Malware is pervasive in networks, and poses a critical threat to network security. However, we have very limited understanding of malware behavior in networks to date. In this paper, we investigate how malware propagate in networks from a global perspective. We formulate the problem, and establish a rigorous two layer epidemic model for malware propagation […]
Category: Mca Projects Titles
Malware Propagation in Large-Scale Networks
Malware is pervasive in networks, and poses a critical threat to network security. However, we have very limited understanding of malware behavior in networks to date. In this paper, we investigate how malware propagate in networks from a global perspective. We formulate the problem, and establish a rigorous two layer epidemic model for malware propagation […]
LOSSLESS AND REVERSIBLE DATA HIDING IN ENCRYPTED IMAGES WITH PUBLIC KEY CRYPTOGRAPHY
This paper proposes a lossless, a reversible, and a combined data hiding schemes for ciphertext images encrypted by public key cryptosystems with probabilistic and homomorphic properties. In the lossless scheme, the ciphertext pixels are replaced with new values to embed the additional data into several LSB-planes of ciphertext pixels by multi-layer wet paper coding. Then, […]
Joint Beamforming, Power and Channel Allocation in Multi-User and Multi-Channel Underlay MISO Cognitive Radio Networks
In this paper, we consider a joint beamforming, power, and channel allocation in a multi-user and multi-channel underlay multiple input single output (MISO) cognitive radio network (CRN). In this system, primary users’ (PUs’) spectrum can be reused by the secondary user transmitters (SUTXs) to maximize the spectrum utilization while the intra-user interference is minimized by […]
GDCLUSTER A GENERAL DECENTRALIZED CLUSTERING ALGORITHM
In many popular applications like peer-to-peer systems, large amounts of data are distributed among multiple sources. Analysis of this data and identifying clusters is challenging due to processing, storage, and transmission costs. In this paper, we propose GDCluster, a general fully decentralized clustering method, which is capable of clustering dynamic and distributed data sets. Nodes […]
GDCLUSTER A GENERAL DECENTRALIZED CLUSTERING ALGORITHM
In many popular applications like peer-to-peer systems, large amounts of data are distributed among multiple sources. Analysis of this data and identifying clusters is challenging due to processing, storage, and transmission costs. In this paper, we propose GDCluster, a general fully decentralized clustering method, which is capable of clustering dynamic and distributed data sets. Nodes […]
Efficient Top-k Retrieval on Massive Data
Top-k query is an important operation to return a set of interesting points in a potentially huge data space. It is analyzed in this paper that the existing algorithms cannot process top-k query on massive data efficiently. This paper proposes a novel table-scan-based T2S algorithm to efficiently compute top-k results on massive data. T2S first […]
Effective Key Management in Dynamic Wireless Sensor Networks
Recently, wireless sensor networks (WSNs) have been deployed for a wide variety of applications, including military sensing and tracking, patient status monitoring, traffic flow monitoring, where sensory devices often move between different locations. Securing data and communications requires suitable encryption key protocols. In this paper, we propose a certificateless-effective key management (CL-EKM) protocol for secure […]
Discovery of Ranking Fraud for Mobile Apps
Ranking fraud in the mobile App market refers to fraudulent or deceptive activities which have a purpose of bumping up the Apps in the popularity list. Indeed, it becomes more and more frequent for App developers to use shady means, such as inflating their Apps’ sales or posting phony App ratings, to commit ranking fraud. […]
DETECTION AND RECTIFICATION OF DISTORTED FINGERPRINTS
Elastic distortion of fingerprints is one of the major causes for false non-match. While this problem affects all fingerprint recognition applications, it is especially dangerous in negative recognition applications, such as watchlist and deduplication applications. In such applications, malicious users may purposely distort their fingerprints to evade identification. In this paper, we proposed novel algorithms […]