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Electronic mail (Email) or the paperless mail is becoming the most acceptable, faster and cheapest way of formal and informal information sharing between users. Around 500 billion mails are sent each day and the count is expected to be increasing. Today, even the sensitive and private information are shared through emails, thus making it the primary target for attackers and hackers. Also, the companies having their own mail server, relies on cloud system for storing the mails at a lower cost and maintenance. This affected the privacy of users as the searching pattern is visible to the cloud. To rectify this, we need to have a secure architecture for storing the emails and retrieve them according to the user queries. Data as well as the queries and computations to retrieve the relevant mails should be hidden from the third party. This article proposes a modified homomorphic encryption (MHE) technique to secure the mails. Homomorphic encryption is made practical using MHE and by incorporating Map Reduce parallel programming model, the execution time is exponentially reduced. Well known techniques in information retrieval, like Vector Space model and Term Frequency -Inverse Document Frequency (TF-IDF) concepts are utilized for finding relevant mails to the query. The analysis done on the dataset proves that our method is efficient in terms of execution time and in ensuring the security of the data and the privacy of the users.

Shrew Attacks or Low Rate Denial of Service(LDoS) Attacks are initiated by sending large amount of packets for very short span of time such that the packet sending rate crosses the link capacity resulting in network congestion. Compared to Denial of Service (DoS) Attack, LDoS attack is very difficult to be detected because, the attacker can maintain low average packet sending rate while executing an attack. If the rate and interval of LDoS attack is properly estimated and executed, this attack can cause a severe threat to the retransmission time out adjustment of TCP and hence reduce its throughput to near zero. This paper proposes a lightweight LDoS filter which can be added with Preferential Dropping RED, to detect and prevent LDoS packets before they reach RED dropping policy. The advantage of this method is that only partial flows need to be analyzed to detect an attack. Simulations done in NS2 shows that, our method can effectively mitigate LDoS attack while maintaining fairness in bandwidth and low average queuing delay.

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