•Effects of formal and self-control on mobile app developers are compared.•Self-control has more positive effects on continuance intention and app quality.•Perceived autonomy mediates the effect of ...self-control on continuance intentions.•Embracing softer governance instruments in platform ecosystems is recommended.
Although control modes have been studied extensively in traditional IS contexts, minimal attention has been directed toward understanding how different control modes operate in platform ecosystems. Drawing on the IS control and self-determination literatures, we examined the differential effects of formal and self-control on third-party developers’ continuance intentions and application quality on mobile software platforms. Two studies from a laboratory experiment (N=138) and a follow-up field survey with Android app developers (N=230) show that self-control is superior to formal control because it allows for higher perceived autonomy that in turn promotes continuance intentions and application quality.
Unlike advertising in traditional media, a mobile platform's in‐app advertising market exhibits two unique features—split structure of the mobile platform with a platform owner and an app developer ...jointly provisioning in‐app advertising, and agency pricing for app sales. We develop a two‐sided market model to analyze the role of these two unique features in determining the platform owner's optimal advertising revenue‐sharing contract. Our results reveal an interesting N‐shaped dynamic regarding the platform owner's optimal choice of her ad revenue share with respect to the overall advertisers’ valuation of in‐app ads. We identify a between‐agent subsidization strategy for the platform owner, where she finds it optimal to subsidize the developer via the advertising channel, leading to greater profits for both of them. We find that the advertising revenue‐sharing contract under agency pricing for app sales leads to a higher app price than would be offered by the integrated platform found in traditional advertising. However, the ad price is coordinated under the platform owner's optimal choice of ad revenue share when she obtains revenue from both the advertising and app sales channels, leading to an alignment of her interest with the app developer's on ad level.
We present a new mobile platform to be used in clinical trials aimed at both collecting data and assessing new technologies and treatments for diabetes care. The main components of the platform are a ...mobile app, that automatically collects data from continuous glucose monitoring sensors and activity trackers, and also allows users to manually log daily events; a cloud database for safe data storage; a web interface, which allows clinicians to monitor patients’ status in real-time. The platform is modular and highly customizable for a multitude of purposes in clinical research. Preliminary tests performed for daily-life data gathering by both clinicians and users are extremely encouraging.
Continued use intention of customers is a critical factor in the development of tourism mobile platforms (TMP), which reflects the degree of users’ attachment to the platforms. However, existing ...research in this field intends to investigate users’ attachment to a TMP by focusing on the overall cognitive satisfaction of the users, which deviates from the “cognition-affect” framework in psychology. Following the stimulus–organism–response (S-O-R) framework, this paper draws upon the attachment theory and the user experience theory, and proposes a model depicting how service experience of TMP affects users’ intention to keep using the TMP through the mediation effect of platform attachment. The empirical results (N = 276) showed that functional experience and social experience positively affect TMP users’ development of platform attachment (i.e., platform dependence and platform identity), which in turn enhance their intention to continuously obtain and provide tourism information
via
the TMP. This study expands the research on the continued use of TMP from an attachment perspective and contributes to the field in both theoretical and practical levels.
This article presents a new mobile platform with two-degree-of-freedom (2-DOF) transformable wheels for service robots, which can overcome steps and stairs of various sizes encountered in indoor ...environments. The concept of the 2-DOF transformable wheel is introduced and the required transformation ranges are examined. In this article, a five-bar PRRRP mechanism is adopted as the base mechanism for 2-DOF transformation. Also, to separate the wheel rotation from the wheel transformation effectively, a four-bar RRPP mechanism is incorporated into the base mechanism. The design variables for the new wheel are determined not only to satisfy the kinematic constraints but also to provide the torque required for the mobile platform called STEP with the new wheels to overcome steps. The experiments using the STEP are performed for different steps and combined steps to prove the good obstacle-overcoming ability of the STEP with the new transformable wheels.
•Mobile platform providers have become central players in the mobile ecosystem.•Satisfaction is an antecedent of app developers’ loyalty to a mobile platform.•The quality of SDK is an important ...determinant of satisfaction and credibility.
Mobile platform providers, including Apple and Google, have grown quickly to become central players in the mobile ecosystem. They now act as gatekeepers of information among multiple niche players in the mobile ecosystem. Many players from different industry sectors have tried to build their ecosystem centered on their own mobile platform, but only a few have succeeded so far. In the so called ‘ecosystem war’, one of the key issues for platform providers is how to retain a sustainable relationship with other niche players in the ecosystem. This paper investigates the factors influencing application developers’ loyalty to mobile platforms. To do this, this paper develops a model with key variables based on loyalty theory and adds variables that reflect the specific context of mobile platforms. The empirical analysis that was conducted in South Korea shows that satisfaction is a direct antecedent of application developers’ loyalty to a mobile platform. The results also show that the quality of a mobile platform’s software development kit (SDK) is one of the important determinants of application developers’ satisfaction with a particular mobile platform and also of the platform’s credibility. However, there is no significant relationship between the credibility and loyalty, which is not consistent with previous studies in different research settings. This provides us a clue to understand how the mobile platform market works and that mobile platform providers have less incentive to create a fair relationship with developers when they have a large customer base.
Machine learning (ML) classifiers have been widely deployed to detect Android malware, but at the same time the application of ML classifiers also faces an emerging problem. The performance of such ...classifiers degrades---or called ages---significantly over time given the malware evolution. Prior works have proposed to use retraining or active learning to reverse and improve aged models. However, the underlying classifier itself is still blind, unaware of malware evolution. Unsurprisingly, such evolution-insensitive retraining or active learning comes at a price, i.e., the labeling of tens of thousands of malware samples and the cost of significant human efforts. In this paper, we propose the first framework, called APIGraph, to enhance state-of-the-art malware classifiers with the similarity information among evolved Android malware in terms of semantically-equivalent or similar API usages, thus naturally slowing down classifier aging. Our evaluation shows that because of the slow-down of classifier aging, APIGraph saves significant amounts of human efforts required by active learning in labeling new malware samples.
HoMonit Zhang, Wei; Meng, Yan; Liu, Yugeng ...
Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security,
10/2018
Conference Proceeding
Smart home is an emerging technology for intelligently connecting a large variety of smart sensors and devices to facilitate automation of home appliances, lighting, heating and cooling systems, and ...security and safety systems. Our research revolves around Samsung SmartThings, a smart home platform with the largest number of apps among currently available smart home platforms. The previous research has revealed several security flaws in the design of SmartThings, which allow malicious smart home apps (or SmartApps) to possess more privileges than they were designed and to eavesdrop or spoof events in the SmartThings platform. To address these problems, this paper leverages side-channel inference capabilities to design and develop a system, dubbed HoMonit, to monitor SmartApps from encrypted wireless traffic. To detect anomaly, HoMonit compares the SmartApps activities inferred from the encrypted traffic with their expected behaviors dictated in their source code or UI interfaces. To evaluate the effectiveness of HoMonit, we analyzed 181 official SmartApps and performed evaluation on 60 malicious SmartApps, which either performed over-privileged accesses to smart devices or conducted event-spoofing attacks. The evaluation results suggest that HoMonit can effectively validate the working logic of SmartApps and achieve a high accuracy in the detection of SmartApp misbehaviors.
The use of mobile devices is rising daily in this technological era. A continuous and increasing number of mobile applications are constantly offered on mobile marketplaces to fulfil the needs of ...smartphone users. Many Android applications do not address the security aspects appropriately. This is often due to a lack of automated mechanisms to identify, test, and fix source code vulnerabilities at the early stages of design and development. Therefore, the need to fix such issues at the initial stages rather than providing updates and patches to the published applications is widely recognized. Researchers have proposed several methods to improve the security of applications by detecting source code vulnerabilities and malicious codes. This Systematic Literature Review (SLR) focuses on Android application analysis and source code vulnerability detection methods and tools by critically evaluating 118 carefully selected technical studies published between 2016 and 2022. It highlights the advantages, disadvantages, applicability of the proposed techniques, and potential improvements of those studies. Both Machine Learning (ML)-based methods and conventional methods related to vulnerability detection are discussed while focusing more on ML-based methods, since many recent studies conducted experiments with ML. Therefore, this article aims to enable researchers to acquire in-depth knowledge in secure mobile application development while minimizing the vulnerabilities by applying ML methods. Furthermore, researchers can use the discussions and findings of this SLR to identify potential future research and development directions.
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