Secure DNS from amplification attack by using modified bloom filters

Sattar, Uzma; Naqash, Talha; Zafar, Muhammad Raheel; Razzaq, Kashif; Ubaid, Faisal Bin

doi:10.1109/icdim.2013.6694018

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…Kumbourakis et.al in his article [21] have devised a mechanism that operates on individual-centric mapping phenomenon that mainly works on the request-response scenario of the DNS query wherein the context of the DNS amplification there be an absence of such kind of querying procedure. Weizhang et.al [22] in the context of detecting the anomaly has made use of the data mining based approaches that classify the traffic of the DNS query. UzmaSattar et.al [23] have developed a modified bloom filter based mechanism such that his research study that demonstrates the process in which the filter stores the request generated to the server such that if the response from the server is delivered in specific time period then it allows that particular IP address else the IP address is blocked.…”

Section: Detection and Prediction Of Volumetric Attacksmentioning

confidence: 99%

Prediction of DDoS Attacksusing Machine Learning and Deep Learning Algorithms

Saritha*,

Reddy,

Babu

2019

IJRTE

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With the emergence of network-based computing technologies like Cloud Computing, Fog Computing and IoT (Internet of Things), the context of digitizing the confidential data over the network is being adopted by various organizations where the security of that sensitive data is considered as a major concern. Over a decade there is a massive growth in the usage of internet along with the technological advancements that demand the need for the development of efficient security algorithms that could withstand various patterns of the security breaches. The DDoS attack is the most significant network-based attack in the domain of computer security that disrupts the internet traffic of the target server. This study mainly focuses to identify the advancements and research gaps in the development of efficient security algorithms addressing DDoS attacks in various ubiquitous network environments.

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Section: Detection and Prediction Of Volumetric Attacksmentioning

confidence: 99%

Prediction of DDoS Attacksusing Machine Learning and Deep Learning Algorithms

Saritha*,

Reddy,

Babu

2019

IJRTE

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“…• Black lists. The Bloom filter is used to store a black list to prevent threats such as DDoS attack [27] and amplification attack [33]. However, when an IP address is queried, even if the IP address is legal, the result might be a false positive and the IP address is regarded it as malicious.…”

Section: Introductionmentioning

confidence: 99%

Elastic Bloom Filter: Deletable and Expandable Filter Using Elastic Fingerprints

Shen

et al. 2022

IEEE Trans. Comput.

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The Bloom filter, answering whether an item is in a set, has achieved great success in various fields, including networking, databases, and bioinformatics. However, the Bloom filter has two main shortcomings: no support of item deletion and no support of expansion. Existing solutions either support deletion at the cost of using additional memory, or support expansion at the cost of increasing the false positive rate and decreasing the query speed. Unlike existing solutions, we propose the Elastic Bloom filter (EBF) to address the two shortcomings simultaneously. Importantly, when EBF expands, the false positives decrease. Our key technique is Elastic Fingerprints, which dynamically absorb and release bits during compression and expansion. To support deletion, EBF can first delete the corresponding fingerprint and then update the corresponding bit in the Bloom filter. To support expansion, Elastic Fingerprints release bits and insert them to the Bloom filter. Our experimental results show that the Elastic Bloom filter significantly outperforms existing works.

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Detect the reflection amplification attack based on UDP protocol

Liu

Xiong

Liu

et al. 2015

2015 10th International Conference on Communications and Networking in China (ChinaCom)

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As the DDoS (Distributed Denial of Service) attack becomes more and more popular and the IDS evasion technology continuously renews, the security of the Internet attracts more attention of researchers and attackers. However, the evasion technology against IDS needs a lot of advanced work and has strict requirements for attackers. Thus, the attack to the IDS is paid more attention to because of attacking the targeted host easily. Among different attacks, DDoS attack implements relatively easily, and one typical popular attack frequently seen in large scale DDoS attacks is the reflection amplification attack with a little difference with the DRDOS (Distributed Reflection Denial of Service). To this end, we provide a detection method for this attack specially. And the result of the experiments shows the method is of great theoretical and practical value.

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Secure DNS from amplification attack by using modified bloom filters

Cited by 3 publications

References 7 publications

Prediction of DDoS Attacksusing Machine Learning and Deep Learning Algorithms

Prediction of DDoS Attacksusing Machine Learning and Deep Learning Algorithms

Elastic Bloom Filter: Deletable and Expandable Filter Using Elastic Fingerprints

Detect the reflection amplification attack based on UDP protocol

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