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.

With the current significant penetration of mobile devices (i.e. smartphones and tablets) and the tremendous increase in the number of the corresponding mobile applications, they have become an indispensable part of our lives. Nowadays, there is a significant growth in the number of sensitive applications such as personal health applications, personal financial applications, home monitoring applications, etc. In addition, with the significant growth of Internet-of-Things (IoT) devices, smartphones and the corresponding applications are widely considered as the Internet gateways for these devices. Mobile devices mostly use wireless LANs (WLANs) (i.e., WiFi networks) as the prominent network interface to the Internet. However, due to the broadcast nature of WiFi links, wireless traffics are exposed to any eavesdropping adversary within the WLAN. Despite WiFi encryption, studies show that application usage information could be inferred from the encrypted wireless traffic. The leakage of this sensitive information is very serious issue that will significantly impact users' privacy and security. In addressing this privacy concern, we design and develop a lightweight programmable privacy framework, called PrivacyGuard. PrivacyGuard is inspired by the vision of pushing the Software Defined Network (SDN)-like paradigm all the way to wireless network edge, is designed to support of adopting privacy preserving policies to protect the wireless communication of the sensitive applications. In this paper, we demonstrate and evaluate a prototype of PrivacyGuard framework on Android devices showing the flexibility and efficiency of the framework.

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.

The paper is devoted to the comparison of performance of prospective lightweight block cipher Cypress with performances of the known modern lightweight block ciphers such as AES, SPECK, SPARX etc. The measurement was done on different platforms: Windows, Linux and Android. On all platforms selected, the block cipher Cypress showed the best results. The block cipher Cypress-256 showed the highest performance on Windows x32 (almost 3.5 Gbps), 64-bit Linux (over 8 Gbps) and Android (1.3 Gbps). On Windows x64 the best result was obtained by Cypress- 512 (almost 5 Gbps).

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.

Malware variants exhibit polymorphic attacks due to the tremendous growth of the present technologies. For instance, ransomware, an astonishingly growing set of monetary-gain threats in the recent years, is peculiarized as one of the most treacherous cyberthreats against innocent individuals and businesses by locking their devices and/or encrypting their files. Many proposed attempts have been introduced by cybersecurity researchers aiming at mitigating the epidemic of the ransomware attacks. However, this type of malware is kept refined by utilizing new evasion techniques, such as sophisticated codes, dynamic payloads, and anti-emulation techniques, in order to survive against detection systems. This paper introduces RanDetector, a new automated and lightweight system for detecting ransomware applications in Android platform based on their behavior. In particular, this detection system investigates the appearance of some information that is related to ransomware operations in an inspected application before integrating some supervised machine learning models to classify the application. RanDetector is evaluated and tested on a dataset of more 450 applications, including benign and ransomware. Hence, RanDetector has successfully achieved more that 97.62% detection rate with nearly zero false positive.

We introduce MobiCeal, the first practical Plausibly Deniable Encryption (PDE) system for mobile devices that can defend against strong coercive multi-snapshot adversaries, who may examine the storage medium of a user's mobile device at different points of time and force the user to decrypt data. MobiCeal relies on "dummy write" to obfuscate the differences between multiple snapshots of storage medium due to existence of hidden data. By incorporating PDE in block layer, MobiCeal supports a broad deployment of any block-based file systems on mobile devices. More importantly, MobiCeal is secure against side channel attacks which pose a serious threat to existing PDE schemes. A proof of concept implementation of MobiCeal is provided on an LG Nexus 4 Android phone using Android 4.2.2. It is shown that the performance of MobiCeal is significantly better than prior PDE systems against multi-snapshot adversaries.

In this paper, we discuss the digital forensic procedure and techniques for analyzing the local artifacts from four popular Instant Messaging applications in Android. As part of our findings, the user chat messages details and contacts were investigated for each application. By using two smartphones with different brands and the latest Android operating systems as experimental objects, we conducted digital investigations in a forensically sound manner. We summarize our findings regarding the different Instant Messaging chat modes and the corresponding encryption status of artifacts for each of the four applications. Our findings can be helpful to many mobile forensic investigations. Additionally, these findings may present values to Android system developers, Android mobile app developers, mobile security researchers as well as mobile users.

Most mobile applications generate local data on internal memory with SharedPreference interface of an Android operating system. Therefore, many possible loopholes can access the confidential information such as passwords. We propose a hybrid encryption approach for SharedPreferences to protect the leaking confidential information through the source code. We develop an Android application and store some data using SharedPreference. We produce different experiments with which this data could be accessed. We apply Hybrid encryption approach combining encryption approach with Android Keystore system, for providing better encryption algorithm to hide sensitive data.

Wireless cameras are widely deployed in surveillance systems for security guarding. However, the privacy concerns associated with unauthorized videotaping, are drawing an increasing attention recently. Existing detection methods for unauthorized wireless cameras are either limited by their detection accuracy or requiring dedicated devices. In this paper, we propose DeWiCam, a lightweight and effective detection mechanism using smartphones. The basic idea of DeWiCam is to utilize the intrinsic traffic patterns of flows from wireless cameras. Compared with traditional traffic pattern analysis, DeWiCam is more challenging because it cannot access the encrypted information in the data packets. Yet, DeWiCam overcomes the difficulty and can detect nearby wireless cameras reliably. To further identify whether a camera is in an interested room, we propose a human-assisted identification model. We implement DeWiCam on the Android platform and evaluate it with extensive experiments on 20 cameras. The evaluation results show that DeWiCam can detect cameras with an accuracy of 99% within 2.7 s.

Recent research suggests that 88% of Android applications that use Java cryptographic APIs make at least one mistake, which results in an insecure implementation. It is unclear, however, if these mistakes originate from code written by application or third-party library developers. Understanding the responsible party for a misuse case is important for vulnerability disclosure. In this paper, we bridge this knowledge gap and introduce source attribution to the analysis of cryptographic API misuse. We developed BinSight, a static program analyzer that supports source attribution, and we analyzed 132K Android applications collected in years 2012, 2015, and 2016. Our results suggest that third-party libraries are the main source of cryptographic API misuse. In particular, 90% of the violating applications, which contain at least one call-site to Java cryptographic API, originate from libraries. When compared to 2012, we found the use of ECB mode for symmetric ciphers has significantly decreased in 2016, for both application and third-party library code. Unlike application code, however, third-party libraries have significantly increased their reliance on static encryption keys for symmetric ciphers and static IVs for CBC mode ciphers. Finally, we found that the insecure RC4 and DES ciphers were the second and the third most used ciphers in 2016.

First standardized by the IETF in the 1990's, SSL/TLS is the most widely-used encryption protocol on the Internet. This makes it imperative to study its usage across different platforms and applications to ensure proper usage and robustness against attacks and vulnerabilities. While previous efforts have focused on the usage of TLS in the desktop ecosystem, there have been no studies of TLS usage by mobile apps at scale. In our study, we use anonymized data collected by the Lumen mobile measurement app to analyze TLS usage by Android apps in the wild. We analyze and fingerprint handshake messages to characterize the TLS APIs and libraries that apps use, and evaluate their weaknesses. We find that 84% of apps use the default TLS libraries provided by the operating system, and the remaining apps use other TLS libraries for various reasons such as using TLS extensions and features that are not supported by the Android TLS libraries, some of which are also not standardized by the IETF. Our analysis reveals the strengths and weaknesses of each approach, demonstrating that the path to improving TLS security in the mobile platform is not straightforward. Based on work published at: Abbas Razaghpanah, Arian Akhavan Niaki, Narseo Vallina-Rodriguez, Srikanth Sundaresan, Johanna Amann, and Phillipa Gill. 2017. Studying TLS Usage in Android Apps. In Proceedings of CoNEXT '17. ACM, New York, NY, USA, 13 pages. https://doi.org/10.1145/3143361.3143400

With the rapid development of Android systems and the growing of Android market, Android system has become a focus of developers and users. MTK6795 is System-on-a-chip (SoC), which is specially designed by MediaTek for high-end smart phones. It integrates the application processor and the baseband processor in just one chip. In this paper, a new encryption method based on the baseband processor of MT6795 SoC is proposed and successfully applied on one Android-based smart phone to protect user data. In this method, the encryption algorithm and private user data are isolated into two processors, which improves the security of users' private data.

Application repackaging is a severe threat to Android users and the market. Existing countermeasures mostly detect repackaging based on app similarity measurement and rely on a central party to perform detection, which is unscalable and imprecise. We instead consider building the detection capability into apps, such that user devices are made use of to detect repackaging in a decentralized fashion. The main challenge is how to protect repackaging detection code from attacks. We propose a creative use of logic bombs, which are regularly used in malware, to conquer the challenge. A novel bomb structure is invented and used: the trigger conditions are constructed to exploit the differences between the attacker and users, such that a bomb that lies dormant on the attacker side will be activated on one of the user devices, while the repackaging detection code, which is packed as the bomb payload, is kept inactive until the trigger conditions are satisfied. Moreover, the repackaging detection code is woven into the original app code and gets encrypted; thus, attacks by modifying or deleting suspicious code will corrupt the app itself. We have implemented a prototype, named BombDroid, that builds the repackaging detection into apps through bytecode instrumentation, and the evaluation shows that the technique is effective, efficient, and resilient to various adversary analysis including symbol execution, multi-path exploration, and program slicing.

In contrast to the Electronic Medical Record (EMR) and Electronic Health Record (EHR) systems that are created to maintain and manage patient data by health professionals and organizations, Personal Health Record (PHR) systems are operated and managed by patients. Therefore, it necessitates increased attention to the importance of security and privacy challenges, as patients are most often unfamiliar with the potential security threats that can result from release of their health data. On the other hand, the use of PHR systems is increasingly becoming an important part of the healthcare system by sharing patient information among their circle of care. To have a system with a more favorable interface and a high level of security, it is crucial to provide a mobile application for PHR that fulfills six important features: (1) ease the usage for various patient demographics and their delegates, (2) security, (3) quickly transfer patient data to their health professionals, (4) give the ability of access revocation to the patient, (5) provide ease of interaction between patients and their circle of care, and (6) inform patients about any instances of access to their data by their circle of care. In this work, we propose an implementation of a Privacy-Preserving PHR system (P3HR) for Android devices to fulfill the above six characteristics, using a Ciphertext Policy Attribute Based Encryption to enhance security and privacy of the system, as well as providing access revocation in a hierarchical scheme of the health professionals and organizations involved. Using this application, patients can securely store their health data, share the records, and receive feedback and recommendations from their circle of care.

Android applications are vulnerable to reverse engineering which could result in tampering and repackaging of applications. Even though there are many off the shelf obfuscation tools that hardens Android applications, they are limited to basic obfuscation techniques. Obfuscation techniques that transform the code segments drastically are difficult to implement on Android because of the Android runtime verifier which validates the loaded code. In this paper, we introduce a novel obfuscation technique, Android Encryption based Obfuscation (AEON), which can encrypt code segments and perform runtime decryption during execution. The encrypted code is running outside of the normal Android virtual machine, in an embeddable Java source interpreter and thereby circumventing the scrutiny of Android runtime verifier. Our obfuscation technique works well with Android source code and Dalvik bytecode.

Opportunistic Networks are delay-tolerant mobile networks with intermittent node contacts in which data is transferred with the store-carry-forward principle. Owners of smartphones and smart objects form such networks due to their social behaviour. Opportunistic Networking can be used in remote areas with no access to the Internet, to establish communication after disasters, in emergency situations or to bypass censorship, but also in parallel to familiar networking. In this work, we create a mobile network application that connects Android devices over Wi-Fi, offers identification and encryption, and gathers information for routing in the network. The network application is constructed in such a way that third party applications can use the network application as network layer to send and receive data packets. We create secure and reliable connections while maintaining a high transmission speed, and with the gathered information about the network we offer knowledge for state of the art routing protocols. We conduct tests on connectivity, transmission range and speed, battery life and encryption speed and show a proof of concept for routing in the network.

The growing popularity of Android and the increasing amount of sensitive data stored in mobile devices have lead to the dissemination of Android ransomware. Ransomware is a class of malware that makes data inaccessible by blocking access to the device or, more frequently, by encrypting the data; to recover the data, the user has to pay a ransom to the attacker. A solution for this problem is to backup the data. Although backup tools are available for Android, these tools may be compromised or blocked by the ransomware itself. This paper presents the design and implementation of RANSOMSAFEDROID, a TrustZone based backup service for mobile devices. RANSOMSAFEDROID is protected from malware by leveraging the ARM TrustZone extension and running in the secure world. It does backup of files periodically to a secure local persistent partition and pushes these backups to external storage to protect them from ransomware. Initially, RANSOMSAFEDROID does a full backup of the device filesystem, then it does incremental backups that save the changes since the last backup. As a proof-of-concept, we implemented a RANSOMSAFEDROID prototype and provide a performance evaluation using an i.MX53 development board.

Mobile apps are widely adopted in daily life, and contain increasing security flaws. Many regulatory agencies and organizations have announced security guidelines for app development. However, most security guidelines involving technicality and compliance with this requirement is not easily feasible. Thus, we propose Mobile Apps Assessment and Analysis System (MAS), an automatic security validation system to improve guideline compliance. MAS combines static and dynamic analysis techniques, which can be used to verify whether android apps meet the security guideline requirements. We implemented MAS in practice and verified 143 real-world apps produced by the Taiwan government. Besides, we also validated 15,000 popular apps collected from Google Play Store produced in three countries. We found that most apps contain at least three security issues. Finally, we summarize the results and list the most common security flaws for consideration in further app development.

Mobile attack approaches can be categorized as Application Based Attacks and Frequency Based Attacks. Application based attacks are reviewed extensively in the literature. However, frequency based attacks to mobile phones are not experimented in detail. In this work, we have experimentally succeeded to attack an Android smartphone using a simple software based radio circuit. We have developed a software “Primary Mobile Hack Builder” to control Android operated cellphone as a distance. The SMS information and pictures in the cellphone can be obtained using this device. On the other hand, after launching a software into targeting cellphone, the camera of the cellphone can be controlled for taking pictures and downloading them into our computers. It was also possible to eavesdropping the conversation.

The state-of-the-art Android malware often encrypts or encodes malicious code snippets to evade malware detection. In this paper, such undetectable codes are called Mysterious Codes. To make such codes detectable, we design a system called Droidrevealer to automatically identify Mysterious Codes and then decode or decrypt them. The prototype of Droidrevealer is implemented and evaluated with 5,600 malwares. The results show that 257 samples contain the Mysterious Codes and 11,367 items are exposed. Furthermore, several sensitive behaviors hidden in the Mysterious Codes are disclosed by Droidrevealer.