text: With rapidly increasing cyber attacks, network security has become an important issue. To protect ourselves against cyber attacks, the Intrusion Detection System (IDS) has been introduced. In such systems, different kinds of machine learning algorithms play a more and more important role, such as support vector machine(SVM), artificial neural network(ANN), etc. False positive rate and false negative rate, in addition to accuracy, are widely used for the evaluation of IDSs. These indices, however, are often related to each other, which makes it is difficult for us to improve all the indices at the same time. For example, when we try to make the false negative rate decrease to prevent from missing attacks, more normal communications tend to be classified into attacks and the false positive rate may increase, and vice versa. In this study, we propose an ANN based sequential classifier method to mitigate this problem. We design each subclassifier with a low false positive rate, which may lead to high false negative rate. To decrease the false negative rate, the reported negative instances from the former subclassifier are sent to the next one to further check (reclassification). In this way, it can be expected that the false negative rate can also reach an acceptable level. The results of our experiment shows that our proposed method can bring lower false negative rate and higher accuracy, in the mean time the false positive rate is kept at an acceptable level. We also investigated the effect of the number of subclassifiers on detection performance and found that the detection system performed best when using four subclassifiers.
  It is well-known that quadratic extension fields (QEFs) based on optimal extension fields (OEFs) are typically used for supersingular isogeny Diffie-Hellman (SIDH) key exchange protocol. On the other hand, there is a possibility of the performance improvement of SIDH by employing other attractive choices of QEFs with efficient performing arithmetics which are based on all-one polynomial extension fields (AOPFs) and extension fields with normal basis representation (EFNs). Thus, the authors confirm that the applicability of the new candidates of QEFs for SIDH and evaluate SIDH applied the possible choices of QEFs. As a result of the experiment, the authors found that the performances of SIDH applied the QEFs based on AOPF and EFN are comparable to that of the previous QEF. Moreover, one of the QEFs based on EFN result in a new efficient implementation of the SIDH with SIDH-friendly prime given as p= 2^{e_A}3^{e_B}f+1 where e_A, e_B and $f$ are positive integers.
  A cellular automaton (CA) is a well-studied non-linear computational model of complex systems in which an infinite one-dimensional array of finite state machines (cells) updates itself in a synchronous manner according to a uniform local rule. A sequence generation problem on the CA model has been studied for a long time and a lot of generation algorithms has been proposed for a variety of non-regular sequences such as { 2^n | n = 1, 2, 3, ... }, primes, Fibonacci sequences etc. In this paper, we study a real-time sequence generation algorithm for k-th powers of natural numbers on a CA . In the previous studies, Kamikawa and Umeo (2012, 2019) showed that sequences { n^2 | n = 1, 2, 3, ...}, { n^3 | n = 1, 2, 3, ... } and { n^4 | n = 1, 2, 3, ... } can be generated in real-time by one-dimensional CA s. We extend the generation algorithm for { n^4 | n = 1, 2, 3, ... } shown by Kamikawa and Umeo, and present a generation algorithm for the sequence { n^k | n = 1, 2, 3, ... } implemented.
  Various side-channel attacks against elliptic curve cryptography (ECC) have been proposed so far, including simple power analysis, horizontal collision correlation analysis, improving the Big Mac attack, and differential power analysis. Developing countermeasures against such attacks is considered as an important research task in cryptography. They are executed by analyzing power consumption while a device implemented in a cryptosystem performs cryptographic processing. To address this problem, we propose using three atomic blocks serving as the countermeasures against such attacks on ECC over finite fields of characteristic two. Two of them are basic atomic blocks, while the third one is an improved version of these two, having lower computational cost. In this paper, concerning the possibility of more sophisticated side-channel attacks appearing in the future, we propose a threat model based on the atomic blocks that is constructed to be secure for strong side-channel attacks with more powerful abilities.
  One of the reasons why neural networks are used in machine learning is their high expressive power, that is, the ability to express functions. Expressive power of neural networks depends on its structures and is measured by some indices. In this paper, we focus on one of these measures named "expressive number", which is based on the number of data that can be expressed. Expressive numbers enable us to see whether the size of a neural network is suitable for the given training data before we conduct machine learning. However, existing works on expressive numbers mainly target single hidden layer neural networks, and little is known about those with two or more hidden layers. In this paper, we give a lower bound of the maximum expressive number of two hidden layer neural networks and an upper bound of that of multilayer neural networks with ReLU activation function. This result shows the expressive number of two hidden layer neural networks is in O(a_1a_2) where a_1 and a_2 are the numbers of each hidden layer's neurons.
  At PKC 2018, Chen et al. proposed SOFIA, the first MQ-based digital signature scheme having tight security in the quantum random oracle model (QROM). SOFIA is constructed by applying an extended version of the Unruh transform (EUROCRYPT 2015) to the mathcal MQ-based 5-pass identification scheme (IDS) proposed by Sakumoto et al. (CRYPTO 2011). In this paper, we propose an MQ-based 3-pass IDS with impersonation probability of 1/2 and apply the original version of the Unruh transform to it to obtain a more efficient MQ-based digital signature scheme tightly secure in the QROM. The signature size of our digital signature scheme decreases by about 35% compared with SOFIA in the level I of NIST PQC security category, and is supposed to be the shortest among that of MQ-based signatures tightly secure in the QROM.
  
  Recently, COVID19 has been declared a pandemic worldwide due to its infection in more than 200 countries after China, Italy, Spain, USA, India and many more. In India, total 74925 number of COVID19 cases have been reported as on 13 May 20201 and out of which 24887 cases were recovered and 2436 deaths occurred.