Biblio

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.

With Android application packing technology evolving, there are more and more ways to harden APPs. Manually unpacking APPs becomes more difficult as the time needed for analyzing increase exponentially. At the beginning, the packing technology is designed to prevent APPs from being easily decompiled, tampered and re-packed. But unfortunately, many malicious APPs start to use packing service to protect themselves. At present, most of the antivirus software focus on APPs that are unpacked, which means if malicious APPs apply the packing service, they can easily escape from a lot of antivirus software. Therefore, we should not only emphasize the importance of packing, but also concentrate on the unpacking technology. Only by doing this can we protect the normal APPs, and not miss any harmful APPs at the same time. In this paper, we first systematically study a lot of DEX packing and unpacking technologies, then propose and develop a universal unpacking system, named CrackDex, which is capable of extracting the original DEX file from the packed APP. We propose three core technologies: simulation execution, DEX reassembling, and DEX restoration, to get the unpacked DEX file. CrackDex is a part of the Dalvik virtual machine, and it monitors the execution of functions to locate the unpacking point in the portable interpreter, then launches the simulation execution, collects the data of original DEX file through corresponding structure pointer, finally fulfills the unpacking process by reassembling the data collected. The results of our experiments show that CrackDex can be used to effectively unpack APPs that are packed by packing service in a universal approach without any other knowledge of packing service.

For mobile phone users, short message service (SMS) is the most commonly used text-based communication type on mobile devices. Users can interact with other users and services via SMS. For example, users can send private messages, use information services, apply for a job advertisement, conduct bank transactions, and so on. Users should be very careful when using SMS. During the sending of SMS, the message content should be aware that it can be captured and act accordingly. Based on these findings, the elderly, called as “Silent Generation” which represents 70 years or older adults, are text messaging much more than they did in the past. Therefore, they need solutions which are both simple and secure enough if there is a need to send sensitive information via SMS. In this study, we propose and develop an android application to secure text messages. The application has a simple and easy-to-use graphical user interface but provides significant security.

The rapid growth of science and technology in the telecommunications world can come up with new ways for some people bent on abusing for threatening information security as hackers, crackers, carder, phreaker and so on. If the information is on the wrong side will result in losses. Information that must be considered is the security of confidential information. Steganography is a method that can be used to hide a message by using digital media. Digital Steganography using digital media as the container vessel such as images, sounds, text, and video. Hidden secret data can also include images, audio, text, and video. In this final audio steganography implemented. One method that can be used in steganography is the Least Significant Bit (LSB). Steganography implementation will be accompanied by the application of cryptography in the form of encryption and decryption. This method works is messages that have been encrypted beforehand will be hidden evenly on each region in MP3 or WAV already divided, with modify / change the LSB of the media container with the bits of information to be hidden. In making the steganography application, the author uses the Java programming language eclipse, because the program is quite easy and can be run in the Android smartphone operating system.

Interchange of information through cell phones, Tabs and PDAs (Personal Digital Assistant) is the new trend in the era of digitization. In day-to-day activities, sensitive information through mobile phones is exchanged among the users. This sensitive information can be in the form of text messages, images, location, etc. The research on Android mobile applications was done at the MIT, and found that applications are leaking enormous amount of information to the third party servers. 73 percent of 55 Android applications were detected to leak personal information of the users [8]. Transmission of files securely on Android is a big issue. Therefore it is important to shield the privacy of user data on Android operating system. The main motive of this paper is to protect the privacy of data on Android Platform by allowing transmission of textual data, location, pictures in encrypted format. By doing so, we achieved intimacy and integrity of data.

We propose $μ$Leech, a new embedded trusted platform module for next generation power scavenging devices. Such power scavenging devices are already widely deployed. For instance, the Square point-of-sale reader uses the microphone/speaker interface of a smartphone for communications and as power supply. While such devices are used as trusted devices in security critical applications in the wild, they have not been properly evaluated yet. $μ$Leech can securely store keys and provide cryptographic services to any connected smart phone. Our design also facilitates physical security analysis by providing interfaces to facilitate acquisition of power traces and clock manipulation attacks. Thus $μ$Leech empowers security researchers to analyze leakage in next generation embedded and IoT devices and to evaluate countermeasures before deployment.

The Internet of Vehicles (IoV) is a complex and dynamic mobile network system that enables information sharing between vehicles, their surrounding sensors, and clouds. While IoV opens new opportunities in various applications and services to provide safety on the road, it introduces new challenges in the field of digital forensics investigations. The existing tools and procedures of digital forensics cannot meet the highly distributed, decentralized, dynamic, and mobile infrastructures of the IoV. Forensic investigators will face challenges while identifying necessary pieces of evidence from the IoV environment, and collecting and analyzing the evidence. In this article, we propose TrustIoV - a digital forensic framework for the IoV systems that provides mechanisms to collect and store trustworthy evidence from the distributed infrastructure. Trust-IoV maintains a secure provenance of the evidence to ensure the integrity of the stored evidence and allows investigators to verify the integrity of the evidence during an investigation. Our experimental results on a simulated environment suggest that Trust-IoV can operate with minimal overhead while ensuring the trustworthiness of evidence in a strong adversarial scenario.

Crowd management in urban settings has mostly relied on either classical, non-automated mechanisms or spontaneous notifications/alerts through social networks. Such management techniques are heavily marred by lack of comprehensive control, especially in terms of averting risks in a manner that ensures crowd safety and enables prompt emergency response. In this paper, we propose a Markov Decision Process Scheme MDP to realize a smart infrastructure that is directly aimed at crowd management. A key emphasis of the scheme is a robust and reliable scalability that provides sufficient flexibility to manage a mixed crowd (i.e., pedestrian, cyclers, manned vehicles and unmanned vehicles). The infrastructure also spans various population settings (e.g., roads, buildings, game arenas, etc.). To realize a reliable and scalable crowd management scheme, the classical MDP is decomposed into Local MDPs with smaller action-state spaces. Preliminarily results show that the MDP decomposition can reduce the system global cost and facilitate fast convergence to local near-optimal solution for each L-MDP.

Mobile tracking is a key challenge that has been investigated from both practical and theoretical aspects. This paper proposes an anti-theft mobile phone security system using basic input/output system (BIOS). This mobile phone security system allows us to determine the position of mobile device. The proposed security system is based on hardware implementation technique in which mobile is designed in such a way that a mobile can be traced out even if battery and Subscriber Identity Module (SIM) are plug-out. Furthermore, we also consider the usage of BIOS and its importance in our daily life. Our proposed solution will help the designers in improving the device security.

Smartphones have become the pervasive personal computing platform. Recent years thus have witnessed exponential growth in research and development for secure and usable authentication schemes for smartphones. Several explicit (e.g., PIN-based) and/or implicit (e.g., biometrics-based) authentication methods have been designed and published in the literature. In fact, some of them have been embedded in commercial mobile products as well. However, the published studies report only the brighter side of the proposed scheme(s), e.g., higher accuracy attained by the proposed mechanism. While other associated operational issues, such as computational overhead, robustness to different environmental conditions/attacks, usability, are intentionally or unintentionally ignored. More specifically, most publicly available frameworks did not discuss or explore any other evaluation criterion, usability and environment-related measures except the accuracy under zero-effort. Thus, their baseline operations usually give a false sense of progress. This paper, therefore, presents some guidelines to researchers for designing, implementation, and evaluating smartphone user authentication methods for a positive impact on future technological developments.

Ambient infrasound with frequency ranges well below 20 Hz is known to carry robust navigation cues that can be exploited to authenticate the location of a speaker. Unfortunately, many of the mobile devices like smartphones have been optimized to work in the human auditory range, thereby suppressing information in the infrasonic region. In this paper, we show that these ultra-low frequency cues can still be extracted from a standard smartphone recording by using acceleration-based cepstral features. To validate our claim, we have collected smartphone recordings from more than 30 different scenes and used the cues for scene fingerprinting. We report scene recognition rates in excess of 90% and a feature set analysis reveals the importance of the infrasonic signatures towards achieving the state-of-the-art recognition performance.

Authentication of smartphone users is important because a lot of sensitive data is stored in the smartphone and the smartphone is also used to access various cloud data and services. However, smartphones are easily stolen or co-opted by an attacker. Beyond the initial login, it is highly desirable to re-authenticate end-users who are continuing to access security-critical services and data. Hence, this paper proposes a novel authentication system for implicit, continuous authentication of the smartphone user based on behavioral characteristics, by leveraging the sensors already ubiquitously built into smartphones. We propose novel context-based authentication models to differentiate the legitimate smartphone owner versus other users. We systematically show how to achieve high authentication accuracy with different design alternatives in sensor and feature selection, machine learning techniques, context detection and multiple devices. Our system can achieve excellent authentication performance with 98.1% accuracy with negligible system overhead and less than 2.4% battery consumption.

Software components, which are vulnerable to being exploited, need to be identified and patched. Employing any prevention techniques designed for the purpose of detecting vulnerable software components in early stages can reduce the expenses associated with the software testing process significantly and thus help building a more reliable and robust software system. Although previous studies have demonstrated the effectiveness of adapting prediction techniques in vulnerability detection, the feasibility of those techniques is limited mainly because of insufficient training data sets. This paper proposes a prediction technique targeting at early identification of potentially vulnerable software components. In the proposed scheme, the potentially vulnerable components are viewed as mislabeled data that may contain true but not yet observed vulnerabilities. The proposed hybrid technique combines the supports vector machine algorithm and ensemble learning strategy to better identify potential vulnerable components. The proposed vulnerability detection scheme is evaluated using some Java Android applications. The results demonstrated that the proposed hybrid technique could identify potentially vulnerable classes with high precision and relatively acceptable accuracy and recall.

Android is currently the most widely used mobile environment. This trend encourages malware writers to develop specific attacks targeting this platform with threats designed to covertly collect data or financially extort victims, the so-called ransomware. In this paper we use formal methods, in particular model checking, to automatically dissect ransomware samples. Starting from manual inspection of few samples, we define a set of rule in order to check whether the behaviours we find are representative of ransomware functionalities.

Smartwatches, with motion sensors, are becoming a common utility for users. With the increasing popularity of practical wearable computers, and in particular smartwatches, the security risks linked with sensors on board these devices have yet to be fully explored. Recent research literature has demonstrated the capability of using a smartphone's own accelerometer and gyroscope to infer tap locations; this paper expands on this work to demonstrate a method for inferring smartphone PINs through the analysis of smartwatch motion sensors. This study determines the feasibility and accuracy of inferring user keystrokes on a smartphone through a smartwatch worn by the user. Specifically, we show that with malware accessing only the smartwatch's motion sensors, it is possible to recognize user activity and specific numeric keypad entries. In a controlled scenario, we achieve results no less than 41% and up to 92% accurate for PIN prediction within 5 guesses.

Automation systems are gaining popularity around the world. The use of these powerful technologies for home security has been proposed and some systems have been developed. Other implementations see the user taking a central role in providing and receiving updates to the system. We propose a system making use of an Android based smartphone as the user control point. Our Android application allows for dual factor (facial and secret pin) based authentication in order to protect the privacy of the user. The system successfully implements facial recognition on the limited resources of a smartphone by making use of the Eigenfaces algorithm. The system we created was designed for home automation but makes use of technologies that allow it to be applied within any environment. This opens the possibility for more research into dual factor authentication and the architecture of our system provides a blue print for the implementation of home based automation systems. This system with minimal modifications can be applied within an industrial application.

To establish a secure connection between a mobile user and a remote server, this paper presents a session key agreement scheme through remote mutual authentication protocol by using mobile application software(MAS). We analyzed the security of our protocol informally, which confirms that the protocol is secure against all the relevant security attacks including off-line identity-password guessing attacks, user-server impersonation attacks, and insider attack. In addition, the widely accepted simulator tool AVISPA simulates the proposed protocol and confirms that the protocol is SAFE under the OFMC and CL-AtSe back-ends. Our protocol not only provide strong security against the relevant attacks, but it also achieves proper mutual authentication, user anonymity, known key secrecy and efficient password change operation. The performance comparison is also performed, which ensures that the protocol is efficient in terms of computation and communication costs.

Increased use of Android devices and its open source development framework has attracted many digital crime groups to use Android devices as one of the key attack surfaces. Due to the extensive connectivity and multiple sources of network connections, Android devices are most suitable to botnet based malware attacks. The research focuses on developing a cloud-based Android botnet malware detection system. A prototype of the proposed system is deployed which provides a runtime Android malware analysis. The paper explains architectural implementation of the developed system using a botnet detection learning dataset and multi-layered algorithm used to predict botnet family of a particular application.

The threats of smartphone security are mostly from the privacy disclosure and malicious chargeback software which deducting expenses abnormally. They exploit the vulnerabilities of previous permission mechanism to attack to mobile phones, and what's more, it might call hardware to spy privacy invisibly in the background. As the existing Android operating system doesn't support users the monitoring and auditing of system resources, a dynamic supervisory mechanism of process behavior based on Dalvik VM is proposed to solve this problem. The existing android system framework layer and application layer are modified and extended, and special underlying services of system are used to realize a dynamic supervisory on the process behavior of Dalvik VM. Via this mechanism, each process on the system resources and the behavior of each app process can be monitored and analyzed in real-time. It reduces the security threats in system level and positions that which process is using the system resource. It achieves the detection and interception before the occurrence or the moment of behavior so that it protects the private information, important data and sensitive behavior of system security. Extensive experiments have demonstrated the accuracy, effectiveness, and robustness of our approach.

User uses smartphones for web surfing and browsing data. Many smartphones are embedded with inbuilt location aware system called GPS [Global Positioning System]. Using GPS user have to register and share his all private information to the LBS server. LBS is nothing but Location Based Service. Simply user sends the query to the LBS server. Then what is happening the LBS server gives a private information regarding particular user location. There will be a possibility to misuse this information so using mobile crowd method hides user location from LBS server and avoid sharing of privacy information with server. Our solution does not required to change the LBS server architecture.

Steganography is a method of hiding information, whereas the goal of cryptography is to make data unreadable. Both of these methodologies have their own advantages and disadvantages. Encrypted messages are easily detectable. If someone is spying on communication channel for encrypted message, he/she can easily identify the encrypted messages. Encryption may draw unnecessary attention to the transferred messages. This may lead to cryptanalysis of the encrypted message if the spy tries to know the message. If the encryption technique is not strong enough, the message may be deciphered. In contrast, Steganography tries to hide the data from third party by smartly embedding the data to some other file which is not at all related to the message. Here care is to be taken to minimize the modification of the container file in the process of embedding data. But the disadvantage of steganography is that it is not as secure as cryptography. In the present method the authors have introduced three-step security. Firstly the secret message is encrypted using bit level columnar transposition method introduced by Nath et al and after that the encrypted message is embedded in some image file along with its size. Finally the modified image is encoded into a QR Code TM. The entire method has also been implemented for the Android mobile environment. This method may be used to transfer confidential message through Android mobile phone.

Session management in distributed Internet services is traditionally based on username and password, explicit logouts and mechanisms of user session expiration using classic timeouts. Emerging biometric solutions allow substituting username and password with biometric data during session establishment, but in such an approach still a single verification is deemed sufficient, and the identity of a user is considered immutable during the entire session. Additionally, the length of the session timeout may impact on the usability of the service and consequent client satisfaction. This paper explores promising alternatives offered by applying biometrics in the management of sessions. A secure protocol is defined for perpetual authentication through continuous user verification. The protocol determines adaptive timeouts based on the quality, frequency and type of biometric data transparently acquired from the user. The functional behavior of the protocol is illustrated through Matlab simulations, while model-based quantitative analysis is carried out to assess the ability of the protocol to contrast security attacks exercised by different kinds of attackers. Finally, the current prototype for PCs and Android smartphones is discussed.
 

Security as a condition is the degree of resistance to, or protection from harm. Securing gadgets in a way that is simple for the user to deploy yet, stringent enough to deny any malware intrusions onto the protected circle is investigated to find a balance between the extremes. Basically, the dominant approach on current control access is via password or PIN, but its flaw is being clearly documented. An application (to be incorporated in a mobile phone) that allows the user's gadget to be used as a Biometric Capture device in addition to serve as a Biometric Signature acquisition device for processing a multi-level authentication procedure to allow access to any specific Web Service of exclusive confidentiality is proposed. To evaluate the lucidness of the proposed procedure, a specific set of domain specifications to work on are chosen and the accuracy of the Biometric face Recognition carried out is evaluated along with the compatibility of the Application developed with different sample inputs. The results obtained are exemplary compared to the existing other devices to suit a larger section of the society through the Internet for improving the security.

We propose an optical security method for object authentication using photon-counting encryption implemented with phase encoded QR codes. By combining the full phase double-random-phase encryption with photon-counting imaging method and applying an iterative Huffman coding technique, we are able to encrypt and compress an image containing primary information about the object. This data can then be stored inside of an optically phase encoded QR code for robust read out, decryption, and authentication. The optically encoded QR code is verified by examining the speckle signature of the optical masks using statistical analysis. Optical experimental results are presented to demonstrate the performance of the system. In addition, experiments with a commercial Smartphone to read the optically encoded QR code are presented. To the best of our knowledge, this is the first report on integrating photon-counting security with optically phase encoded QR codes.