding

{"title":"Analysis of the Propagation of Miner Botnet","authors":"Yuxi Cheng, Zi Jin, Wei Ding","doi":"10.1109/CSP55486.2022.00026","DOIUrl":"https://doi.org/10.1109/CSP55486.2022.00026","url":null,"abstract":"Miner Botnet, a new type of botnet that perform digital cryptocurrency mining by invading and implanting malware programs in normal noncooperative user terminals, and occupy their computational resource, has been widely propagated with the soaring price of crypto currencies and become one of the major threats to the security of today’s cyber-space. Since the rapid spread of miner botnet mainly relies on the vulnerabilities in the computer system, the security of the computer system will be greatly improved if the vulnerability exploitation tactics of miner botnet can be predicted. In this paper, we study the exploitation history of the vulnerabilities exploited by miner botnets, build a new set of attributes on the basis of CVSS3.0 and use the knowledge graph as the framework to model the relationship between miner botnet, vulnerabilities and vulnerability attributes, and propose a method, combined with Apriori, Fast-Unfolding and a reasoning algorithm based on the knowledge structure, to predict the vulnerability exploitation tactics of miner botnet. Thereby we can prejudge the exploitation of miner botnets with historical data of vulnerability exploitation. The experimental results also show that the algorithm has a certain predictive effect on the vulnerability exploitation tactics of miner botnets. The algorithm can help security personnel respond to the attacker's behavior in advance and reduce the loss .","PeriodicalId":187713,"journal":{"name":"2022 6th International Conference on Cryptography, Security and Privacy (CSP)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116542590","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

Analyzing Initial Design Theory Components for Developing Information Security Laboratories 分析发展信息安全实验室的初始设计理论组成部分

2022 6th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2022-01-01 DOI: 10.1109/CSP55486.2022.00015

S. Iqbal

引用次数: 1

Vertical Scanning Behavior Analysis of High-Frequency Superpoints 高频叠加点垂直扫描行为分析

2022 6th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2022-01-01 DOI: 10.1109/csp55486.2022.00029

Wenxian Guo, Haiqing Yu, Wei Ding

{"title":"Vertical Scanning Behavior Analysis of High-Frequency Superpoints","authors":"Wenxian Guo, Haiqing Yu, Wei Ding","doi":"10.1109/csp55486.2022.00029","DOIUrl":"https://doi.org/10.1109/csp55486.2022.00029","url":null,"abstract":"Access superpoint is a host that communicates with a large number of peers at the same time in the network, occupying a large number of network communication resources. Under the background that access superpoint detection algorithms have been developed relatively mature, the anomaly detection research based on this is the direction worth exploring at present. In terms of time, access superpoints can be divided into high-frequency, medium-frequency and low-frequency superpoints. Among them, high-frequency superpoints often contain important data resources and are the first choice for hackers to attack, while vertical scanning is a common pre-invasion method for attackers. Therefore, detecting and analyzing the vertical scanning behavior of high-frequency superpoints plays an important role in the protection of high-frequency superpoints. In this paper, a time-frequency attribute is defined for the detected access superpoints and a time-frequency classification algorithm based on sliding window is proposed. The experimental results show that the algorithm has a high accuracy of 98.26% in a high-speed network environment. The vertical scanning behavior was screened based on the rules. And XGBoost algorithm was used to generate a classifier that can distinguish the abnormal behaviors of high frequency superpoints caused by vertical scanning. The classifier can identify the abnormal behaviors of high frequency superpoints caused by vertical scanning with an accuracy of 93.19%.","PeriodicalId":187713,"journal":{"name":"2022 6th International Conference on Cryptography, Security and Privacy (CSP)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124922557","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