scholarly journals Hierarchical Identifier: Application to User Privacy Eavesdropping on Mobile Payment App

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3052 ◽  
Author(s):  
Yaru Wang ◽  
Ning Zheng ◽  
Ming Xu ◽  
Tong Qiao ◽  
Qiang Zhang ◽  
...  
Keyword(s):  
Learning Strategies ◽  
Ensemble Learning ◽  
Network Traffic ◽  
Experimental Results ◽  
Mobile Payment ◽  
Identification System ◽  
Traffic Data ◽  
User Privacy ◽  
Hierarchical Identification ◽  
Financial Transactions

Mobile payment apps have been widely-adopted, which brings great convenience to people’s lives. However, at the same time, user’s privacy is possibly eavesdropped and maliciously exploited by attackers. In this paper, we consider a possible way for an attacker to monitor people’s privacy on a mobile payment app, where the attacker aims to identify the user’s financial transactions at the trading stage via analyzing the encrypted network traffic. To achieve this goal, a hierarchical identification system is established, which can acquire users’ privacy information in three different manners. First, it identifies the mobile payment app from traffic data, then classifies specific actions on the mobile payment app, and finally, detects the detailed steps within the action. In our proposed system, we extract reliable features from the collected traffic data generated on the mobile payment app, then use a series of well-performing ensemble learning strategies to deal with three identification tasks. Compared with prior works, the experimental results demonstrate that our proposed hierarchical identification system performs better.

scholarly journals Improving Security of Future Networks Using Enhanced Customer Edge Switching and Risk-Based Analysis

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1107
Author(s):  
Slawomir Nowaczewski ◽  
Wojciech Mazurczyk
Keyword(s):  
Network Traffic ◽  
Information Exchange ◽  
Experimental Results ◽  
It Impacts ◽  
Future Networks

Customer Edge Switching (CES) is an extension of the already known classical firewall that is often described and used in future networks like 5G. It extends its functionality by enabling information exchange with other firewalls to decide whether the inspected network traffic should be considered malicious or legitimate. In this paper, we show how the Passive DNS can be used to further improve security of this solution. First, we discuss CES solution and its internals. We also determine how it uses DNS and CETP protocols. Secondly, we describe the basics of the Passive DNS and how it impacts the DNS protocol. Thirdly, we evaluate how the Passive DNS can be extended to collect also CETP information. Finally, we integrate the solutions and present obtained experimental results.

scholarly journals “Chatty Devices” and edge-based activity classification

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Mike Lakoju ◽  
Amir Javed ◽  
Omer Rana ◽  
Pete Burnap ◽  
Samuelson T. Atiba ◽  
...  
Keyword(s):  
Learning Strategies ◽  
Manufacturing Process ◽  
Data Privacy ◽  
Human Robot Interaction ◽  
Production Environment ◽  
User Privacy ◽  
Robot Interaction ◽  
Actual Usage ◽  
Product Use ◽  
Edge Based

AbstractWith increasing automation of manufacturing processes (focusing on technologies such as robotics and human-robot interaction), there is a realisation that the manufacturing process and the artefacts/products it produces can be better connected post-production. Built on this requirement, a “chatty" factory involves creating products which are able to send data back to the manufacturing/production environment as they are used, whilst still ensuring user privacy. The intended use of a product during design phase may different significantly from actual usage. Understanding how this data can be used to support continuous product refinement, and how the manufacturing process can be dynamically adapted based on the availability of this data provides a number of opportunities. We describe how data collected on product use can be used to: (i) classify product use; (ii) associate a label with product use using unsupervised learning—making use of edge-based analytics; (iii) transmission of this data to a cloud environment where labels can be compared across different products of the same type. Federated learning strategies are used on edge devices to ensure that any data captured from a product can be analysed locally (ensuring data privacy).

scholarly journals Reducing Network Traffic Data Sets

2007 ◽  
Author(s):  
A. Botta ◽  
A. Dainotti ◽  
A. Pescape ◽  
G. Ventre
Keyword(s):  
Network Traffic ◽  
Data Sets ◽  
Traffic Data

scholarly journals Diagnosis of Out-of-control Signals in Multivariate Statistical Process Control Based on Bagging and Decision Tree

2017 ◽  
Vol 2 (2) ◽  
pp. 1 ◽  
Author(s):  
Jing Jiang ◽  
Hua-Ming Song
Keyword(s):  
Process Control ◽  
Decision Tree ◽  
Statistical Process Control ◽  
Ensemble Learning ◽  
Experimental Results ◽  
Multivariate Statistical Process Control ◽  
Multivariate Statistical ◽  
Statistical Process ◽  
Multiple Classifiers ◽  
Control Signals

In this paper, we propose an ensemble method based on bagging and decision tree to resolve the problem of diagnosing out-of-control signals in multivariate statistical process control. To classify the out-of-control signals, we obtain a series of classifiers through ensemble learning on decision tree. Then we will integrate the classification results of multiple classifiers to determine the final classification. The experimental results show that our method could improve the accuracy of classification and is superior to other methods in terms of diagnosing out-of-control signals in multivariate statistical process control.

Ship Trajectories Pre-processing Based on AIS Data

2018 ◽  
Vol 71 (5) ◽  
pp. 1210-1230 ◽  
Author(s):  
Liangbin Zhao ◽  
Guoyou Shi ◽  
Jiaxuan Yang
Keyword(s):  
Data Mining ◽  
Traffic Density ◽  
Automatic Identification ◽  
Identification System ◽  
Traffic Data ◽  
Density Maps ◽  
Different Types ◽  
Quality Dimensions ◽  
Time Accuracy

Data derived from the Automatic Identification System (AIS) plays a key role in water traffic data mining. However, there are various errors regarding time and space. To improve availability, AIS data quality dimensions are presented for detecting errors of AIS tracks including physical integrity, spatial logical integrity and time accuracy. After systematic summary and analysis, algorithms for error pre-processing are proposed. Track comparison maps and traffic density maps for different types of ships are derived to verify applicability based on the AIS data from the Chinese Zhoushan Islands from January to February 2015. The results indicate that the algorithms can effectively improve the quality of AIS trajectories.

scholarly journals Efficient Multifactor Two-Server Authenticated Scheme under Mobile Cloud Computing

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Ziyi Han ◽  
Li Yang ◽  
Shen Wang ◽  
Sen Mu ◽  
Qiang Liu
Keyword(s):  
Cloud Computing ◽  
Information Disclosure ◽  
Mobile Cloud Computing ◽  
User Authentication ◽  
High Reliability ◽  
Security Analysis ◽  
Security Requirements ◽  
Mobile Payment ◽  
Mobile Cloud ◽  
User Privacy

Because the authentication method based on username-password has the disadvantage of easy disclosure and low reliability and the excess password management degrades the user experience tremendously, the user is eager to get rid of the bond of the password in order to seek a new way of authentication. Therefore, the multifactor biometrics-based user authentication wins the favor of people with advantages of simplicity, convenience, and high reliability. Now the biometrics-based (especially the fingerprint information) authentication technology has been extremely mature, and it is universally applied in the scenario of the mobile payment. Unfortunately, in the existing scheme, biometric information is stored on the server side. As thus, once the server is hacked by attackers to cause the leakage of the fingerprint information, it will take a deadly threat to the user privacy. Aiming at the security problem due to the fingerprint information in the mobile payment environment, we propose a novel multifactor two-server authenticated scheme under mobile cloud computing (MTSAS). In the MTSAS, it divides the authentication method and authentication means; in the meanwhile, the user’s biometric characteristics cannot leave the user device. Thus, MTSAS avoids the fingerprint information disclosure, protects user privacy, and improves the security of the user data. In the same time, considering user actual requirements, different authentication factors depending on the privacy level of authentication are chosen. Security analysis proves that MTSAS has achieved the authentication purpose and met security requirements by the BAN logic. In comparison with other schemes, the result shows that MTSAS not only has the reasonable computational efficiency, but also keeps the superior communication cost.

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