2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)最新文献_第7页

Modeling and Verification of Spatio-Temporal Intelligent Transportation Systems 时空智能交通系统的建模与验证

2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) Pub Date : 2020-12-01 DOI: 10.1109/TrustCom50675.2020.00081

Tengfei Li, Xiaohong Chen, Haiying Sun, Jing Liu, Jiajia Yang, Chenchen Yang, Junfeng Sun

引用次数: 1

LTMS: A Lightweight Trust Management System for Wireless Medical Sensor Networks LTMS:用于无线医疗传感器网络的轻量级信任管理系统

2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) Pub Date : 2020-12-01 DOI: 10.1109/TrustCom50675.2020.00245

Muhammad Shadi Hajar, M. Al-Kadri, H. Kalutarage

{"title":"LTMS: A Lightweight Trust Management System for Wireless Medical Sensor Networks","authors":"Muhammad Shadi Hajar, M. Al-Kadri, H. Kalutarage","doi":"10.1109/TrustCom50675.2020.00245","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00245","url":null,"abstract":"Wireless Medical Sensor Networks (WMSNs) offer ubiquitous health applications that enhance patients' quality of life and support national health systems. Detecting internal attacks on WMSNs is still challenging since cryptographic measures can not protect from compromised or selfish sensor nodes. Establishing a trust relationship between sensor nodes is recognized as a promising measure to reinforce the overall security of Wireless Sensor Networks (WSNs). However, the existing trust schemes for WSNs are not necessarily fit for WMSNs due to their different operation, topology, resources limitations, and critical applications. In this paper, the aforementioned factors are regarded, and accordingly, two different methods to evaluate the trust value have been proposed to fit in-body, on-body, and off-body sensor nodes. Our Lightweight Trust Management System (LTMS) provides a further line of defense to detect packet drop attacks launched by compromised or selfish sensor nodes. Moreover, simulation results show that LTMS is more robust against complicated on-off attacks and can significantly reduce the processing overhead.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129841759","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: 8

Awareness of Secure Coding Guidelines in the Industry - A first data analysis 业界对安全编码指引的认识-首个数据分析

2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) Pub Date : 2020-12-01 DOI: 10.1109/TrustCom50675.2020.00055

T. Gasiba, U. Lechner, M. Pinto-Albuquerque, Daniel Méndez Fernández

引用次数: 13

VCKSCF: Efficient Verifiable Conjunctive Keyword Search Based on Cuckoo Filter for Cloud Storage 基于Cuckoo过滤器的云存储高效可验证联合关键字搜索

2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) Pub Date : 2020-12-01 DOI: 10.1109/TrustCom50675.2020.00048

C. Fan, Xiaolei Dong, Z. Cao, Jiachen Shen

引用次数: 2

An Approach for Poisoning Attacks against RNN-Based Cyber Anomaly Detection 一种针对rnn网络异常检测的投毒攻击方法

2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) Pub Date : 2020-12-01 DOI: 10.1109/TrustCom50675.2020.00231

Jinghui Xu, Yu Wen, Chun Yang, Dan Meng

{"title":"An Approach for Poisoning Attacks against RNN-Based Cyber Anomaly Detection","authors":"Jinghui Xu, Yu Wen, Chun Yang, Dan Meng","doi":"10.1109/TrustCom50675.2020.00231","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00231","url":null,"abstract":"In the face of the increasingly complex Internet environment, the traditional intrusion detection system is difficult to cope with the unknown variety of attacks. People hope to find reliable anomaly detection technology to help improve the security of cyberspace. The rapid development of artificial intelligence technology provides new development opportunities for anomaly detection technology, and the anomaly detection system based on deep learning performs well in some studies. However, neural networks are highly dependent on data quality, and a small number of poisoned samples injected into the data set will have a huge impact on the results. The online abnormal threat detection system based on deep learning is likely to be attacked by poisoning due to the need for continuous data collection and training. We propose a poisoning attack method using adversarial samples to resist the anomaly detection system based on an unsupervised deep neural network, which can destroy the neural network with as few samples as possible. We verified the effectiveness of poisoning attacks on the network security data set of los alamos national laboratory and further demonstrated its generality on other abnormal detection data set.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121622606","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: 8

Password Policies vs. Usability: When Do Users Go “Bananas”? 密码策略vs可用性:用户什么时候会“抓狂”?

2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) Pub Date : 2020-12-01 DOI: 10.1109/TrustCom50675.2020.00032

Roberto Dillon, S. Chawla, Dayana Hristova, Barbara Göbl, Suzana Jovicic

引用次数: 3

On the Comparison of Classifiers' Construction over Private Inputs 私人投入分类器结构比较研究

2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) Pub Date : 2020-12-01 DOI: 10.1109/TrustCom50675.2020.00096

M. Alishahi, Nicola Zannone

引用次数: 2

Monitoring Social Media for Vulnerability-Threat Prediction and Topic Analysis 监控社交媒体的漏洞-威胁预测和主题分析

2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) Pub Date : 2020-12-01 DOI: 10.1109/TrustCom50675.2020.00243

Shin-Ying Huang, Tao Ban

{"title":"Monitoring Social Media for Vulnerability-Threat Prediction and Topic Analysis","authors":"Shin-Ying Huang, Tao Ban","doi":"10.1109/TrustCom50675.2020.00243","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00243","url":null,"abstract":"Publicly available software vulnerabilities and exploit code are often abused by malicious actors to launch cyberattacks to vulnerable targets. Organizations not only have to update their software to the latest versions, but do effective patch management and prioritize security-related patching as well. In addition to intelligence sources such as Computer Emergency Response Team (CERT) alerts, cybersecurity news, national vulnerability database (NBD), and commercial cybersecurity vendors, social media is another valuable source that facilitates early stage intelligence gathering. To early detect future cyber threats based on publicly available resources on the Internet, we propose a dynamic vulnerability-threat assessment model to predict the tendency to be exploited for vulnerability entries listed in Common Vulnerability Exposures, and also to analyze social media contents such as Twitter to extract meaningful information. The model takes multiple aspects of vulnerabilities gathered from different sources into consideration. Features range from profile information to contextual information about these vulnerabilities. For the social media data, this study leverages machine learning techniques specially for Twitter which helps to filter out non-cybersecurity-related tweets and also label the topic categories of each tweet. When applied to predict the vulnerabilities exploitation and analyzed the real-world social media discussion data, it showed promising prediction accuracy with purified social media intelligence. Moreover, the AI-enabling modules have been deployed into a threat intelligence platform for further applications.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121232988","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: 3

ELPPS: An Enhanced Location Privacy Preserving Scheme in Mobile Crowd-Sensing Network Based on Edge Computing ELPPS:一种基于边缘计算的移动人群传感网络位置隐私保护增强方案

2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) Pub Date : 2020-12-01 DOI: 10.1109/TrustCom50675.2020.00071

Minghui Li, Yang Li, Liming Fang

{"title":"ELPPS: An Enhanced Location Privacy Preserving Scheme in Mobile Crowd-Sensing Network Based on Edge Computing","authors":"Minghui Li, Yang Li, Liming Fang","doi":"10.1109/TrustCom50675.2020.00071","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00071","url":null,"abstract":"Mobile Crowd-Sensing (MCS) is gradually extended to the edge network to reduce the delay of data transmission and improve the ability of data processing. However, a challenge is that there are still loopholes in the protection of privacy data, especially in location-based services. The attacker can reconstruct the location relationship network among the correlation about the environment information, identity information, and other sensing data provided by mobile users. Moreover, in the edge environment, this kind of attack is more accurate and more threatening to the location privacy information. To solve this problem, we propose a location privacy protection scheme (ELPPS) for a mobile crowd-sensing network in the edge environment, to protect the position correlation weight between sensing users through differential privacy. We use the grid anonymous algorithm to confuse the location information in order to reduce the computing cost of edge nodes. The experiment results show that the proposed framework can effectively protect the location information of the sensing users without reducing the availability of the sensing task results, and has a low delay.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"232 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116324476","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: 1

IoT-Sphere: A Framework To Secure IoT Devices From Becoming Attack Target And Attack Source 物联网领域:防止物联网设备成为攻击目标和攻击源的框架

2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) Pub Date : 2020-12-01 DOI: 10.1109/TrustCom50675.2020.00189

Syed Ghazanfar Abbas, M. Husnain, U. U. Fayyaz, F. Shahzad, G. Shah, K. Zafar

{"title":"IoT-Sphere: A Framework To Secure IoT Devices From Becoming Attack Target And Attack Source","authors":"Syed Ghazanfar Abbas, M. Husnain, U. U. Fayyaz, F. Shahzad, G. Shah, K. Zafar","doi":"10.1109/TrustCom50675.2020.00189","DOIUrl":"https://doi.org/10.1109/TrustCom50675.2020.00189","url":null,"abstract":"In this research we propose a framework that will strengthen the IoT devices security from dual perspectives; avoid devices to become attack target as well as a source of an attack. Unlike traditional devices, IoT devices are equipped with insufficient host-based defense system and a continuous internet connection. All time internet enabled devices with insufficient security allures the attackers to use such devices and carry out their attacks on rest of internet. When plethora of vulnerable devices become source of an attack, intensity of such attacks increases exponentially. Mirai was one of the first well-known attack that exploited large number of vulnerable IoT devices, that bring down a large part of Internet. To strengthen the IoT devices from dual security perspective, we propose a two step framework. Firstly, confine the communication boundary of IoT devices; IoT-Sphere. A sphere of IPs that are allowed to communicate with a device. Any communication that violates the sphere will be blocked at the gateway level. Secondly, only allowed communication will be evaluated for potential attacks and anomalies using advance detection engines. To show the effectiveness of our proposed framework, we perform couple of attacks on IoT devices; camera and google home and show the feasibility of IoT-Sphere.","PeriodicalId":221956,"journal":{"name":"2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127802465","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: 4