National Institute of Standards and Technology における超伝導研究及び生活

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Rfid Handbook Fundamentals And Applications In Contactless Smart Cards And Identification

Distributed denial-of-service is one kind of the most highlighted and most important attacks of today’s cyberworld. With simple but extremely powerful attack mechanisms, it introduces an immense th...

A survey of distributed denial-of-service attack, prevention, and mitigation techniques:

This paper provides an extensive review of the popular multi-objective optimization algorithm NSGA-II for selected combinatorial optimization problems viz. assignment problem, allocation problem, travelling salesman problem, vehicle routing problem, scheduling problem, and knapsack problem. It is identified that based on the manner in which NSGA-II has been implemented for solving the aforementioned group of problems, there can be three categories: Conventional NSGA-II, where the authors have implemented the basic version of NSGA-II, without making any changes in the operators; the second one is Modified NSGA-II, where the researchers have implemented NSGA-II after making some changes into it and finally, Hybrid NSGA-II variants, where the researchers have hybridized the conventional and modified NSGA-II with some other technique. The article analyses the modifications in NSGA-II and also discusses the various performance assessment techniques used by the researchers, i.e., test instances, performance metrics, statistical tests, case studies, benchmarking with other state-of-the-art algorithms. Additionally, the paper also provides a brief bibliometric analysis based on the work done in this study.

/pdf/a-comprehensive-review-on-nsga-ii-for-multi-objective-4ihlcswg3c.pdf

A Comprehensive Review on NSGA-II for Multi-Objective Combinatorial Optimization Problems

Examining the use of YouTube as a Learning Resource in higher education: Scale development and validation of TAM model

Several packet marking schemes have been proposed for DoS/DDoS defence to trace back the attackers to their source One of the major challenge in design of efficient traceback scheme is to minimize the number of packets required for successful traceback DDoS attacks are becoming highly distributed and increasingly sophisticated Even though the net sum of attack packets is high enough to overwhelm the resources at the victim, number of packets originating from individual sources is not so high Hence in order for traceback scheme to be efficient in tracing in case of DDoS attacks, traceback scheme should require minimal number of packets from the attacker to perform IP Traceback In this paper we propose a novel packet marking scheme called Linear Packet Marking (LPM) which requires number of packets which is equal to hop distance between attacker and the victim which is less than 31 [5] We also present a randomized version of LPM called Remainder Packet Marking (RPM) Even though RPM requires a bit more number of packets for successful traceback, it is more robust to certain kind of attacks that are possible on LPM Both the scheme uses IP ID field and TTL values for deciding which router in the path will mark the packet Using extensive simulation we show that our algorithm performs much better than the existing packet marking schemes in term of packets required for successful traceback and in handling large scale DDoS attacks Besides it generates no storage overhead and only a small processing overhead at the intermediate routers

Linear and Remainder Packet Marking for fast IP traceback

The IEEE 1588 precision time protocol (PTP) is a time synchronization protocol with sub-microsecond precision primarily designed for wired networks. In this letter, we propose wireless precision time protocol (WPTP) as an extension to PTP for multi-hop wireless networks. WPTP significantly reduces the convergence time and the number of packets required for synchronization without compromising on the synchronization accuracy.

Wireless Precision Time Protocol

ICMP based IP traceback with negligible overhead for highly distributed reflector attack using bloom filters

In this paper, we develop an intrusion detection system (IDS) based on machine learning. We employ genetic algorithm (GA) along with Support Vector Machine (SVM) for automatically determining the appropriate set of features. The idea is then developed into a fully functional IDS. Experiments of testing the IDS on the benchmark KDD CUP 99 datasets are presented. Results show encouraging performance that opens a avenue for further research.

Genetic algorithm combined with support vector machine for building an intrusion detection system

Social networking sites like Facebook, Twitter and YouTube have changed the way people live. Today we depend heavily on social networking sites for our day to day activities. This paper presents a case study where we research the effect of YouTube on education. We have studied one of YouTube’s most famous education channel called Khan Academy, founded by a MIT graduate. It has a huge collection of around 3,200 video lectures. We perform in-depth study of Khan Academy. We provide results regarding viewer-ship and popularity of these lectures by providing statistics on view count, age of videos, user comments and rating of videos. We also study viewer characteristics like age, gender and location distribution. Overall, we believe that the results presented here are crucial in understanding importance and relevance of social network for education system. The results provide valuable information to educationalists in better using the social media to facilitate quality education.

Ashok Singh Sairam

Papers

Linear and Remainder Packet Marking for fast IP traceback

Wireless Precision Time Protocol

ICMP based IP traceback with negligible overhead for highly distributed reflector attack using bloom filters

Genetic algorithm combined with support vector machine for building an intrusion detection system

Professors – the new YouTube stars: education through Web 2.0 and social network