Cryptanalyzing an image encryption algorithm based on autoblocking and electrocardiography

This paper performs a thorough security analysis of a chaotic image encryption algorithm based on autoblocking and electrocardiography from the view point of modern cryptography. The algorithm uses electrocardiography (ECG) signals to generate the initial key for a chaotic system and applies an autoblocking method to divide a plain image into blocks of certain sizes suitable for subsequent encryption. The designers claimed that the proposed algorithm is “strong and flexible enough for practical applications”. We find it is vulnerable to the known plaintext attack: based on one pair of a known plain-image and its corresponding cipher-image, an adversary is able to derive a mask image, which can be used as an equivalent secret key to successfully decrypt other cipher images encrypted under the same key with a non-negligible probability of 1/256. Using this as a typical counterexample, we summarize some security defects existing in many image encryption algorithms

Identifying functional network changing patterns in individuals at clinical high-risk for psychosis and patients with early illness schizophrenia: A group ICA study.

Although individuals at clinical high risk (CHR) for psychosis exhibit a psychosis-risk syndrome involving attenuated forms of the positive symptoms typical of schizophrenia (SZ), it remains unclear whether their resting-state brain intrinsic functional networks (INs) show attenuated or qualitatively distinct patterns of functional dysconnectivity relative to SZ patients. Based on resting-state functional magnetic imaging data from 70 healthy controls (HCs), 53 CHR individuals (among which 41 subjects were antipsychotic medication-naive), and 58 early illness SZ (ESZ) patients (among which 53 patients took antipsychotic medication) within five years of illness onset, we estimated subject-specific INs using a novel group information guided independent component analysis (GIG-ICA) and investigated group differences in INs. We found that when compared to HCs, both CHR and ESZ groups showed significant differences, primarily in default mode, salience, auditory-related, visuospatial, sensory-motor, and parietal INs. Our findings suggest that widespread INs were diversely impacted. More than 25% of voxels in the identified significant discriminative regions (obtained using all 19 possible changing patterns excepting the no-difference pattern) from six of the 15 interrogated INs exhibited monotonically decreasing Z-scores (in INs) from the HC to CHR to ESZ, and the related regions included the left lingual gyrus of two vision-related networks, the right postcentral cortex of the visuospatial network, the left thalamus region of the salience network, the left calcarine region of the fronto-occipital network and fronto-parieto-occipital network. Compared to HCs and CHR individuals, ESZ patients showed both increasing and decreasing connectivity, mainly hypo-connectivity involving 15% of the altered voxels from four INs. The left supplementary motor area from the sensory-motor network and the right inferior occipital gyrus in the vision-related network showed a common abnormality in CHR and ESZ groups. Some brain regions also showed a CHR-unique alteration (primarily the CHR-increasing connectivity). In summary, CHR individuals generally showed intermediate connectivity between HCs and ESZ patients across multiple INs, suggesting that some dysconnectivity patterns evident in ESZ predate psychosis in attenuated form during the psychosis risk stage. Hence, these connectivity measures may serve as possible biomarkers to predict schizophrenia progression

Cryptanalysis of a Chaotic Image Encryption Algorithm Based on Information Entropy

Recently, a chaotic image encryption algorithm based on information entropy (IEAIE) was proposed. This paper scrutinizes the security properties of the algorithm and evaluates the validity of the used quantifiable security metrics. When the round number is only one, the equivalent secret key of every basic operation of IEAIE can be recovered with a differential attack separately. Some common insecurity problems in the field of chaotic image encryption are found in IEAIE, e.g. the short orbits of the digital chaotic system and the invalid sensitivity mechanism built on information entropy of the plain image. Even worse, each security metric is questionable, which undermines the security credibility of IEAIE. Hence, IEAIE can only serve as a counterexample for illustrating common pitfalls in designing secure communication method for image data.Comment: 9 pages, 6 figures, IEEE Access, 201

Integrating fMRI and SNP data for biomarker identification for schizophrenia with a sparse representation based variable selection method

BACKGROUND: In recent years, both single-nucleotide polymorphism (SNP) array and functional magnetic resonance imaging (fMRI) have been widely used for the study of schizophrenia (SCZ). In addition, a few studies have been reported integrating both SNPs data and fMRI data for comprehensive analysis. METHODS: In this study, a novel sparse representation based variable selection (SRVS) method has been proposed and tested on a simulation data set to demonstrate its multi-resolution properties. Then the SRVS method was applied to an integrative analysis of two different SCZ data sets, a Single-nucleotide polymorphism (SNP) data set and a functional resonance imaging (fMRI) data set, including 92 cases and 116 controls. Biomarkers for the disease were identified and validated with a multivariate classification approach followed by a leave one out (LOO) cross-validation. Then we compared the results with that of a previously reported sparse representation based feature selection method. RESULTS: Results showed that biomarkers from our proposed SRVS method gave significantly higher classification accuracy in discriminating SCZ patients from healthy controls than that of the previous reported sparse representation method. Furthermore, using biomarkers from both data sets led to better classification accuracy than using single type of biomarkers, which suggests the advantage of integrative analysis of different types of data. CONCLUSIONS: The proposed SRVS algorithm is effective in identifying significant biomarkers for complicated disease as SCZ. Integrating different types of data (e.g. SNP and fMRI data) may identify complementary biomarkers benefitting the diagnosis accuracy of the disease

Traffic sign detection using a cascade method with fast feature extraction and saliency test

Automatic traffic sign detection is challenging due to the complexity of scene images, and fast detection is required in real applications such as driver assistance systems. In this paper, we propose a fast traffic sign detection method based on a cascade method with saliency test and neighboring scale awareness. In the cascade method, feature maps of several channels are extracted efficiently using approximation techniques. Sliding windows are pruned hierarchically using coarse-to-fine classifiers and the correlation between neighboring scales. The cascade system has only one free parameter, while the multiple thresholds are selected by a data-driven approach. To further increase speed, we also use a novel saliency test based on mid-level features to pre-prune background windows. Experiments on two public traffic sign data sets show that the proposed method achieves competing performance and runs 27 times as fast as most of the state-of-the-art methods

A possible role of crustacean cardioactive peptide in regulating immune response in hepatopancreas of mud crab

Crustacean cardioactive peptide (CCAP), a cyclic amidated non-apeptide, is widely found in arthropods. The functions of CCAP have been revealed to include regulation of heart rate, intestinal peristalsis, molting, and osmotic pressure. However, to date, there has not been any report on the possible involvement of CCAP in immunoregulation in crustaceans. In this study, a CCAP precursor (designated as Sp-CCAP) was identified in the commercially important mud crab Scylla paramamosain, which could be processed into four CCAP-associated peptides and one mature peptide (PFCNAFTGC-NH2). Bioinformatics analysis indicated that Sp-CCAP was highly conserved in crustaceans. RT-PCR results revealed that Sp-CCAP was expressed in nerve tissues and gonads, whereas the Sp-CCAP receptor gene (Sp-CCAPR) was expressed in 12 tissues of S. paramamosain, including hepatopancreas. In situ hybridization further showed that an Sp-CCAPR-positive signal is mainly localized in the F-cells of hepatopancreas. Moreover, the mRNA expression level of Sp-CCAPR in the hepatopancreas was significantly up-regulated after lipopolysaccharide (LPS) or polyriboinosinic polyribocytidylic acid [Poly (I:C)] challenge. Meanwhile, the mRNA expression level of Sp-CCAPR, nuclear transcription factor NF-kappa B homologs (Sp-Dorsal and Sp-Relish), member of mitogen-activated protein kinase (MAPK) signaling pathway (Sp-P38), pro-inflammatory cytokines factor (Sp-TNFSF and Sp-IL16), and antimicrobial peptide (Sp-Lysozyme, Sp-ALF, Sp-ALF4, and Sp-ALF5) in the hepatopancreas were all up-regulated after the administration of synthetic Sp-CCAP mature peptide both in vivo and in vitro. The addition of synthetic Sp-CCAP mature peptide in vitro also led to an increase in nitric oxide (NO) concentration and an improved bacterial clearance ability in the hepatopancreas culture medium. The present study suggested that Sp-CCAP signaling system might be involved in the immune responses of S. paramamosain by activating immune molecules on the hepatopancreas. Collectively, our findings shed new light on neuroendocrine-immune regulatory system in arthropods and could potentially provide a new strategy for disease prevention and control for mud crab aquaculture

A bibliometric and visualized analysis of preoperative future liver remnant augmentation techniques from 1997 to 2022

BackgroundThe size and function of the future liver remnant (FLR) is an essential consideration for both eligibility for treatment and postoperative prognosis when planning surgical hepatectomy. Over time, a variety of preoperative FLR augmentation techniques have been investigated, from the earliest portal vein embolization (PVE) to the more recent Associating liver partition and portal vein ligation for staged hepatectomy (ALPPS) and liver venous deprivation (LVD) procedures. Despite numerous publications on this topic, no bibliometric analysis has yet been conducted.MethodsWeb of Science Core Collection (WoSCC) database was searched to identify studies related to preoperative FLR augmentation techniques published from 1997 to 2022. The analysis was performed using the CiteSpace [version 6.1.R6 (64-bit)] and VOSviewer [version 1.6.19].ResultsA total of 973 academic studies were published by 4431 authors from 920 institutions in 51 countries/regions. The University of Zurich was the most published institution while Japan was the most productive country. Eduardo de Santibanes had the most published articles, and Masato Nagino was the most frequently co-cited author. The most frequently published journal was HPB, and the most cited journal was Ann Surg, with 8088 citations. The main aspects of preoperative FLR augmentation technique is to enhance surgical technology, expand clinical indications, prevent and treat postoperative complications, ensure long-term survival, and evaluate the growth rate of FLR. Recently, hot keywords in this field include ALPPS, LVD, and Hepatobiliary Scintigraphy.ConclusionThis bibliometric analysis provides a comprehensive overview of preoperative FLR augmentation techniques, offering valuable insights and ideas for scholars in this field