Biblio

As the technological progress of mobile Internet, smartphone based on Android OS accounts for the vast majority of market share. The traditional encryption technology cannot resolve the dilemma in smartphone information leakage, and the Android-based authentication system in view of biometric recognition emerge to offer more reliable information assurance. In this paper, we summarize several biometrics providing their attributes. Furthermore, we also review the algorithmic framework and performance index acting on authentication techniques. Thus, typical identity authentication systems including their experimental results are concluded and analyzed in the survey. The article is written with an intention to provide an in-depth overview of Android-based biometric verification systems to the readers.

GPS signals, the main origin of navigation, are not functional in indoor environments. Therefore, Wi-Fi access points have started to be increasingly used for localization and tracking inside the buildings by relying on fingerprint-based approach. However, with these types of approaches, several concerns regarding the privacy of the users have arisen. Malicious individuals can determine a clients daily habits and activities by simply analyzing their wireless signals. While there are already efforts to incorporate privacy to the existing fingerprint-based approaches, they are limited to the characteristics of the homo-morphic cryptographic schemes they employed. In this paper, we propose to enhance the performance of these approaches by exploiting another homomorphic algorithm, namely DGK, with its unique encrypted sorting capability and thus pushing most of the computations to the server side. We developed an Android app and tested our system within a Columbia University dormitory. Compared to existing systems, the results indicated that more power savings can be achieved at the client side and DGK can be a viable option with more powerful server computation capabilities.

In pervasive computing, the human-computer interaction emphasizes on information and communication technology and user experience. Now it is possible to communicate scientific and engineering technique informally through leisure activities, for instance aquascaping. It is necessary to keep the aquascape environment fresh and healthy, and the fish have to be feed regularly. This paper proposes an autonomous aquascape preservation system based on Arduino controller connected to a remote Android smartphone. However, it is widely known that the wireless communication is not as reliable as the wired counterpart. An unauthorized party should not be able to take control of the wireless aquascape preservation system. SIMON lightweight cryptography is used to tackle security issues in constrained devices. From experiments result, the DS18B20 sensor is able to measure aquascape temperature precisely with approximately 0.5% tolerance. The Android graphical user interface application is user-friendly. Moreover, the SIMON lightweight encryption SIMON64/128 is able to secure wireless communication channel efficiently with small hardware footprints.

Detecting repackaged apps is one of the important issues in the Android ecosystem. Many attackers usually reverse engineer a legitimate app, modify or embed malicious codes into the app, repackage and distribute it in the online markets. They also employ code obfuscation techniques to hide app cloning or repackaging. In this paper, we propose a new technique for detecting repackaged Android apps, which is robust to code obfuscation. The technique analyzes the similarity of Android apps based on the method call information of component classes that receive implicit intents. We developed a tool Calldroid that implemented the proposed technique, and evaluated it on apps transformed using well-known obfuscators. The evaluation results showed that the proposed technique can effectively detect repackaged apps.

Android applications (Apps) have penetrated almost every aspect of our lives, bring users great convenience as well as security concerns. Even though Android system adopts permission mechanism to restrict Apps from accessing important resources of a smartphone, such as telephony, camera and GPS location, users face still significant risk of privacy leakage due to the overprivileged permissions. The overprivileged permission means the extra permission declared by the App but has nothing to do with its function. Unfortunately, there doesn't exist any tool for ordinary users to detect the overprivileged permission of an App, hence most users grant any permission declared by the App, intensifying the risk of private information leakage. Although some previous studies tried to solve the problem of permission overprivilege, their methods are not applicable nowadays because of the progress of App protection technology and the update of Android system. Towards this end, we develop a user-friendly tool based on frequent item set mining for the detection of overprivileged permissions of Android Apps, which is named Droidtector. Droidtector can operate in online or offline mode and users can choose any mode according to their situation. Finally, we run Droidtector on 1000 Apps crawled from Google Play and find that 479 of them are overprivileged, accounting for about 48% of all the sample Apps.

Insecure data storage may open a door to malicious malware to steal users' and system sensitive information. These problems may due to developer negligence or lack of security knowledge. Android developers use various storage methods to store data. However, Attackers have attacked these vulnerable data storage. Although the developers have modified the apps after knowing the vulnerability, the user's personal information has been leaked and caused serious consequences. As a result, instead of patching and fixing the vulnerability, we should conduct proactive control for secure Android data storage. In this paper, we analyzed Android external storage vulnerability and discussed the prevention solutions to prevent sensitive information in external storage from disclosure.

Recently, damage caused by ransomware has been increasing in PC and Android environments. There are many studies into real-time ransomware detection because the most important time to prevent encryption is before ransomware is able to execute its malicious process. Traditional analyses determine an application is ransomware or not by static/dynamic methods. Those analyses can serve as components of a method to detect ransomware in real time. However, problems can occur such as the inability to detect new/variant/unknown ransomware. These types require signed patches from a trusted party that can only be created after attacks occur. In a previous study into realtime new/variant/unknown ransomware detection in a PC environment, important files are monitored and only programs that have been previously analyzed and evaluated as nonmalicious are allowed. As such, programs that have not been analyzed are restricted from accessing important files. In an Android environment, this method can be applied using Android applications to prevent emerging threats and verify consistency with user intent. Thus, this paper proposes a method of detecting new/variant/unknown ransomware in real time in an Android environment.

Air-gapped computers are hermetically isolated from the Internet to eliminate any means of information leakage. In this paper we present HOTSPOT - a new type of airgap crossing technique. Signals can be sent secretly from air-gapped computers to nearby smartphones and then on to the Internet - in the form of thermal pings. The thermal signals are generated by the CPUs and GPUs and intercepted by a nearby smartphone. We examine this covert channel and discuss other work in the field of air-gap covert communication channels. We present technical background and describe thermal sensing in modern smartphones. We implement a transmitter on the computer side and a receiver Android App on the smartphone side, and discuss the implementation details. We evaluate the covert channel and tested it in a typical work place. Our results show that it possible to send covert signals from air-gapped PCs to the attacker on the Internet through the thermal pings. We also propose countermeasures for this type of covert channel which has thus far been overlooked.

Prior work on mobile app reviews has demonstrated that user reviews contain a wealth of information and are seen as a potential source of requirements. However, most of the studies done in this area mainly focused on mining and analyzing user reviews from the US App Store, leaving reviews of users from other countries unexplored. In this paper, we seek to understand if the perception of the same apps between users from other countries and that from the US differs through analyzing user reviews. We retrieve 300,643 user reviews of the 15 most downloaded iOS apps of 2018, published directly by Apple, from nine English-speaking countries over the course of 5 months. We manually classify 3,358 reviews into several software quality and improvement factors. We leverage a random forest based algorithm to identify factors that can be used to differentiate reviews between the US and other countries. Our preliminary results show that all countries have some factors that are proportionally inconsistent with the US.

While enjoying the convenience brought by mobile phones, users have been exposed to high risk of private information leakage. It is known that many applications on mobile devices read private data and send them to remote servers. However how, when and in what scale the private data are leaked are not investigated systematically in the real-world scenario. In this paper, a framework is proposed to analyze the usage data from mobile devices and the traffic data from the mobile network and make a comprehensive privacy leakage detection and privacy inference mining on a large scale of realworld mobile data. Firstly, this paper sets up a training dataset and trains a privacy detection model on mobile traffic data. Then classical machine learning tools are used to discover private usage patterns. Based on our experiments and data analysis, it is found that i) a large number of private information is transmitted in plaintext, and even passwords are transmitted in plaintext by some applications, ii) more privacy types are leaked in Android than iOS, while GPS location is the most leaked privacy in both Android and iOS system, iii) the usage pattern is related to mobile device price. Through our experiments and analysis, it can be concluded that mobile privacy leakage is pervasive and serious.

In this paper, we propose the first traffic monitoring and labeling system for iOS devices, named iMonitor, which not just captures mobile network traffic in .pcap files, but also provides comprehensive APP-related and user-related information of captured packets. Through further analysis, one can obtain the exact APP or device where each packet comes from. The labeled traffic can be used in many research areas for mobile security, such as privacy leakage detection and user profiling. Given the implementation methodology of NetworkExtension framework of iOS 9+, APP labels of iMonitor are reliable enough so that labeled traffic can be regarded as training data for any traffic classification methods. Evaluations on real iPhones demonstrate that iMonitor has no notable impact upon user experience even with slight packet latency. Also, the experiment result supports our motivation that mobile traffic monitoring for iOS is absolutely necessary, as traffic generated by different OSes like Android and iOS are different and unreplaceable in researches.

People increasingly rely on mobile devices for banking transactions or two-factor authentication (2FA) and thus trust in the security provided by the underlying operating system. Simultaneously, jailbreaks gain tremendous popularity among regular users for customizing their devices. In this paper, we show that both do not go well together: Jailbreaks remove vital security mechanisms, which are necessary to ensure a trusted environment that allows to protect sensitive data, such as login credentials and transaction numbers (TANs). We find that all but one banking app, available in the iOS App Store, can be fully compromised by trivial means without reverse-engineering, manipulating the app, or other sophisticated attacks. Even worse, 44% of the banking apps do not even try to detect jailbreaks, revealing the prevalent, errant trust in the operating system's security. This study assesses the current state of security of banking apps and pleads for more advanced defensive measures for protecting user data.

As the accessibility of high-resolution smartphone camera has increased and an improved computational speed, it is now convenient to build Business Card Readers on mobile phones. The project aims to design and develop a Business Card Reader (BCR) Application for iOS devices, using an open-source OCR Engine - Tesseract. The system accuracy was tested and evaluated using a dataset of 55 digital business cards obtained from an online repository. The accuracy result of the system was up to 74% in terms of both text recognition and data detection. A comparative analysis was carried out against a commercial business card reader application and our application performed vastly reasonable.

Increased use of secure chat and voice/ video apps has transformed the social life. While the benefits and facilitations are seemingly limitless, so are the asscoiacted vulnerabilities and threats. Besides ensuring confidentiality requirements for common users, known facts of non-readable contents over the network make these apps more attractive for criminals. Though access to contents of cryptograhically secure sessions is not possible, network forensics of secure apps can provide interesting information which can be of great help during criminal invetigations. In this paper, we presented a novel framework of profiling the secure chat and voice/ video calling apps which can be employed to extract hidden patterns about the app, information of involved parties, activities of chatting, voice/ video calls, status indications and notifications while having no information of communication protocol of the app and its security architecture. Signatures of any secure app can be developed though our framework and can become base of a large scale solution. Our methodology is considered very important for different cases of criminal investigations and bussiness intelligence solutions for service provider networks. Our results are applicable to any mobile platform of iOS, android and windows.

Software Engineering is a field of new challenges every day. With every passing day, new technologies emerge. There was an era of web Applications, but the time has changed and most of the web Applications are available as Mobile Applications as well. The Mobile Applications are either android based or iOS based. To deliver error free, secure and reliable Application, it is necessary to test the Applications properly. Software testing is a phase of software development life cycle, where we test an Application in all aspects. Nowadays different type of tools are available for testing an Application automatically but still we have too many challenges for applying test cases on a given Application. In this paper the authors will discuss the challenges of automation of test cases for a Mobile based payment Application.

This paper presents a detailed analysis of some relevant security features of iOS and Android -the two most popular operating systems for mobile devices- from the perspective of user privacy. In particular, permissions that can be modified at run time on these platforms are analyzed. Additionally, a framework is introduced for permission analysis, a hybrid mobile application that can run on both iOS and Android. The framework, which can be extended, places special emphasis on the relationship between the user's privacy and the permission system.

This article is devoted to new asynchronous methods for rendering text information in mobile applications for iOS operating system.

The growing use of smart phones has also given opportunity to the intruders to create malicious apps thereby the security and privacy concerns of a novice user has also grown. This research focuses on the privacy concerns of a user who unknowingly installs a malicious apps created by the programmer. In this paper we created an attack scenario and created an app capable of compromising the privacy of the users. After accepting all the permissions by the user while installing the app, the app allows us to track the live location of the Android device and continuously sends the GPS coordinates to the server. This spying app is also capable of sending the call log details of the user. This paper evaluates two leading smart phone operating systems- Android and IOS to find out the flexibility provided by the two operating systems to their programmers to create the malicious apps.

Providing fault tolerance in Mobile Ad hoc Networks (MANETs) is very tricky activity as nodes migrate from one place to other place and changes network topology. Also MANET is very susceptible for various attacks like DoS attacks etc. So providing security to MANET is also very difficult job. Multipath protocols provide better results than unipath protocols. Multipath protocols provide fault tolerance but many multipath protocols for MANETs not targeted security issues. Distributed and cooperative security that means Intrusion Detection System (IDS) gives better security to MANETs. In this paper we have discussed many confronts and concerns regarding fault tolerance and IDS.

Users can directly access and share information from portable devices such as a smartphone or an Internet of Things (IoT) device. However, to prevent them from becoming victims to launch cyber attacks, they must allow selective sharing based on roles of the users such as with the Ciphertext-Policy Attribute Encryption (CP-ABE) scheme. However, to match the resource constraints, the scheme must be efficient for storage. It must also protect the device from malicious users as well as allow uninterrupted access to valid users. This paper presents the CCA secure PROxy-based Scalable Revocation for Constant Cipher-text (C-PROSRCC) scheme, which provides scalable revocation for a constant ciphertext length CP-ABE scheme. The scheme has a constant number of pairings and computations. It can also revoke any number of users and does not require re-encryption or redistribution of keys. We have successfully implemented the C-PROSRCC scheme. The qualitative and quantitative comparison with related schemes indicates that C-PROSRCC performs better with acceptable overheads. C-PROSRCC is Chosen Ciphertext Attack (CCA) secure. We also present a case study to demonstrate the use of C-PROSRCC for mobile-based selective sharing of a family car.

With the rapid development of mobile internet, mobile devices are requiring more complex authorization policy to ensure an secure access control on mobile data. However mobiles have limited resources (computing, storage, etc.) and are not suitable to execute complex operations. Cloud computing is an increasingly popular paradigm for accessing powerful computing resources. Intuitively we can solve that problem by moving the complex access control process to the cloud and implement a fine-grained access control relying on the powerful cloud. However the cloud computation may not be trusted, a crucial problem is how to verify the correctness of such computations. In this paper, we proposed a public verifiable cloud access control scheme based on Parno's public verifiable computation protocol. For the first time, we proposed the conception and concrete construction of verifiable cloud access control. Specifically, we firstly design a user private key revocable Key Policy Attribute Based Encryption (KP-ABE) scheme with non-monotonic access structure, which can be combined with the XACML policy perfectly. Secondly we convert the XACML policy into the access structure of KP-ABE. Finally we construct a security provable public verifiable cloud access control scheme based on the KP-ABE scheme we designed.

Crowdsensing, driven by the proliferation of sensor-rich mobile devices, has emerged as a promising data sensing and aggregation paradigm. Despite useful, traditional crowdsensing systems typically rely on a centralized third-party platform for data collection and processing, which leads to concerns like single point of failure and lack of operation transparency. Such centralization hinders the wide adoption of crowdsensing by wary participants. We therefore explore an alternative design space of building crowdsensing systems atop the emerging decentralized blockchain technology. While enjoying the benefits brought by the public blockchain, we endeavor to achieve a consolidated set of desirable security properties with a proper choreography of latest techniques and our customized designs. We allow data providers to safely contribute data to the transparent blockchain with the confidentiality guarantee on individual data and differential privacy on the aggregation result. Meanwhile, we ensure the service correctness of data aggregation and sanitization by delicately employing hardware-assisted transparent enclave. Furthermore, we maintain the robustness of our system against faulty data providers that submit invalid data, with a customized zero-knowledge range proof scheme. The experiment results demonstrate the high efficiency of our designs on both mobile client and SGX-enabled server, as well as reasonable on-chain monetary cost of running our task contract on Ethereum.

Virtual reality (VR) recently is a promising technique in both industry and academia due to its potential applications in immersive experiences including website, game, tourism, or museum. VR technique provides an amazing 3-Dimensional (3D) experiences by requiring a very high amount of elements such as images, texture, depth, focus length, etc. However, in order to apply VR technique to various devices, especially in mobiles, ultra-high transmission rate and extremely low latency are really big challenge. Considering this problem, this paper proposes a novel combination model by transforming the computing capability of VR device into an equivalent caching amount while remaining low latency and fast transmission. In addition, Classic caching models are used to computing and catching capabilities which is easily apply to multi-user models.

Nowadays, mobile devices have become one of the most popular instruments used by a person on its regular life, mainly due to the importance of their applications. In that context, mobile devices store user's personal information and even more data, becoming a personal tracker for daily activities that provides important information about the user. Derived from this gathering of information, many tools are available to use on mobile devices, with the restrain that each tool only provides isolated information about a specific application or activity. Therefore, the present work proposes a tool that allows investigators to obtain a complete report and timeline of the activities that were performed on the device. This report incorporates the information provided by many sources into a unique set of data. Also, by means of an example, it is presented the operation of the solution, which shows the feasibility in the use of this tool and shows the way in which investigators have to apply the tool.

Outsourcing services to cloud server (CS) becomes popular in these years. However, the outsourced services often involve with sensitive activity and CS naturally becomes a target of varieties of attacks. Even worse, CS itself can misuse the outsourced services for illegal profit. Traditional online banking system also can make use of a cloud framework to provide economical and high-speed online services to the consumers, which makes the financial dealing easy and convenient. Most of the banking organizations provide services through passbook, ATM, mobile banking, electronic banking (e-banking) etc. Among these, the e-banking and mobile banking are more convenient and becomes essential. Therefore, it is critical to provide an efficient, reliable and more importantly, secure e-banking services to the consumers. The cloud environment is suitable paradigm to a new, small and medium scale banking organization as it eliminates the requirement for them to start with small resources and increase gradually as the service demand rises. However, security is one of the main concerns since it deals with many sensitive data of the valuable customers. In addition to this, the access of various data needs to be restricted to prevent any unauthorized transaction. Nagaraju et al. presented a framework to achieve reliability and security in public cloud based online banking using multi-factor authentication concept. Unfortunately, the login and authentication protocol of this framework is prone to impersonation attack. In this paper, we have revised the framework to avoid this attack.