Strengthening the Security of Supervised Networks by Automating Hardening Mechanisms

In recent years, the place occupied by the various manifestations of cyber-crime in companies has been considerable. Indeed, due to the rapid evolution of telecommunications technologies, companies, regardless of their size or sector of activity, are now the target of advanced persistent threats. The Work 2035 study also revealed that cyber crimes (such as critical infrastructure hacks) and massive data breaches are major sources of concern. Thus, it is important for organizations to guarantee a minimum level of security to avoid potential attacks that can cause paralysis of systems, loss of sensitive data, exposure to blackmail, damage to reputation or even a commercial harm. To do this, among other means, hardening is used, the main objective of which is to reduce the attack surface within a company. The execution of the hardening configurations as well as the verification of these are carried out on the servers and network equipment with the aim of reducing the number of openings present by keeping only those which are necessary for proper operation. However, nowadays, in many companies, these tasks are done manually. As a result, the execution and verification of hardening configurations are very often subject to potential errors but also highly consuming human and financial resources. The problem is that it is essential for operators to maintain an optimal level of security while minimizing costs, hence the interest in automating hardening processes and verifying the hardening of servers and network equipment. It is in this logic that we propose within the framework of this work the reinforcement of the security of the information systems (IS) by the automation of the mechanisms of hardening. In our work, we have, on the one hand, set up a hardening procedure in accordance with international security standards for servers, routers and switches and, on the other hand, designed and produced a functional application which makes it possible to: 1) Realise the configuration of the hardening;2) Verify them;3) Correct the non conformities;4) Write and send by mail a verification report for the configurations;5) And finally update the procedures of hardening. Our web application thus created allows in less than fifteen (15) minutes actions that previously took at least five (5) hours of time. This allows supervised network operators to save time and money, but also to improve their security standards in line with international standards.

An Analysis on the Inconsistency of the Security Supervision Policy in the Method of Game Theory

This article expounds and proves the basic model of the inconsistency of the security supervision policy and makes an analysis in the method of game theory on the inconsistency of the security transaction-tax-rate policy, concludes that the security supervision department is inclined to increase or decrease the security transaction tax rate, thus points out ways for supervision department to surmount this difficulty.

Research on the supervision system of social security fund ——based on the diversified supervision subject

Social security fund is the foundation of the social security to run, so to strengthen the supervision of social security fund, and promote the sustainable development of it is particularly important. However, the supervision of social security fund of China exists many difficulties at present. In this paper ,the author will be based on the angle of the diversity of regulation, and put forward some relevant suggestions to improve the system of supervision of social security fund.

Adaptive Marine Predator Optimization Algorithm(AOMA)-Deep Supervised Learning Classification(DSLC)based IDS framework for MANET security

Due to the dynamic nature and node mobility,assuring the security of Mobile Ad-hoc Networks(MANET)is one of the difficult and challenging tasks today.In MANET,the Intrusion Detection System(IDS)is crucial because it aids in the identification and detection of malicious attacks that impair the network’s regular operation.Different machine learning and deep learning methodologies are used for this purpose in the conventional works to ensure increased security of MANET.However,it still has significant flaws,including increased algorithmic complexity,lower system performance,and a higher rate of misclassification.Therefore,the goal of this paper is to create an intelligent IDS framework for significantly enhancing MANET security through the use of deep learning models.Here,the min-max normalization model is applied to preprocess the given cyber-attack datasets for normalizing the attributes or fields,which increases the overall intrusion detection performance of classifier.Then,a novel Adaptive Marine Predator Optimization Algorithm(AOMA)is implemented to choose the optimal features for improving the speed and intrusion detection performance of classifier.Moreover,the Deep Supervise Learning Classification(DSLC)mechanism is utilized to predict and categorize the type of intrusion based on proper learning and training operations.During evaluation,the performance and results of the proposed AOMA-DSLC based IDS methodology is validated and compared using various performance measures and benchmarking datasets.

Practical Security Approaches against Border Gateway Protocol (BGP) Session Hijacking Attacks between Autonomous Systems

The border gateway protocol (BGP) is the default inter domain routing protocol used on the internet for exchanging information between autonomous systems. Available literature suggests that BGP is vulnerable to session hijacking attacks. There are a number of proposals aimed at improving BGP security which have not been fully implemented. This paper examines a number of approaches for securing BGP through a comparative study and identifies the reasons why these proposals have not been implemented commercially. This paper analyses the architecture of internet routing and the design of BGP while focusing on the problem of BGP session hijacking attacks. Using Graphical Network Simulator 3 (GNS-3), a session hijack is demonstrated and a solution which involves the implementation of route filtering, policy-maps and route-maps on CISCO routers representing ASes is carried out. In the end, a workable industry standard framework for securing and protecting BGP sessions and border routers from exploitation with little or no modification to the existing routing infrastructure is demonstrated.

Technical methods of national security supervision:Grain storage security as an example

Grain security guarantees national security.China has many widely distributed grain depots to supervise grain storage security.However,this has led to a lack of regulatory capacity and manpower.Amid the development of reserve-level information technology,big data supervision of grain storage security should be improved.This study proposes big data research architecture and an analysis model for grain storage security;as an example,it illustrates the supervision of the grain loss problem in storage security.The statistical analysis model and the prediction and clustering-based model for grain loss supervision were used to mine abnormal data.A combination of feature extraction and feature selection reduction methods were chosen for dimensionality.A comparative analysis showed that the nonlinear prediction model performed better on the grain loss data set,with R2 of 87.21%,87.83%,91.97%,and 89.40%for Gradient Boosting Regressor(GBR),Random Forest,Decision Tree,XGBoost regression on test sets,respectively.Nineteen abnormal data were filtered out by GBR combined with residuals as an example.The deep learning model had the best performance on the mean absolute error,with an R2 of 85.14%on the test set and only one abnormal data identified.This is contrary to the original intention of finding as many anomalies as possible for supervisory purposes.Five classes were generated using principal component analysis dimensionality reduction combined with Density-Based Spatial Clustering of Applications with Noise(DBSCAN)clustering,with 11 anomalous data points screened by adding the amount of normalized grain loss.Based on the existing grain information system,this paper provides a supervision model for grain storage that can help mine abnormal data.Unlike the current post-event supervision model,this study proposes a pre-event supervision model.This study provides a framework of ideas for subsequent scholarly research;the addition of big data technology will help improve efficient supervisory capacity in the field of grain supervision.

Regulation of social forces to participate in social security funds

The social security fund is the masses of＂Survival Money＂ ＂lucky money＂. In order to promote the sustainable development of social security funds, the effective supervision of social security funds become very important. This paper based on the aims to promote the sustainable development of the social security fund and analysis of social forces to participate in the supervision of social security fund situation, put forward to further improve the social security fund supervision and management of effective means.

迈向智能监察:人工智能赋能国家监察的逻辑与进路

新一代人工智能的兴起为国家治理注入新动能,为国家监察工作的数字化、智能化指明方向。人工智能赋能国家监察具有以“数据全覆盖”实现“监察全覆盖”、从人力监督到智能监督等现实价值。受限于国家监察的初创性与人工智能的局限性,国家监察智能化呈现阶段性特征。国家监察的智能化发展围绕数据、算法、算力三大核心要素,实现监察“块数据”构建、面向国家监察的语言模型嵌入及算力资源的优化供给。针对人工智能存在的数据隐私、数据安全等技术性风险,可从人工智能政府采购的制度化与规范化、建构监察对象数据隐私与安全保护机制和人工智能监察应用的纠错与救济机制等方面予以防范和化解。

面向未成年人的人工智能技术发展蓝图——面向未成年人的人工智能技术规范研究(四)

随着ChatGPT等新型人工智能技术的进一步发展,未成年人成长面临着新的风险与挑战,急需构建面向未成年人的人工智能规范体系。文章从人才发展、AI向善和人机共融视角出发,构建了面向未成年人的人工智能技术规范体系模型:“技术内容规范”将基础性、时代性和价值性三个维度的知识结合在一起,旨在从核心素养的角度规范学生能接触到的人工智能技术内容;“技术工具规范”围绕可用性、适用性、安全性、价值观对AI学习工具的设计、开发和应用全过程提出规范要求,旨在从应用监管角度保障未成年人的使用体验;“技术伦理规范”基于以人为本、公平公正、安全可控原则,对人工智能技术伦理治理提出要求,旨在从安全伦理角度促进未成年人、社会、自然和人工智能的和谐共处。

Cyberspace Security Using Adversarial Learning and Conformal Prediction

This paper advances new directions for cyber security using adversarial learning and conformal prediction in order to enhance network and computing services defenses against adaptive, malicious, persistent, and tactical offensive threats. Conformal prediction is the principled and unified adaptive and learning framework used to design, develop, and deploy a multi-faceted?self-managing defensive shield to detect, disrupt, and deny intrusive attacks, hostile and malicious behavior, and subterfuge. Conformal prediction leverages apparent relationships between immunity and intrusion detection using non-conformity measures characteristic of affinity, a typicality, and surprise, to recognize patterns and messages as friend or foe and to respond to them accordingly. The solutions proffered throughout are built around active learning, meta-reasoning, randomness, distributed semantics and stratification, and most important and above all around adaptive Oracles. The motivation for using conformal prediction and its immediate off-spring, those of semi-supervised learning and transduction, comes from them first and foremost supporting discriminative and non-parametric methods characteristic of principled demarcation using cohorts and sensitivity analysis to hedge on the prediction outcomes including negative selection, on one side, and providing credibility and confidence indices that assist meta-reasoning and information fusion.

医院管理建设中智慧医保的SWOT分析

采用SWOT分析智慧医保在医院建设中的优势、劣势、机遇和威胁,了解智慧医保对于医院医保建设的影响,为医院医保精细化管理和便捷医保服务提供参考。依托信息平台给医院建设智慧医保服务和医保基金监管带来机遇,同时给医院医保“粗放型管理”转换为“精细化管理”带来挑战。医疗机构需牢牢抓住时代趋势,依靠自身优势以及信息技术的加持,不断加强医疗实力同时,注重智慧医保的机遇与威胁。医疗机构在享受智慧医保带来福利的同时,也要通过智慧医保更规范医院医保基金监管,通过优化信息系统让患者在实处体验到智慧医保带来的便民服务。

浙江省水利网络安全态势感知监管平台设计与实现

针对浙江省水利网络安全威胁信息感知能力弱、系统风险发现滞后、自动报警和处置响应速度慢等问题,依托数据采集、融合、关联分析、态势预测等态势感知技术,结合机器学习、人工智能、NLP分析及SOAR技术能力,设计一种适应浙江省水利网络安全态势感知的监管平台。监管平台架构设计为安全态势提取层、态势分析层、态势预测层、管理及反馈调节层4个层次,实现实时监控、预警与威胁处置、告警管理、安全态势指数展示、自动应急响应等功能。依托网络安全态势感知平台,可从全局角度发现、识别、分析、预测和处置网络安全威胁,提高自动报警和处置反应速度,增强安全监测和主动防御能力。

区块链系统安全防护技术研究进展

区块链是综合运用密码学、共识机制、分布式网络和智能合约等技术所构建的具有安全和可信特征的新型分布式计算范式,在社会、生产、生活等众多领域都得到了广泛应用,对人民生活产生了重大影响.然而,随着区块链技术及应用的蓬勃发展,各种安全问题频发,严重阻碍了区块链的应用和推广.同时,由于区块链技术、框架仍在不断演进之中,研究人员对区块链安全内涵的核心认知和关键特征理解还未统一,存在较大差异,尚未形成一致的区块链安全框架与体系.当前亟需对区块链系统安全技术发展现状进行梳理,为区块链系统所面临的重点安全问题的研究和突破提供参考.本文结合区块链系统技术框架、围绕区块链安全需求,构建了区块链安全技术框架.在此框架下,从区块链密码支撑技术、区块链平台安全技术和区块链风险评估与安全监管3个方面系统梳理区块链安全关键技术研究现状,囊括了区块链业务流程和区块链系统技术框架所涉及的主要安全机制.最后总结了区块链系统安全技术有待解决的核心问题和发展趋势.

数据跨境双轨制下个人信息出境监管豁免制度的适用与完善

数据跨境新规确立了个人信息出境监管豁免制度,既豁免了申报数据出境安全评估,也豁免了订立个人信息出境标准合同、通过个人信息保护认证。但从我国数据跨境管理双轨制体系来看,这些豁免规则在理解适用上仍存在一系列困惑:符合场景豁免的个人信息是否必然豁免安全评估,一定数量个人信息为何可以豁免同等保护要求出境,过境个人信息豁免、负面清单外豁免的合理限度何在,实践需要与安全关切双重压力下应如何完善豁免。破解这些困惑,就应该明确特定豁免只是豁免保护个人权益的监管机制,厘清个人信息与重要数据关系以明确豁免边界,系统把握过境个人信息豁免和负面清单外豁免,增强数据跨境制度协同性以缓解豁免规则压力。

数字检察的法律定位、运行逻辑及风险规制

数字检察的法律定位是法律监督。该定位是在不违背检察机关宪法地位的基础上,对社会发展的回应,对履职的自省,既与“四大检察”“十大业务”的架构相契合,也与《中共中央关于加强新时代检察机关法律监督工作的意见》对检察机关的定性保持一致。数据与监督各自的规律与准则要求数字检察既要遵循数据的规律性,也不可违背法律监督的准则,且后者起着决定性作用,这是数字检察的运行逻辑。数字检察为数据预测下的监督功能延伸提供了空间,但也带来技术至上、数据不安全、监督越界等潜在风险。为规制风险,必须实施规则之治,统筹推进技术赋能与制度规制。一方面提倡数字正义以促进制度理性,另一方面以保护数据法益实现数据安全,同时,坚持法定主义下的比例原则以厘清权力边界。

生成式人工智能的科技安全风险与防范

生成式人工智能作为科技变革和产业赋能的重要引擎,凭借其强大的自然语言处理能力而具备广泛的应用前景。生成式人工智能具有以下科技安全风险:数字霸权和科技资源垄断等国家安全风险;算法黑箱和算法歧视等算法安全风险;人机互动过程人的自主决策意识丧失的科技伦理风险;跨境流动过程产生的数据和知识产权侵权风险。为构建可信任的生成式人工智能,应共同打造多元共治的生成式人工智能安全风险治理局面,形成风险识别及防范的逻辑闭环。在国家层面应以系统安全观为战略指引,分阶段稳步推进生成式人工智能科技安全立法。在行业层面应以场景理论为导向,分情景开展生成式人工智能的风险识别及其防控。在企业层面应将风险意识植入企业内部文化,探索多模块多层次的风险治理模式,落实企业合规责任。在用户层面应自觉以权利意识和自主决策为基本遵循。

西班牙的情报监督机制及其借鉴

[研究目的]有效的情报监督机制有助于规范情报工作,保障公民权利。20世纪70年代后,西班牙逐渐形成了系统性的情报监督机制。就西班牙情报监督机制进行研究对于我国相关机制的建设具有重要借鉴意义。[研究方法]通过历史分析、规范分析的方法,发现西班牙情报监督机制的发展历程是一个不断改革和优化的过程。现阶段西班牙的情报监督机制包括内部监督、议会监督和司法监督在内的正式监督机制以及以媒体监督为主的非正式监督机制。[研究结论]借鉴西班牙情报监督机制建立过程中的经验和教训,我国应构建多元主体情报监督体系,优化情报监督机制的立法并动态化调整情报监督机制。

数字社会建设中的算法安全风险及其化解策略

建设数字社会是我国社会建设的远景目标。数字社会的运行依托人工智能、区块链、云计算等数字技术。算法则是支撑这些技术运行的基础,是影响数字社会运行的底层逻辑。但受算法漏洞、其他算法的攻击以及算法固有逻辑等的影响,数字社会在运行过程中面临诸如公共权力去中心化危机、算法伦理入侵、算法监控隐忧以及意识形态极化风险等算法安全风险。这不仅会使算法招致逆向的算法攻击,导致算法运行不畅,甚至还会出现算法模型的崩溃,进而削弱政府治理权威,引发社会运行风险,造成国家安全危机。因此,有效克服数字社会的算法安全风险,不仅需要加强算法模型的研发,弥合算法模型漏洞,使算法模型适应不断变化的现实社会运行环境,还需要加强政府数字权威,提升算法的人文关怀,加强对算法的制度规制,以不断提升数字社会质量。

我国医保基金智能监管体系建设的SWOT分析与政策建议

随着医疗体制改革的稳步推进和“十四五”全民医疗保障规划的实施,医保覆盖人数和医保数据信息大幅增加,传统的人工监管手段已不能满足新形势下的要求,我国医保基金亟需建立规范化、科学化、常态化的监管体系。文章采用SWOT分析法,阐述了我国医保基金智能监管的基本格局以及实践经验,面对医保基金监管中跨部门协同不充分、区域发展不平衡、数据共享不畅等问题,从工作制度建设、新技术手段应用、专业化人才培养等角度提出相应的建议。

遮蔽与解蔽:论算法对个人信息安全的影响及其应对——基于媒介可见性视角的展开

[研究目的]全面揭示算法技术应用与普及对个人信息安全保护的负面影响及其内在原因,继而深刻挖掘应对这些负面影响的有效举措,以实现个人信息在算法遮蔽下的安全突围。[研究方法]充分运用多学科交叉的研究方法,从媒介可见性的视角出发,对算法技术应用和个人信息安全的冲突和矛盾展开探讨,并在此基础上着力探寻该冲突的具体化解路径。[研究结论]算法技术的应用与普及,使得个人追求隐匿性的初衷与平台以商业利益为导向的透明度追求发生了逻辑倒置,并对公民个体隐私权、个体自主权和个体拒绝权构成威胁。为解除算法对个体信息安全的不当遮蔽,应当遵循人本主义的理念,从技术端、监管端和用户端着手,通过算法设计与运行、算法监管与问责、算法公众参与保障等方面的机制优化对其予以多维度化解。