Signalling over-privileged mobile applications using passive security indicators

Iacono, Luigi Lo; Gorski, Peter Leo; Grosse, Josephine; Gruschka, Nils

doi:10.1016/j.jisa.2016.11.006

Cited by 2 publications

(7 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, information may be presented in a complex manner, leaving the user unsatisfied and without a true understanding of the intention of the information that were disseminated. To illustrate the function of information dissemination, a study by Iacono et al (2017) investigated the approaches to communicate the degree of over-privilege in mobile applications. It used an additional rating system in application stores to inform users before making the decision of installing a specific application.…”

Section: Usagementioning

confidence: 99%

User, Usage and Usability: Redefining Human Centric Cyber Security

Grobler¹,

Gaire²,

Nepal³

2021

Front. Big Data

View full text Add to dashboard Cite

The effectiveness of cyber security measures are often questioned in the wake of hard hitting security events. Despite much work being done in the field of cyber security, most of the focus seems to be concentrated on system usage. In this paper, we survey advancements made in the development and design of the human centric cyber security domain. We explore the increasing complexity of cyber security with a wider perspective, defining user, usage and usability (3U’s) as three essential components for cyber security consideration, and classify developmental efforts through existing research works based on the human centric security design, implementation and deployment of these components. Particularly, the focus is on studies that specifically illustrate the shift in paradigm from functional and usage centred cyber security, to user centred cyber security by considering the human aspects of users. The aim of this survey is to provide both users and system designers with insights into the workings and applications of human centric cyber security.

show abstract

Section: Usagementioning

confidence: 99%

User, Usage and Usability: Redefining Human Centric Cyber Security

Grobler¹,

Gaire²,

Nepal³

2021

Front. Big Data

View full text Add to dashboard Cite

show abstract

“…In this paper, we use a metric as shown in (6) to measure the similarity of color features between the target image and the input test image. In (6), I ref and I inp represent the target image and the input image, respectively. W and H mean the horizontal length and the vertical length of the sample data, respectively.…”

Section: Detection Of Faulty Imagesmentioning

confidence: 99%

“…W and H mean the horizontal length and the vertical length of the sample data, respectively. In (6), the color similarity is normalized to a value between 0 and 100 for ease of calculation. (6) In this paper, we use the similarity measure as shown in (7).…”

Section: Detection Of Faulty Imagesmentioning

confidence: 99%

“…In (6), the color similarity is normalized to a value between 0 and 100 for ease of calculation. (6) In this paper, we use the similarity measure as shown in (7). In 7 (7) In this paper, we define the similarity measure like (8) to calculate the final similarity between a target image and a test image by integrating similarity measure of color feature and texture feature.…”

Section: Detection Of Faulty Imagesmentioning

confidence: 99%

“…In particular, these devices have high-speed wired and wireless network functions and location-based sensors, thus the functions of the applications being developed are becoming more diverse [1][2][3][4][5]. Applications developed in this way run on a variety of platforms, and they are actually applied and used in various fields related to the Fourth Industrial Revolution, including artificial intelligence, autonomous driving, robots, drones, 3D printers, virtual reality and extended reality [6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Effective Image Quality Inspection Based on Color and Texture Features

Jang*,

Lee*

2020

IJRTE

View full text Add to dashboard Cite

As people’s interest in software increases, the number and types of newly developed applications increase day by day. Therefore, there are attempts to automatically check whether the newly developed interface of these programs works correctly through image processing instead of manually. In this paper, we describe a strategy to robustly detect execution error screens of applications through comparative analysis of key features from various kinds of image scenes. In the approach described in this study, we extract the main multiple features representing the image. Then, by comparing the difference of the extracted multiple features, it is effectively determined whether the image is the same normal image as the reference image or an error image similar to the target image but different from each other. Experimental results verify that the described algorithm accurately detects normal and faulty images by comparing the main multiple features from various types of images. For performance evaluation, we quantitatively compared the performance of the introduced dissimilar region extraction strategy with those of other conventional methods. The existing methods of extracting similarity between images based on one feature or histogram comparison mostly lack information to sufficiently express the entire image. Therefore, when similar areas between two images are extracted, many errors occurred due to incorrect matching. However, the proposed multiple feature-based method obtains richer information by extracting multiple features from the input image. In addition, because the matching is done based on this information, the accuracy is relatively high. The approach introduced in this study is expected to be effectively used in many practical applications related to image processing such as image retrieval, trademark comparison, video security, application quality inspection, etc.

show abstract

Signalling over-privileged mobile applications using passive security indicators

Cited by 2 publications

References 2 publications

User, Usage and Usability: Redefining Human Centric Cyber Security

User, Usage and Usability: Redefining Human Centric Cyber Security

Effective Image Quality Inspection Based on Color and Texture Features

Contact Info

Product

Resources

About