Deduplication is a widely used technology to reduce the storage and communication cost for cloud storage services. For any cloud infrastructure, data confidentiality is one of the primary concerns. Data confidentiality can be achieved via user-side encryption. However, conventional encryption mechanism is at odds with deduplication. Developing a user-side encryption mechanism with deduplication is a vital research topic. Existing state-of-the-art solutions in security of deduplication are vulnerable to dictionary attacks and tag inconsistency anomaly. In this paper, we present SPARK, a novel approach for secure pseudorandom key-based encryption for deduplicated storage. SPARK achieves semantic security along with deduplication. Security analysis proves that SPARK is secure against dictionary attacks and tag inconsistency anomaly. As a proof of concept, we implement SPARK in realistic environment and demonstrate its efficiency and effectiveness.

Since its launch in 2007, Google's open source mobile operating system Android has become the most prominent OS for smartphones. Availability of 3 million Android apps on official repository, Google Play Store, and a not too tightly controlled environment for app developers have added to the popularity of Android and growth of Android devices. This, however, has also provided an opportunity for malware writers to create inroads into Android devices through malicious apps on App stores including Google Play. These malicious apps may access and leak sensitive information such as details of calls, SMS, emails, pictures, contacts, location, password, etc. Loss of this personal data may lead to fraud, financial loss, threatening, etc. Various solutions based on static, dynamic, or hybrid analysis are proposed by state-of-the-art in the last decade. However, malware writers have also come up with ingenious ways of circumventing detection tools. Recent malware deploy threats like obfuscated and encrypted code, dynamic code loading, and reflection, etc. which fail static analysis approaches employing bytecode for analysis. Dynamic analysis is robust against these evasive methods because it executes the application in the controlled environment. In this chapter, we review dynamic analysis techniques for Android and evaluate these experimentally. We discuss various antidetection methods used by recent Android malware to circumvent even dynamic analysis. We compare the effectiveness of various state-of-the-art dynamic analysis techniques against antidetection techniques. With this chapter, we try to highlight issues and challenges concerned to Android malware analysis techniques that require the attention of research community to avoid loss of end user.