Data Security and Privacy in Industrial IoT

2021 ◽  
pp. 21-39
Author(s):  
Nafiseh Sharghivand ◽  
Farnaz Derakhshan
Keyword(s):  
Data Security ◽  
Security And Privacy ◽  
Industrial Iot

Valuing Data Security and Privacy Using Cyber Insurance

2015 ◽  
Author(s):  
Anand Shah ◽  
Shishir Dahake ◽  
Sri Hari Haran J
Keyword(s):  
Data Security ◽  
Security And Privacy ◽  
Cyber Insurance

scholarly journals IoT Big Data Security and Privacy Versus Innovation

2019 ◽  
Vol 6 (2) ◽  
pp. 1628-1635 ◽  
Author(s):  
Karen R. Sollins
Keyword(s):  
Big Data ◽  
Data Security ◽  
Security And Privacy

scholarly journals Challenges and techniques in Big data security and privacy: A review

2018 ◽  
Vol 1 (4) ◽  
pp. e13 ◽  
Author(s):  
Rongxin Bao ◽  
Zhikui Chen ◽  
Mohammad S. Obaidat
Keyword(s):  
Big Data ◽  
Data Security ◽  
Security And Privacy

scholarly journals Data Security and Privacy in Cloud Computing

2014 ◽  
Vol 10 (7) ◽  
pp. 190903 ◽  
Author(s):  
Yunchuan Sun ◽  
Junsheng Zhang ◽  
Yongping Xiong ◽  
Guangyu Zhu
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Security And Privacy

scholarly journals RBP: a website fingerprinting obfuscation method against intelligent fingerprinting attacks

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Tao Luo ◽  
LiangMin Wang ◽  
ShangNan Yin ◽  
Hao Shentu ◽  
Hui Zhao
Keyword(s):  
Data Security ◽  
Arrival Time ◽  
State Of The Art ◽  
Web Security ◽  
Security And Privacy ◽  
Low Delay ◽  
Defense Technology ◽  
The Difference ◽  
Bandwidth Overhead ◽  
Traffic Analysis Attack

AbstractEdge computing has developed rapidly in recent years due to its advantages of low bandwidth overhead and low delay, but it also brings challenges in data security and privacy. Website fingerprinting (WF) is a passive traffic analysis attack that threatens website privacy which poses a great threat to user’s privacy and web security. It collects network packets generated while a user accesses website, and then uses a series of techniques to discover patterns of network packets to infer the type of website user accesses. Many anonymous networks such as Tor can meet the need of hide identity from users in network activities, but they are also threatened by WF attacks. In this paper, we propose a website fingerprinting obfuscation method against intelligent fingerprinting attacks, called Random Bidirectional Padding (RBP). It is a novel website fingerprinting defense technology based on time sampling and random bidirectional packets padding, which can covert the real packets distribution to destroy the Inter-Arrival Time (IAT) features in the traffic sequence and increase the difference between the datasets with random bidirectional virtual packets padding. We evaluate the defense against state-of-the-art website fingerprinting attacks in real scenarios, and show its effectiveness.

Behavioral Economics Issues for Software Requirements Optimization for Personal Data Security and Privacy

2021 ◽  
Author(s):  
Shatadru Shikta ◽  
Somania Nur Mahal ◽  
Kazi Bushra Al Jannat ◽  
MAHADY HASAN ◽  
M. ROKONUZZAMAN
Keyword(s):  
Behavioral Economics ◽  
Data Security ◽  
Personal Data ◽  
Security And Privacy ◽  
Software Requirements

scholarly journals Is Big Data Security Essential for Students to Understand?

2020 ◽  
Vol 11 (2) ◽  
pp. 161-170
Author(s):  
Rochman Hadi Mustofa
Keyword(s):  
Big Data ◽  
Undergraduate Students ◽  
Data Security ◽  
Personal Data ◽  
Digital Data ◽  
Security And Privacy ◽  
Group Discussions ◽  
Technology Applications ◽  
Digital Payments ◽  
Financial Technology

AbstractBig Data has become a significant concern of the world, along with the era of digital transformation. However, there are still many young people, especially in developing countries, who are not yet aware of the security of their big data, especially personal data. Misuse of information from big data often results in violations of privacy, security, and cybercrime. This study aims to determine how aware of the younger generation of security and privacy of their big data. Data were collected qualitatively by interviews and focus group discussions (FGD) from. Respondents were undergraduate students who used social media and financial technology applications such as online shopping, digital payments, digital wallet and hotel/transportation booking applications. The results showed that students were not aware enough and understood the security or privacy of their digital data, and some respondents even gave personal data to potentially scam sites. Most students are not careful in providing big data information because they are not aware of the risks behind it, socialization is needed in the future as a step to prevent potential data theft.

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