Static and Dynamic Integrated Analysis Scheme for Android Malware

The Android platform is the most popular mobile operating system. With the increase of the number of Android users, a lot of security issues have occurred. In order to detect the malicious behaviors for the installed Android Apps, in this paper, we propose an Android malware detecting scheme by integrating static and dynamic analysis methods. We use Androguard and DroidBox to extract the features, and then remove the irrelevant features. Then we employ the support vector machine (SVM) to classify the Android malware and benignware. From the result of our proposed scheme, the proposed integrated static and dynamic analysis scheme with SVM can effectively detect the Android malware.     

Conceptual framework for the security of mobile health applications on Android platform

Mobile Health (mHealth) applications are readily accessible to the average user of mobile devices, and despite the potential of mHealth applications to improve the availability, affordability and effectiveness of delivering healthcare services, they handle sensitive medical data, and as such, have also the potential to carry substantial risks to the security and privacy of their users. Developers of applications are usually unknown, and users are unaware of how their data are being managed and used. This is combined with the emergence of new threats due to the deficiency in mobile applications development or the design ambiguities of the current mobile operating systems. A number of mobile operating systems are available in the market, but the Android platform has gained the topmost popularity. However, Android security model is short of completely ensuring the privacy and security of users’ data, including the data of mHealth applications. Despite the security mechanisms provided by Android such as permissions and sandboxing, mHealth applications are still plagued by serious privacy and security issues. These security issues need to be addressed in order to improve the acceptance of mHealth applications among users and the efficacy of mHealth applications in the healthcare systems. Thus, this paper presents a conceptual framework to improve the security of medical data associated with Android mHealth applications, as well as to protect the privacy of their users. Based on the literature review that suggested the need for the intended security framework, three-distinct and successive phases are presented, each of which is described in a separate section. First, discussed the design process of the first phase to develop a security framework for mHealth apps to ensure the security and privacy of sensitive medical data. The second phase is discussed who to achieve the implementation of a prototypic proof-of-concept version of the framework. Finally, the third phase ending discussed the evaluation process in terms of effectiveness and efficiency for the proposed framework.     

一种基于匹配的Android系统漏洞检测方法

目前Android系统占领了智能移动操作系统的绝大多数份额,然而Android系统的安全问题却令人忧虑,近年来频频爆出高危漏洞,给广大Android用户带来了很大的安全隐患。对Android系统漏洞检测进行了研究,提出了一种基于匹配的快速检测Android系统漏洞的方法,同时设计和实现了一个基于脚本的漏洞扫描工具。实验表明,该工具可有效检测Android系统漏洞,运行效果良好。     

基于Android的通信安防设计

针对当前Android手机用户通过手机访问网络的需求日益增加的情况。提出了增强基于Android手机网络通信的安全性的目标,研究并采用在Android系统上实现拦截和过滤骚扰电话及短信的关键技术。继而给出一种实现Android系统过滤电话和短信黑白名单的防骚扰的方法。通过测试Android系统手机的实时短信以及来电．达到拦截白名单以外所有电话以及短信,或者拦截黑名单内所有的电话以及短信的效果,从而验证Android通信安防系统的方法性和可实现性。     

iOS与Android操作系统的优缺点比较

Android和iOS发展至今已经有着界面融合的趋势,双方都在进行取长补短,已经很难说谁比谁更为优秀。Android系统的开发性特点更能够吸引开发者对其进行开发。而随之带来的是手机病毒和恶意吸费软件在损害着Android手机的用户。但是相对较为廉价的优势使得Android的市场占有率远远高于iOS。而iOS封闭的系统能够带来更为安全的保证,但是用户不得不面对应用选择的制约以及系统使用中的一些不便。     

终端操作系统安全审计功能测评

安卓是基于Linux内核的移动智能终端操作系统,随着移动互联网的发展,安卓得到了广泛的应用.同时,安卓操作系统的安全性变得越来越重要,然而安全审计策略是整个安全策略的重要组成部分,所以有必要对安卓移动智能终端操作系统的安全审计系统进行评估.文章在深入分析了安卓移动智能终端日志系统以及Linux日志系统的基础上,结合信息安全评估标准,提出了安卓移动智能终端操作系统安全审计的评估方法,并设计评估实例来验证评估方法的可行性.     

一种基于Android系统漏洞的通用攻击模型

Android系统中的各类漏洞给Android平台的安全性带来了巨大威胁。漏洞利用技术、移动操作系统安全、Android生态系统安全逐渐成为研究热点。从漏洞利用的角度出发,分析典型系统漏洞的利用过程,提出了一种Android系统漏洞利用的通用模型,并构建了一个漏洞利用有效性评估框架。验证结果表明,该模型能够较好地表述黑色产业链中利用漏洞实施攻击的过程。同时,有效性评估框架可以评估特定漏洞对Android生态系统安全性的影响。     

基于Android平台的网上商城的实现

随着移动通信与Internet的飞速发展及相互融合,GPRS使无线网络高速接入到Internet 成为现实,移动用户从而可以享受到Internet提供的服务.这样,移动终端不再仅是通讯网络的终端,还将成为互联网的终端.首先给出了系统研究背景,对当前手机操作系统发展做了简单的介绍.进而详细地分析了android的特征、架构、以及android应用的构成和工作机制,并对android和其他手机操作系统进行了比较,说明了android在手机操作系统中的优势.本系统主要用于对手机上网用户在线浏览该网站,用户管理员可以对商品信息进行增删改查等功能,用户可以在该网站注册,注册后的用户还可以商品进行购买以及评价.使用该系统很大的提高了用户购买能力.     

基于Android视频客户端的设计

普通的网络视频监控已普及于安防应用和人们的家庭生活,但不能满足人们用手机实时监视的需求。因此,设计An-droid系统下的视频客户端具有了一定的实际意义。介绍了Android操作系统的特点及应用,设计了视频客户端分层的结构,分析了视频客户端各层的关键技术及功能。最后,系统通过性能测试,实现了客户端远程实时视频监视的功能。     

Android下基于用户识别的文件共享设计与实现

针对Android文件共享的安全需要,提出了一种基于用户识别的文件共享应用设计方案,并实现了该方案.该应用分为服务器端和移动终端两部分.服务器端为移动终端提供注册、识别、路由服务.测试表明,该应用能够提供基于用户识别的安全保护,阻止未在服务器端注册的用户使用该应用进行文件共享,达到了设计目的.     

A Secure Path Selection Scheme for Mobile Ad Hoc Network

Mobile ad hoc network is open medium, infrastructure-less and easy to install. Despite these features, mobile ad hoc network is vulnerable to various security attacks. Black hole and gray hole security attacks outrank among all security attacks. This paper proposes a distributed delegation-based scheme, namely, a secure path selection scheme. The proposed scheme identifies and allows only trusted nodes to become part of active path. The simulation results revealed that proposed scheme improved the packet delivery ratio, packet loss rate, throughput by 8% and routing overhead by 5% as compared to other system.

     

Reliable and secure data transfer in IoT networks

With the rapid technological improvements in mobile devices and their inclusion in Internet of Things (IoT), secure key management becomes mandatory to ensure security of information exchange. For instance, IoT applications, such as smart health-care and smart homes, provide automated services to the users with less or no user intervention. As these application use user-sensitive data, ensuring their security and privacy should be paramount, especially during the key management process. However, traditional approaches for key management will not suit well in IoT environment because of the inherent resource constraint property of IoT devices. In this paper, we propose a novel distributed key management scheme for IoT ecosystem. The proposed scheme efficiently provides security to IoT devices by delegating most of the resource consuming cryptographic processing to a local entity. This entity coordinates with other peer entities to provide a distributed key as well as an authentication mechanism to network devices. In particular, the proposed scheme exploits the advantages of mobile agents by deploying them in different subnetworks as and when required: (1) to process the cryptography work for the IoT devices, and (2) to act as an local authenticated entity to perform fast authentication process. To verify the effectiveness and correctness of our proposed scheme, we have simulated it in a large IoT scenario and evaluated against relevant metrics that includes user mobility, certification generation time, and communication overhead.

     

Android应用不可忽视的安全问题

移动互联网的普及和大量新应用的推出,在带给人们方便的同时也带了的很多的安全问题。文章主要针对基于Android系统的应用出现的安全漏洞和Android系统自身存在的安全问题进行了介绍和分析,并提出了应对这些安全问题的建议和应对措施。     

DroidEnemy: Battling adversarial example attacks for Android malware detection

In recent years, we have witnessed a surge in mobile devices such as smartphones, tablets, smart watches, etc., most of which are based on the Android operating system. However, because these Android-based mobile devices are becoming increasingly popular, they are now the primary target of mobile malware, which could lead to both privacy leakage and property loss. To address the rapidly deteriorating security issues caused by mobile malware, various research efforts have been made to develop novel and effective detection mechanisms to identify and combat them. Nevertheless, in order to avoid being caught by these malware detection mechanisms, malware authors are inclined to initiate adversarial example attacks by tampering with mobile applications. In this paper, several types of adversarial example attacks are investigated and a feasible approach is proposed to fight against them. First, we look at adversarial example attacks on the Android system and prior solutions that have been proposed to address these attacks. Then, we specifically focus on the data poisoning attack and evasion attack models, which may mutate various application features, such as API calls, permissions and the class label, to produce adversarial examples. Then, we propose and design a malware detection approach that is resistant to adversarial examples. To observe and investigate how the malware detection system is influenced by the adversarial example attacks, we conduct experiments on some real Android application datasets which are composed of both malware and benign applications. Experimental results clearly indicate that the performance of Android malware detection is severely degraded when facing adversarial example attacks.     

Secure user authentication scheme with novel server mutual verification for multiserver environments

The fast growth of mobile services and devices has made the conventional single‐server architecture ineffective from the point of its functional requirements. To extend the scalability and availability of mobile services to various applications, it is required to deploy multiserver architecture. In 2016, Moon et al insisted that Lu et al's scheme is weak to insiders and impersonation attack, then they proposed a biometric‐based scheme for authentication and key agreement of users in multiserver environments. Unfortunately, we analyze Moon et al's scheme and demonstrate that their scheme does not withstand various attacks from a malicious registered server. We propose a user authentication scheme with server mutual verification to overcome these security drawbacks. The proposed scheme withstands an attack from malicious insiders in multiserver environments. We use a threshold cryptography to strengthen the process of server authorization and to provide better security functionalities. We then prove the authentication and session key of the proposed scheme using Burrows‐Abadi‐Needham (BAN) logic and show that our proposed scheme is secure against various attacks.     

基于Android的流量监控白名单策略

Android安全问题是制约Android应用发展的一个重要因素,分析了目前Android流量监控系统存在的安全缺陷,针对Android恶意软件吸费问题,提出了一种基于白名单的流量监控改进策略.该策略实施在协议层,通过建立白名单数据库实现对应用进程的联网访问控制.实验结果表明,改进后的流量监控系统在当前网络环境下,加强了对应用联网的约束,能有效降低流量损失,增强系统安全性.     

Android vs. IOS: a comparative analysis over mobile operator infrastructures based on crowdsourced mobile dataset

User equipment (UE)’s operating system (OS) and category types are important factors that are affecting the end-user performance in a given mobile network operator (MNO)’s infrastructure. For this reason, fair and statistically accurate observed network performance differences of UE’s OSs based on category types, MNOs or locations can be of interest for mobile telecommunication ecosystem players. This paper’s focus is on performance comparisons of UE OSs (including Android, IOS (iPhone Operating System) and Windows phones) over different UE categories, MNOs and locations based on previously collected end-to-end nationwide crowd-sourced data measurements in Turkey. The analysis results performed in this paper uses statistical comparisons of unpaired observations due to imbalance between number of observations between all OSs and yield insight on how the mobile OS types’ network performances differ using some important Key Performance Indicators (KPIs) such as downlink (DL) speed, latency, jitter and packet loss (PL). The outcome of the analysis indicate that Android devices perform better in terms of DL speed among all MNOs, whereas IOS devices are better in terms of latency values. On the other hand depending on the UE category, the performances of MNOs may vary when IOS and Android OSs are compared based on different KPIs. Additionally, IOS has shown better performance than Android in large geographical areas of Turkey. Finally, the business aspects of performing the proposed statistical OS comparisons from the perspectives of OS developers, MNOs, device manufacturers, and end-users are highlighted.

     

Enhancing cooperative spectrum sensing in cognitive radio ad hoc networks using priority-based two-stage detection model

Cooperation among unlicensed secondary users was more significant in cognitive radio ad hoc networks (CRAHNs). The main challenges of CRAHNs now a day address the main issues of spectrum scarcity and underutilization. Due to the lack of channel sensing, cooperative spectrum sensing (CSS) is the main challenge in CRAHNs. Efficient CSS is more essential to enhance the detection of performance by utilizing the theoretical studies of spatially distributed secondary users (SUs). This paper uses the priority-based two-stage detection model (PBTSDM) to analyze the cooperation strategy among secondary users (SUs) and primary users (PUs). SUs in distributed CSS sense continuously amongst themselves and take unified decision on the presence or absence of PUs by using entropy-based energy detection mechanism. The simulation results reveal that the sensing accuracy in terms of sensing time and energy efficiency (in terms of minimum energy consumption) increased significantly by using the proposed scheme.

     

Intelligent Vehicle Parking System (IVPS) Using Wireless Sensor Networks

Android smartphones are employed widely due to its flexible programming system with several user-oriented features in daily lives. With the substantial growth rate of smartphone technologies, cyber-attack against such devices has surged at an exponential rate. Majority of the smartphone users grant permission blindly to various arbitrary applications and hence it weakens the efficiency of the authorization mechanism. Numerous approaches were established in effective malware detection, but due to certain limitations like low identification rate, low malware detection rate as well as category detection, the results obtained are ineffective. Therefore, this paper proposes a convolutional neural network based adaptive red fox optimization (CNN-ARFO) approach to detect the malware applications as benign or malware. The proposed approach comprising of three different phases namely the pre-processing phase, feature extraction phase and the detection phase for the effective detection of android malware applications. In the pre-processing phase, the selected dataset utilizes Minmax technique to normalize the features. Then the malicious APK and the collected benign apps are investigated to identify and extract the essential features for the proper functioning of malware in the extraction phase. Finally, the android mobile applications are detected using CNN based ARFO approach. Then the results based on detecting the benign and malicious applications from the android mobiles are demonstrated by evaluating certain parameters like model accuracy rate, model loss rate, accuracy, precision, recall and f-measure. The resulting outcome revealed that the detection accuracy achieved by the proposed approach is 97.29%.