Novel assessment method for accessing private data in social network security services

2017 ◽  
Vol 73 (7) ◽  
pp. 3307-3325 ◽  
Author(s):  
Jong Hyuk Park ◽  
Yunsick Sung ◽  
Pradip Kumar Sharma ◽  
Young-Sik Jeong ◽  
Gangman Yi
2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Jinyu Hu ◽  
Zhiwei Gao ◽  
Weisen Pan

Multiangle social network recommendation algorithms (MSN) and a new assessment method, called similarity network evaluation (SNE), are both proposed. From the viewpoint of six dimensions, the MSN are classified into six algorithms, including user-based algorithm from resource point (UBR), user-based algorithm from tag point (UBT), resource-based algorithm from tag point (RBT), resource-based algorithm from user point (RBU), tag-based algorithm from resource point (TBR), and tag-based algorithm from user point (TBU). Compared with the traditional recall/precision (RP) method, the SNE is more simple, effective, and visualized. The simulation results show that TBR and UBR are the best algorithms, RBU and TBU are the worst ones, and UBT and RBT are in the medium levels.


2013 ◽  
Vol 5 (2) ◽  
pp. 45-49
Author(s):  
Suha Hameed ◽  
Zahraa Muhsen ◽  
Salwa Alsamarai

2010 ◽  
Vol 108-111 ◽  
pp. 948-953 ◽  
Author(s):  
Hao Yuan

Based on the research of domestic and foreign vulnerability assessment systems, in this paper, we propose an improved network security assessment method based on Immunity algorithm. It integrates the advantages of both host based and network based scan system. Our goal is to explore the known security vulnerabilities, and to check hosts’ security effectively as well. It has the features of self-adaptive, distributed, and real time. Therefore, it provides a good solution to risk assessment for network security.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Oussama BenRhouma ◽  
Ali AlZahrani ◽  
Ahmad AlKhodre ◽  
Abdallah Namoun ◽  
Wasim Ahmad Bhat

Purpose The purpose of this paper is to investigate the private-data pertaining to the interaction of users with social media applications that can be recovered from second-hand Android devices. Design/methodology/approach This study uses a black-box testing-principles based methodology to develop use-cases that simulate real-world case-scenarios of the activities performed by the users on the social media application. The authors executed these use-cases in a controlled experiment and examined the Android smartphone to recover the private-data pertaining to these use-cases. Findings The results suggest that the social media data recovered from Android devices can reveal a complete timeline of activities performed by the user, identify all the videos watched, uploaded, shared and deleted by the user, disclose the username and user-id of the user, unveil the email addresses used by the user to download the application and share the videos with other users and expose the social network of the user on the platform. Forensic investigators may find this data helpful in investigating crimes such as cyber bullying, racism, blasphemy, vehicle thefts, road accidents and so on. However, this data-breach in Android devices is a threat to user's privacy, identity and profiling in second-hand market. Practical implications Perceived notion of data sanitisation as a result of application removal and factory-reset can have serious implications. Though being helpful to forensic investigators, it leaves the user vulnerable to privacy breach, identity theft, profiling and social network revealing in second-hand market. At the same time, users' sensitivity towards data-breach might compel users to refrain from selling their Android devices in second-hand market and hamper device recycling. Originality/value This study attempts to bridge the literature gap in social media data-breach in second-hand Android devices by experimentally determining the extent of the breach. The findings of this study can help digital forensic investigators in solving crimes such as vehicle theft, road accidents, cybercrimes and so on. It can assist smartphone users to decide whether to sell their smartphones in a second-hand market, and at the same time encourage developers and researchers to design methods of social media data sanitisation.


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