scholarly journals Ask, Acquire, and Attack: Data-Free UAP Generation Using Class Impressions

2018 ◽  
pp. 20-35 ◽  
Author(s):  
Konda Reddy Mopuri ◽  
Phani Krishna Uppala ◽  
R. Venkatesh Babu
Keyword(s):  
Attack Data

TEKNIK PENYEMBUNYIAN PESAN TEKS TERENKRIPSI ALGORITMA MERKLE-HELLMAN KNAPSACK MENGGUNAKAN METODE PIXEL VALUE DIFFERENCING KE DALAM CITRA DIGITAL

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Agung Lestari ◽  
Abdul Sani Sembiring ◽  
Taronisokhi Zebua
Keyword(s):  
Digital Image ◽  
Data Security ◽  
Object Based ◽  
Pixel Value ◽  
Attack Data ◽  
Pixel Value Differencing ◽  
Knapsack Algorithm ◽  
Cryptographic Techniques

Optimization of data security techniques is very necessary so that the data or information that is secured is really safe from attack. Data that has been encrypted based on cryptographic techniques very quickly raises suspicion that the data is confidential or important. Therefore, this technique is better combined with steganography techniques. Utilization of steganography techniques can minimize the attacker's suspicion of data that is secured, because by using steganography data techniques can be hidden on certain objects. This study discusses how to encode a text based on the Merkle-Hellman Knapsack algorithm and the resulting password is hidden in a grayscale digital image as a hiding object based on the pixel value differencing algorithm. This is done to minimize suspicion and make it difficult for attackers to find out confidential or important data.Keywords: cryptography,steganography, merkle-hellmankanpsack, PVD, image

scholarly journals An Efficient Method for Detection of DDoS Attacks on the Web Using Deep Learning Algorithms

2021 ◽  
Vol 10 (4) ◽  
pp. 2821-2829
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Deep Neural Network ◽  
State Of The Art ◽  
Ddos Attacks ◽  
Problem Statement ◽  
Neural Network Approach ◽  
Learning Techniques ◽  
Attack Data ◽  
Deep Learning Neural Network

Recently, DDoS attacks is the most significant threat in network security. Both industry and academia are currently debating how to detect and protect against DDoS attacks. Many studies are provided to detect these types of attacks. Deep learning techniques are the most suitable and efficient algorithm for categorizing normal and attack data. Hence, a deep neural network approach is proposed in this study to mitigate DDoS attacks effectively. We used a deep learning neural network to identify and classify traffic as benign or one of four different DDoS attacks. We will concentrate on four different DDoS types: Slowloris, Slowhttptest, DDoS Hulk, and GoldenEye. The rest of the paper is organized as follow: Firstly, we introduce the work, Section 2 defines the related works, Section 3 presents the problem statement, Section 4 describes the proposed methodology, Section 5 illustrate the results of the proposed methodology and shows how the proposed methodology outperforms state-of-the-art work and finally Section VI concludes the paper.

scholarly journals A Novel Method for Intrusion Detection Based on SARSA and Radial Bias Feed Forward Network (RBFFN)

2013 ◽  
Vol 7 (3) ◽  
pp. 646-653
Author(s):  
Anshul Chaturvedi ◽  
Prof. Vineet Richharia
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Intrusion Detection ◽  
Rbf Neural Network ◽  
Neural Network Approach ◽  
Feed Forward Network ◽  
Machine Learning Approach ◽  
Network Process ◽  
Reinforced Learning ◽  
Attack Data

The Internet, computer networks and information are vital resources of current information trend and their protection has increased importance in current existence. Any attempt, successful or unsuccessful to finding the middle ground the discretion, truthfulness and accessibility of any information resource or the information itself is measured a security attack or an intrusion. Intrusion compromised a loose of information credential and trust of security concern. The mechanism of intrusion detection faced a problem of new generated schema and pattern of attack data. Various authors and researchers proposed a method for intrusion detection based on machine learning approach and neural network approach all these compromised with new pattern and schema. Now in this paper a new model of intrusion detection based on SARAS reinforced learning scheme and RBF neural network has proposed. SARAS method imposed a state of attack behaviour and RBF neural network process for training pattern for new schema. Our empirical result shows that the proposed model is better in compression of SARSA and other machine learning technique.

Effect of Acclimation Temperature and Heat Shock on Vulnerability of Fry of Lake Whitefish (Coregonus clupeaformis) to Predation

1974 ◽  
Vol 31 (9) ◽  
pp. 1503-1506 ◽  
Author(s):  
Thomas G. Yocom ◽  
Thomas A. Edsall
Keyword(s):  
Heat Shock ◽  
Yellow Perch ◽  
Perca Flavescens ◽  
Acclimation Temperature ◽  
Coregonus Clupeaformis ◽  
Lake Whitefish ◽  
Attack Data

Fry of lake whitefish (Coregonus clupeaformis) acclimated to 10, 15, and 18 C were exposed to temperatures of 24.5, 25, and 28 C for 1 min and then immediately returned to water at their acclimation temperature, in test tanks containing yearling yellow perch (Perca flavescens). The number of attacks on the fry and the number captured and eaten in 30 min were recorded in separate tests of shocked and unshocked (control) whitefish.Significantly more whitefish were captured per attack (data for shocked and unshocked fry combined) at 15 and 18 C than at 10 C; and shocked fry were significantly more vulnerable to capture by the perch than were unshocked controls.

scholarly journals A Multivariate Model to Quantify and Mitigate Cybersecurity Risk

Risks ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 61 ◽  
Author(s):  
Mark Bentley ◽  
Alec Stephenson ◽  
Peter Toscas ◽  
Zili Zhu
Keyword(s):  
Numerical Experiments ◽  
Optimal Choice ◽  
Multivariate Model ◽  
Cyber Attacks ◽  
Mitigation Strategies ◽  
Cyber Attack ◽  
Simplifying Assumptions ◽  
Attack Data ◽  
The Cost ◽  
Support Decision Making

The cost of cybersecurity incidents is large and growing. However, conventional methods for measuring loss and choosing mitigation strategies use simplifying assumptions and are often not supported by cyber attack data. In this paper, we present a multivariate model for different, dependent types of attack and the effect of mitigation strategies on those attacks. Utilising collected cyber attack data and assumptions on mitigation approaches, we look at an example of using the model to optimise the choice of mitigations. We find that the optimal choice of mitigations will depend on the goal—to prevent extreme damages or damage on average. Numerical experiments suggest the dependence aspect is important and can alter final risk estimates by as much as 30%. The methodology can be used to quantify the cost of cyber attacks and support decision making on the choice of optimal mitigation strategies.

scholarly journals Synthesizing Nile crocodile Crocodylus niloticus attack data and historical context to inform mitigation efforts in South Africa and eSwatini (Swaziland)

Oryx ◽  
2019 ◽  
Vol 54 (5) ◽  
pp. 629-638 ◽  
Author(s):  
Simon Pooley ◽  
Hannes Botha ◽  
Xander Combrink ◽  
George Powell
Keyword(s):  
South Africa ◽  
Literature Review ◽  
Natural Water ◽  
Historical Context ◽  
Conservation Policy ◽  
Fatality Rate ◽  
Spatial And Temporal Patterns ◽  
Nile Crocodile ◽  
Attack Data ◽  
Natural Water Bodies

AbstractConflicts with wildlife are a major challenge for conservation across Africa, and Nile crocodiles Crocodylus niloticus are allegedly responsible for more attacks on people than any other species; however, there is a lack of data regarding such attacks. We analysed reported attacks on people by Nile crocodiles in South Africa and eSwatini (Swaziland) during 1949–2016, identifying spatial and temporal patterns in attack incidence, as well as victim demographics. Through a literature review and archival searches we identified records of 214 attacks. Most attacks occurred in natural water bodies, with attacks in dams increasing since 2000. Most victims were attacked while swimming or bathing, others while fishing, doing domestic chores, and crossing waterways. There was a significant relationship between gender and activity when attacked. Children (< 16 years old) accounted for 51% of all attacks, with a higher fatality rate compared to adults. Most victims were male (65%), with teenage boys being the largest individual category. We make recommendations for conservation policy and management to mitigate attacks by Nile crocodiles.

Eletriptan for the Treatment of Migraine in Patients with Previous Poor Response or Tolerance to Oral Sumatriptan

Cephalalgia ◽  
2003 ◽  
Vol 23 (6) ◽  
pp. 463-471 ◽  
Author(s):  
M Färkkilä ◽  
J Olesen ◽  
C Dahlöf ◽  
LJ Stovner ◽  
JP ter Bruggen ◽  
...  
Keyword(s):  
Receptor Agonist ◽  
Controlled Trial ◽  
Poor Response ◽  
Free Response ◽  
Onset Of Action ◽  
Double Blind ◽  
Effective Response ◽  
Parallel Group ◽  
Pharmacokinetic Properties ◽  
Attack Data

To determine the tolerability and efficacy of eletriptan in patients who had discontinued oral sumatriptan due to lack of efficacy or intolerable adverse events (AEs) during previous clinical treatment (not a controlled trial). Eletriptan is a potent, selective 5-HT1B/1D receptor agonist with beneficial pharmacokinetic properties compared with sumatriptan. In a double-blind, parallel group, placebo-controlled multicentre study, patients with and without aura ( n = 446) were randomized to 40 mg eletriptan (E40, n = 188), 80 mg eletriptan (E80, n = 171) or placebo ( n = 87) for treatment of up to three migraine attacks. Two-hour headache response, based on first-dose, first-attack data, was 59% for eletriptan 40 mg, 70% for eletriptan 80 mg, and 30% for placebo ( P < 0.0001 for both doses of eletriptan vs. PBO; P < 0.05 for E80 vs. E40). Onset of action was rapid, with 1-h headache response rates significantly superior for E40 and E80 vs. placebo (40%, 48%, 15%; P < 0.0005). Both E40 and E80 were significantly superior to placebo, based on first-dose, first-attack data, for 2-h pain-free response (35%, 42%, and 7%; P < 0.0001). Both E40 and E80 demonstrated significant consistency of response, with headache relief rates at 2 h on at least two of three attacks in 66% and 72% vs. 15% on placebo ( P < 0.001). AEs were mild to moderate in severity and dose related. The most commonly reported AEs included nausea, vomiting, asthenia, and chest symptoms. E40 and E80 produce an effective response in patients who had previously discontinued treatment with sumatriptan due to lack of efficacy or side-effects.

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