The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

Matrix Factorization Techniques for Recommender Systems

Distributed denial of service (DDoS) attacks in cloud computing environments are growing due to the essential characteristics of cloud computing. With recent advances in software-defined networking (SDN), SDN-based cloud brings us new chances to defeat DDoS attacks in cloud computing environments. Nevertheless, there is a contradictory relationship between SDN and DDoS attacks. On one hand, the capabilities of SDN, including software-based traffic analysis, centralized control, global view of the network, dynamic updating of forwarding rules, make it easier to detect and react to DDoS attacks. On the other hand, the security of SDN itself remains to be addressed, and potential DDoS vulnerabilities exist across SDN platforms. In this paper, we discuss the new trends and characteristics of DDoS attacks in cloud computing, and provide a comprehensive survey of defense mechanisms against DDoS attacks using SDN. In addition, we review the studies about launching DDoS attacks on SDN, as well as the methods against DDoS attacks in SDN. To the best of our knowledge, the contradictory relationship between SDN and DDoS attacks has not been well addressed in previous works. This work can help to understand how to make full use of SDN's advantages to defeat DDoS attacks in cloud computing environments and how to prevent SDN itself from becoming a victim of DDoS attacks, which are important for the smooth evolution of SDN-based cloud without the distraction of DDoS attacks.

Software-Defined Networking (SDN) and Distributed Denial of Service (DDoS) Attacks in Cloud Computing Environments: A Survey, Some Research Issues, and Challenges

A blockchain future for internet of things security: a position paper

The proposition of increased innovation in network applications and reduced cost for network operators has won over the networking world to the vision of software-defined networking (SDN). With the excitement of holistic visibility across the network and the ability to program network devices, developers have rushed to present a range of new SDN-compliant hardware, software, and services. However, amidst this frenzy of activity, one key element has only recently entered the debate: Network Security . In this paper, security in SDN is surveyed presenting both the research community and industry advances in this area. The challenges to securing the network from the persistent attacker are discussed, and the holistic approach to the security architecture that is required for SDN is described. Future research directions that will be key to providing network security in SDN are identified.

/pdf/a-survey-of-security-in-software-defined-networks-4jj1eikzsg.pdf

A Survey of Security in Software Defined Networks

https://www.mit.edu/~caoj/pub/doc/jcao_j_cloudsec.pdf

Cloud computing-based forensic analysis for collaborative network security management system

Recommendation can be reduced to a sub-problem of link prediction, with specific nodes (users and items) and links (similar relations among users/items, and interactions between users and items). However, previous link prediction approaches must be modified to suit recommendation instances because they neglect to distinguish the fundamental relations similar vs. dissimilar and like vs. dislike. Here, we propose a novel and unified way to cope with this deficiency, modeling the relational dualities using complex numbers. Previous works can still be used in this representation. In experiments with the MovieLens dataset and the Android software website AppChina.com, the proposed Complex Representation-based Link Prediction method (CORLP) achieves significant performance in accuracy and coverage compared with state-of-the-art methods. In addition, the results reveal several new findings. First, performance is improved, when the user and item degrees are taken into account. Second, the item degree plays a more important role than the user degree in the final recommendation. Given its notable performance, we are preparing to use the method in a commercial setting, AppChina.com, for application recommendation.

/pdf/a-link-prediction-approach-for-item-recommendation-with-dnlxq35voa.pdf

A link prediction approach for item recommendation with complex number

https://www.mit.edu/~caoj/pub/doc/jcao_j_netsec.pdf

Collaborative network security in multi-tenant data center for cloud computing

In this paper a simple but efficient real-time detecting algorithm is proposed for tracking community structure of dynamic networks. Community structure is intuitively characterized as divisions of network nodes into subgroups, within which nodes are densely connected while between which they are sparsely connected. To evaluate the quality of community structure of a network, a metric called modularity is proposed and many algorithms are developed on optimizing it. However, most of the modularity based algorithms deal with static networks and cannot be performed frequently, due to their high computing complexity. In order to track the community structure of dynamic networks in a fine-grained way, we propose a modularity based algorithm that is incremental and has very low computing complexity. In our algorithm we adopt a two-step approach. Firstly we apply the algorithm of Blondel et al for detecting static communities to obtain an initial community structure. Then, apply our incremental updating strategies to track the dynamic communities. The performance of our algorithm is measured in terms of the modularity. We test the algorithm on tracking community structure of Enron Email and three other real world datasets. The experimental results show that our algorithm can keep track of community structure in time and outperform the well known CNM algorithm in terms of modularity.

A Real-Time Detecting Algorithm for Tracking Community Structure of Dynamic Networks

Media streaming is the killer application in current Internet. There are a variety of media streaming techniques in today's Internet, such as RTSP, HTTP live streaming and Adobe Flash etc. HTTP live streaming (HLS) is a popular and most promising technique as the protocol is based on the Internet workhorse protocol i.e. HTTP, and supported by HTML5 and mobile platform. Most of these media streaming techniques are based on TCP/IP, which is built on the traditional host-to-host network architecture. The host-to-host architecture is proved to be inefficient in content distribution with a lot of bandwidth waste, and it is complicated to deploy network service because of TCP/IP's location-dependence. Content Centric Networking (CCN) is a future Internet architecture which is targeted to solve the above problems by location-independent content naming and universal content caching in router. In this paper, we investigate both HTTP live streaming and CCN, and propose a design of CCN live streaming, which is a media streaming technique base on CCN. Finally, we demo our CCN live streaming on Android client, and conduct evaluation experiments. The results demonstrate that the CCN live streaming is a low-cost scheme and much easier to deploy and configure in operation compared with HTTP live streaming.

/pdf/live-streaming-with-content-centric-networking-2t9jegh1bx.pdf

Zhen Chen

Papers

Cloud computing-based forensic analysis for collaborative network security management system

A link prediction approach for item recommendation with complex number

Collaborative network security in multi-tenant data center for cloud computing

A Real-Time Detecting Algorithm for Tracking Community Structure of Dynamic Networks

Live Streaming with Content Centric Networking